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The European Council completed the legislative procedure to establish the Carbon Border Adjustment Mechanism (CBAM) on April 25, 2023, which will be launched in 2027. The iron and steel sector is the main target of the forthcoming CBAM due to the industry's energy-intensive consumption with high carbon dioxide (CO 2 ) emissions. However, minimal existing research has been conducted in this regard. This study employs GTAP-e 11.0 and TOPSIS models to estimate the effects of CBAM implementation on the major nations around the world from 2027 to 2030, examining countries' GDP, social welfare, iron and steel production, trade balance, and CO 2 emissions to the global environment. This study concludes: (1) The GDP and social welfare of important iron and steel trade partners throughout the world will be significantly impacted by the application of CBAM. Most nations, including those in the EU, will experience negative GDP effects, with China undergoing the most pronounced social welfare declines followed by India. In contrast, the EU27 will benefit the most in terms of social welfare, followed by the US, Japan, and Russia. (2) Iron and steel production will decrease in all countries outside the EU, but it will have a positive impact on the trade balance of most countries. (3) The CO 2 emissions of all countries except for the EU and Japan will decrease, with a positive impact on preventing carbon leakage in the international iron and steel trade. (4) Comprehensive analysis demonstrates that the EU will benefit the most, and China will suffer the most from CBAM application. Based on the above conclusions, this study proposes corresponding policy recommendations., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper investigates the time-varying effects of fossil fuel consumption on CO2 emissions in India utilizing the time-varying cointegration test, allowing for multivariate long-run time-varying cointegration parameter developed by Bierens and Martins (2010) and the time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005). The long-run time-varying coefficients reveal that GDP has a positive and increasing impact on CO2 emissions over time. Moreover, results confirm the polluting effects of all fossil fuels. Besides, the TVP-VAR model findings also demonstrate that changes in income and fossil fuel consumption have a positive and significant impact on environmental degradation. Coal is found to be the most polluting fuel, followed by oil consumption. Furthermore, the time-varying responses show that increased natural gas consumption has the least influence when compared to other fossil fuels on CO2 emissions., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The focus of sustainable development goals (SDGs) is to promote the use of renewable energy so that countries can achieve better environmental quality. However, the progression is plodding, and still, 80% of energy comes mainly from conventional sources in developing countries. The implementation of procedures depends on the political attitudes, political stability, and quality of institutions. India has a diverse political structure ranging from central government to state government to local governments. In the late '80 s, India witnessed a stiff rise in regional and national political parties, which leads more political competition. This paper tries to explain the possible relationship between political competition and CO 2 emission in India. With the application of the time series non-linear ARDL (NARDL) model, this study tries to find the asymmetric relationship between political competition and CO 2 emission. In our empirical model, we also include other important elements of environmental quality like innovation and fossil fuel consumption. Empirical results show that political competition is asymmetrically related to CO 2 emissions in the long run. Fossil fuel consumption and innovation also have a significant relationship with emissions. Based on the results, a few policy recommendations have been discussed., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent years, environmental issues have become controversial, and policymakers are discovering new predictors of carbon emissions. Some economists/researchers have advocated for fiscal decentralization to improve the quality of the environment by offering more financial authority to provincial/local and sub-national governments. Therefore, this work aims to inspect the effect of fiscal decentralization on economic growth and environmental quality in India by taking data from 1996 to 2021. This work applies both ARDL and NARDL econometric models for empirical examination. The findings of this study suggest that expenditure decentralization has asymmetric long-term and short-term consequences on economic growth, and carbon emission in India. The result of the asymmetric ARDL model also indicates that positive and negative shock in expenditure decentralization contrarily affects economic growth and carbon emission. Moreover, the positive and negative shock in revenue decentralization helps in reducing carbon emissions both in the long run and short run in India. These outcomes are useful for policy analysis from the Indian economic policy perspective. The study also laid out potential outcomes that may benefit India's local governments and central government in resolving the issues of economic growth and environmental degradation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

A key strategy for social development and sustainable urban expansion is building sustainable and affordable transport systems. In this study, we aim to test the validity of the environmental Kuznets curve (EKC) hypothesis and reveal the impact of infrastructure investment in transportation systems in China, Turkey, India, and Japan over the period 1995-2020 on environmental degradation. According to dynamic ordinary least squares (DOLS) method analysis, per capita GDP and per capita GDP 3 have a significant positive impact on per capita CO 2 emission, while per capita GDP 2 has a significant adverse impact on per capita CO 2 emission. These results confirm the validity of the N-shaped EKC assumption, while inconsistent with the results of the FMOLS technique, showing that per capita GDP is significantly positive, while per capita GDP 2 and per capita GDP 3 have a significant negative impact on per capita carbon emissions. Moreover, as clarified by the fully modified ordinary least squares (FMOLS) and DOLS methods, road infrastructure investment (RO), aviation infrastructure investment, trade openness, and foreign direct investment (FDI) have significant positive effects, while railway infrastructure investment (RA) has a significant negative effect on per capita carbon emission. Country-level estimates of per capita carbon emission-based DOLS strategies in the model show that only China and Japan have N-shaped EKC hypothesis. Road infrastructure investment, aviation infrastructure investment, and trade openness have significant positive effects, while railway infrastructure investment has a significant negative effect on per capita CO 2 emission in selected central and east Asian countries. The latest electrified rail systems are well thought out and less polluting, so the contribution of rail infrastructure investment to the transport mix can support sustainable and safe transport systems at city center and intercity levels and reduce environmental pollution in central and east Asian countries. Moreover, the implementation of the basic environmental settings of trade agreements should be strengthened to condense the growing impact of free trade on environmental pollution., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green growth refers to the economic growth strategy, which is less detrimental to natural assets, predominantly the environment. Therefore, the main motive of investment and innovation activities should be to attain economic growth while sustainably utilizing natural assets. In this regard, we aim to explore whether ICT diffusion and financial development matter for attaining green economic growth in BRICS economies. The long-run autoregressive distributed lag (ARDL) results show that internet development exerts a positive influence on green growth in four BRICS economies excluding India. However, the long-run estimates of mobile cellular subscriptions are positive only in Russia and China. On the other side, the increase in bank credit and insurance premium also contributes to the long-run green economic growth in almost all BRICS economies. Policymakers should focus on the increased use of ICT in the economy that would replace the physical resources in the economy with information resources. Besides, financial services should be provided to individuals and small and medium enterprises involved in green consumption and production activities., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The 2030 United Nations Sustainable Development Goal (SDG) 13 agenda hinges on attaining a sustainable environment with the need to "take urgent action to combat climate change and its impacts". Hence, this study empirically revisits the debate on the effect of nonrenewable energy and globalization on carbon emissions within the framework of the Kuznets hypothesis using an unbalanced panel data from seven South Asian countries (Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) covering 1980-2019. The variables of interest are carbon emissions measured in metric tons per capita, energy use measured as kg of oil equivalent per capita, and globalization index. To address five main objectives, we deploy four techniques: panel-corrected standard errors (PCSE), feasible generalized least squares (FGLS), quantile regression (QR), and fully modified ordinary least squares (FMOLS). For the most part, the findings reveal that the (1) inverted U-shaped energy-Kuznets curve holds; (2) U-shaped globalization-Kuznets curve is evident; (3) inverted U-shaped turning points for nonrenewable energy are 496.03 and 640.84, while for globalization are 38.83 and 39.04, respectively; (4) globalization-emission relationship indicates a U-shaped relationship at the median and 75th quantile; and (5) inverted U-shaped energy-Kuznets holds in Pakistan but a U-shaped nexus prevails in Nepal and Sri Lanka; inverted U-shaped globalization-Kuznets holds in Bangladesh and Sri Lanka, but U-shaped nexus is evident in Bhutan, Maldives, and Nepal. Deductively, our results show that South Asia countries (at early stage of development) are faced with the hazardous substance that deteriorates human health. Moreover, the non-linear square term of the nonrenewable energy-emissions relationship is negative, which validates the inverted U-shaped EKC theory. Overall, the effect of energy and globalization on carbon emissions is opposite while the consistency at the 75th quantile result indicates that countries with intense globalization are prone to environmental degradation., (© 2022. The Author(s).)

Climate action got attention from the United Nation's Sustainable Development Goals (SDGs). Although a large number of studies are investigating the said phenomenon, however, the literature on the top five responsible countries is unable to evaluate the role of environment-related technologies (ERTs) and institutional quality (IQ). The top five consumption-based carbon dioxide (CBCO 2 ) emitting economies, i.e., China, India, Japan, Russia, and the USA, are considerable stakeholders in this challenge. To fill this void, with the latest data available from 1992 to 2017, short- and long-run relationships are estimated with dynamic common correlated effects estimator and augmented mean group in the framework of EKC hypothesis. Reported results indicate the negative effect of ERTs and IQ towards CBCO 2 , which means that adoption of ERTs and better IQ is supportive in controlling environmental degradation. Findings are also robust to the policy implications for the UN's SDGs., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

It is need of the hour to investigate the impacts of climate parameters on agricultural production in a developing region of South Asia. Therefore, this work attempts to explore the climatic indicators on agricultural production for selected South Asian countries over the annual data of 1961-2016. This study estimates the impacts of rainfall, temperature, rural population, land under cereal production, and CO 2 emissions (ECO 2 ) on agricultural production. For empirical analysis, we applied second-generation unit root tests. After examining the order of integration of time series, we check for the co-integration among the variables. Before the co-integration test, we check for cross-section dependence among the variables. CD and LM tests confirm the existence of cross-section dependence. Afterward, we apply the Westerlund co-integration test to confirm the strong association among the variables. Further, we applied two methods for long-run coefficients of independent variables. Dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) tests were applied to cross-check the findings. Our findings show that rural population and rainfall are negatively associated with agricultural production. Moreover, temperature, land area under cereal production, and ECO 2 are positively associated with agricultural production. Our findings shed light on some important policy implications for South Asian countries., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental sustainability concerns are growing worldwide. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to human capital. This study examines the impact of human capital on CO2 emissions in Brazil, Russia, India, China, and South Africa (BRICS) economies from 1991 to 2019 using a nonlinear panel autoregressive distributed lag approach. Findings show that positive change in education has reduced CO2 emissions, while a negative change in education has increased CO2 emissions in the long run in a group of BRICS. Regarding economy-wise analysis, a positive change in education reduces CO2 emissions in Russia, China, and South Africa in the long run, but a negative change in education has an increasing impact on CO2 emissions in Brazil and China. The results of robustness are also maintained in group and economy-wise empirical analysis. Policymakers should develop the education sector infrastructure in order to support the decrease of CO2 emissions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The relationship between financial development and environmental sustainability has received significant attention in academic discourse. This study explores the crucial role of financial development in addressing the challenge of increasing CO 2 emissions. Using quantile-on-quantile and nonparametric causality-in-quantile methodologies, this research investigates the impacts and causal links between financial market and institution development and CO 2 emissions levels in five major polluting countries from 1990 to 2019. The findings provide strong evidence regarding the impact of financial institutions and financial market development on CO 2 emissions, demonstrating the presence of shocks and nonparametric causality from financial institutions and financial market development to CO 2 emissions quantiles. However, the effects of financial institution shocks and nonparametric causality are diverse and asymmetric across the sample. Positive and negative shocks are observed in India, while only negative shocks are observed in China, the USA, Russia, and Japan. Moreover, the findings reveal that the influence of financial market development on CO 2 emissions varies across countries, with both positive and negative shocks transmitted to CO 2 emissions in the USA, Russia, and Japan, indicating higher volatility in these countries compared to China and India, where only negative shocks are observed. Therefore, our recommendation emphasizes the prioritization of environmentally conscious financial products and the enhancement of the financial system's capacity to mitigate positive shocks contributing to increased CO 2 emissions. Implementing this strategy requires collective efforts to embrace sustainable financial practices that consider the environmental impact of financial activities., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study investigates the effect of financial development and economic growth on ecological footprint by including non-renewable energy consumption and trade openness as additional determinants. For this purpose, annual data of 10 countries with the highest ecological footprint (China, the USA, India, Japan, Brazil, Indonesia, Mexico, Korea, Turkey, and the UK) for the period 1992-2017 is used. The Westerlund and Edgerton (2007) Panel LM bootstrap test results reveal that there is cointegration between the variables. Additionally, the results obtained from the Common Correlated Effects (CCE) coefficient estimator show that financial development, economic growth, and non-renewable energy consumption negatively affect environmental quality by increasing ecological footprint. On other hand, the effect of trade openness on ecological footprint is found to be statistically insignificant. In addition, according to the panel causality test results, a unidirectional causality from financial development to ecological footprint is found while bidirectional causality between economic growth and ecological footprint exists. Therefore, it would be beneficial for policymakers in such countries to direct financial resources to green energy production and consumption and to encourage projects and practices., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study analyzes the relationship between globalization, energy consumption, and economic growth among selected South Asian countries to promote the green economy and environment. This study also finds causal association between energy growth and nexus of CO 2 emissions and employed the premises of the EKC framework. The study used annual time series analysis, starting from 1985 to 2019. The data set has been collected from the World Development Indicator (WDI). The result of a fully modified ordinary least square (FMOLS) method describes a significantly worse quality environment in the South Asian region. The individual country as Bangladesh shows a positively significant impact on the CO 2 emissions and destroys the level of environment regarding non-renewable energy and globalization index. However, negative and positive growth levels (GDP) and square of GDP confirm the EKC hypothesis in this region. This study has identified the causality between GDP growth and carbon emission and found bidirectional causality between economic growth and energy use., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With rapid economic growth, BRICS is facing enormous burdens of carbon emission and severe issues of income inequality. However, behind this economic success, the BRICS economies also face few thoughtful challenges to improve environmental quality by catching up the sustainable development goals. Consequently, the existing empirical research is concerned with the dynamic links between income inequality and CO 2 emissions by using the novel nonlinear ARDL approach, but small attention has been paid to the BRICS in literature. Therefore, we observed that a negative and positive change in income inequality has positive effect on CO 2 emissions in Russia and South Africa in the long run, although a positive change in income inequality has positive effects on CO 2 emissions in Brazil, Russia, and China, while a negative change in income inequality has negative effect on CO 2 emissions in India, Brazil, and Russia in the short run. Hence, the findings value specific attention from policymakers in BRICS economies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The current study is designed to analyze the relationship between, environmental innovations, globalization, financial development, and CO 2 emissions in the South Asian region over the period of 1996 to 2019. In this regard, the role of governance is also incorporated as a moderator along with Environmental Kuznets Curve (EKC) hypothesis. The sample size includes Bangladesh, India, Pakistan, Nepal, and Sri Lanka. The results of the robust least square show the validity of EKC in the sample countries. Environmental innovations show desirable results on CO 2 emissions, while globalization, financial development, and governance are increasing environmental degradation. The role of governance as a moderator is only effective and favorable with environmental innovation. However, in the case of globalization and financial development, governance appeared to be ineffective in lessening the rate of emissions; rather, it contributes to emissions. It clearly shows the missing link in formulating coherent policy to achieve sustainability targets. Therefore, it is desirable to improve the role of governance with respect to environmental policies not only to handle directly environmental issues but also indirectly while promoting the process of globalization and financial development., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to investigate the impacts of traditional and green economic growth on poverty, income inequalities, and environmental degradation in the case of South Asian economies. In this regard, the study collects data for the period 2000 to 2018 from five South Asian economies (Pakistan, India, Sri Lanka, Nepal, and Bangladesh) from world development indicators (WDI). The study applies second-generation unit root test and co-integration technique, CIPS unit root and Westerlund co-integration tests, to establish the stationarity of the series and co-integration relationship among variables. Furthermore, this study utilized dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) models to investigate the long-run empirical estimates. The study finds that both traditional economic growth (GDP) and green economic growth (GGDP) have a negative impact on poverty and inequality; however, GGDP contributes more than traditional GDP to reducing poverty and inequality. Moreover, the study shows that economic growth has a positive long-run impact on environmental degradation while GGDP has a negative and significant long-run association with environmental degradation. The study recommends that policymakers should develop policies to develop green economic growth to save the environment and for the reduction in poverty and income inequalities in south Asian economies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

A key factor in social development and sustainable urban expansion is the establishment of sustainable and affordable transport systems. This study aims to investigate the impact of transport infrastructure investment on environmental degradation and economic growth and to test the validity of the EKC hypothesis in China, India, Russia, and Japan over the period 1995-2020. The results show that GDP has a significant positive effect, and GDP 2 and GDP 3 have significant adverse effects on environmental degradation, respectively. These results confirm the validity of the inverted U-shaped EKC hypothesis in selected emerging Asian economies. Rail infrastructure investment has significant adverse effects, while road infrastructure investment and aviation infrastructure investment have significant positive effects on environmental degradation. Likewise, the impact of investment in transport infrastructure system (roads, rail, and aviation) on economic growth is positive and statistically significant. Country-level estimates confirm the validity of the inverted U-shaped EKC hypothesis in China, India, and Russia, while the N-shaped EKC is only valid in Japan. Investments in rail infrastructure based on modern rail systems that run on electricity are believed to be less polluting in the transport mix, help create sustainable and safe transport systems, and reduce emissions at the urban and intercity levels in emerging Asian countries. In addition, the growing impact of free trade on environmental pollution should be strengthened to harmonize the strict enforcement of environmental conditions dominated by trade agreements., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The trade-off between environmental degradation and unemployment has been recently termed as Environmental Philips Curve (EPC). This research attempts to investigate the presence of EPC in the Indian context utilizing time series data for the period 1990-2019. Besides contributing to the meagre empirical literature on this issue, the present study makes a novel contribution by introducing a gender dimension to this investigation. In particular, this study investigates whether the nexus between environmental degradation and unemployment is different for men and women. We examine the presence of the EPC by estimating a model that considers growth in CO 2 emission as a function of economic growth, trade openness, and gender segregated unemployment rates. Our findings based on autoregressive distributed lag, fully modified ordinary least squares, and dynamic ordinary least squares estimators generate robust evidence for a negative impact of male unemployment rate on growth in CO 2 emission that validates the existence of the Environmental Philips Curve for the male unemployment rate. However, there is no trade-off between environmental quality and women's employment. In fact, the results point to a favourable effect of reduction in female unemployment on environmental quality. The results of the Block Exogeneity test indicate a unidirectional causality from male unemployment rate to environmental degradation. However, a bidirectional causal relationship exists between female unemployment and environmental degradation. The existence of a trade-off between environmental quality and male employment suggests that India is yet to find viable technologies that can curtail pollution without compromising its livelihood. An optimistic conclusion emanating from our findings is the existence of a virtuous cycle between female employment and environmental quality. An integrated approach to improve environmental quality and increase women's economic activity may facilitate a speedy realization of sustainable development goals for India as both the goals complement and reinforce each other., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Irrespective of the vast array of empirical evaluations pertaining to the environmental Kuznets curve (EKC) hypothesis, both for India and other countries, previous studies, amid divergent submissions, inadvertently failed to highlight the relevant threshold that ensures significant reductions in environmental decay. Additionally, the implications of environmental-control technology on environmental quality are also lacking mostly in the context of Indian economy. Thus, this study enlists environmental-control technology and other relevant factors over the period 1980-2018 and employs the novel multiple threshold nonlinear ARDL technique, a model rarely applied in previous studies for updated empirical narratives. Accordingly, the empirical evidence rectifies that the variables converged to long-run equilibrium. Furthermore, from the tercile partial deviations, it is established that at the middle threshold (GDP 2 ), pollution shrinks more significantly amid rising income, thereby validating the EKC hypothesis for India. Likewise, environmental-control technologies provided only a short-term insignificant carbon neutrality pathway, whereas they provided long-term insignificant emission increasing effects. This implies that the depth of such technology in India is inadequate to invoke cleaner environments at all times. Likewise, energy consumption and urbanization processes are significant environmental polluters, while trade openness provides insignificant long- and short-term carbon emission effects. Against this background, economic growth within the middle threshold promises a more sustainable environment amid rising national income at all times. Moreover, given its short-term outcomes, strengthening the depth of environmental-control technology is imperative to ensure a long-lasting clean environment in India.W2 ), pollution shrinks more significantly amid rising income, thereby validating the EKC hypothesis for India. Likewise, environmental-control technologies provided only a short-term insignificant carbon neutrality pathway, whereas they provided long-term insignificant emission increasing effects. This implies that the depth of such technology in India is inadequate to invoke cleaner environments at all times. Likewise, energy consumption and urbanization processes are significant environmental polluters, while trade openness provides insignificant long- and short-term carbon emission effects. Against this background, economic growth within the middle threshold promises a more sustainable environment amid rising national income at all times. Moreover, given its short-term outcomes, strengthening the depth of environmental-control technology is imperative to ensure a long-lasting clean environment in India., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research examines the linkage between financial risk and carbon emissions using a quarterly dataset spanning from 1991 to 2019 for top carbon emitting countries. To achieve the study objective, this study apply quantile-on-quantile regression (QQR), the quantile regression (QR) approach for robustness check, and the nonparametric predictive test that identifies causality in mean and variance. Empirical findings from the QQR technique disclose the following: (i) financial risk decreases carbon emissions in the USA, Russia, Germany, and Canada; (ii) in China, India, Japan, Brazil, and Indonesia, financial risk enhances carbon emissions (iii) while we find mixed reactions in the case of South Korea. The outcomes of the conventional quantile regression also confirm the QQR outcomes, while that of nonparametric causality discloses evidence of causality in majority of quantiles from financial risk to carbon emissions. Based on these empirical outcomes, policymakers in the financial risk-induced-environmental degradation regions should consider implementing policies or reforms that would keep financial systems sound, in order to prevent shocks to the environment, and its attendant multiplier impact on the environmental sustainability targets implemented to protect both the immediate and the future generations., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Over the period 1980-2016, this study looks into the causal relations between carbon dioxide (CO 2 ) emissions, energy consumption (EC), foreign direct investment (FDI), and gross domestic product (GDP) in five South Asian countries (Bangladesh, India, Nepal, Pakistan, and Sri Lanka). To achieve the research objectives, panel unit root tests, panel co-integration, autoregressive distributed lag model, and Granger causality tests are used. In the long run, GDP has a positive impact on CO 2 emissions, while squared GDP has a negative impact, confirming the framework of the environmental Kuznets curve (EKC) in Pakistan and Sri Lanka. However, in the short run along with these two countries, Bangladesh also confirms the EKC hypothesis. Among these five countries, Bangladesh and Nepal support the pollution haven hypothesis, but India, Pakistan, and Sri Lanka support the FDI halo hypothesis. The EC has a large positive impact on CO 2 emissions across five countries. In the long run, the Granger causality test confirms one-way causation from EC to CO 2 emissions and bidirectional causality of FDI and CO 2 . These countries might encourage clean energy technology through FDI without jeopardizing GDP and environmental quality. The findings of the study provide a guideline for these countries to reduce CO 2 emissions, achieve a long-term green GDP, and combat global warming., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We examine the linkages of economic freedom (ECF), energy use, and CO 2 emissions in selected South Asian countries of Pakistan, India, Bangladesh, and Sri Lanka. Annual data from 1995 to 2018 are analyzed by employing second-generation methodologies. Cross-sectional autoregressive distributed lag (CS-ARDL) is used because this method incorporates the cross-sectional dependence among the data. This work uses three models, where the dependent variables are gross domestic product (GDP), CO 2 emissions, and energy use. The findings reveal that ECF and energy use contributes to more economic development. ECF is improving air quality by lowering CO 2 emissions. The findings suggest that these countries need to increase the percentage of renewable energy in their energy generation mix. At the same time, there is a need to integrate ECF with environmental awareness programs. This will not only increase air quality but also increase economic growth. GDP is found to be dependent on energy use; however, increased energy use from non-renewable also contaminates the environment. Therefore, South Asian countries need to invest more in research and development projects to promote renewable energy., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO 2 ) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO 2 emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO 2 emissions; correspondingly, this study builds a model for CO 2 emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO 2 emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO 2 emissions. Finally, this study forecasted a CO 2 emission trend, with a slowdown predicted in China by 2022; however, CO 2 emission's reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO 2 emissions without harming economic development., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent literature, scholars discussed the role of export diversification in environmental quality. However, most studies analyzed the role of export diversification in influencing carbon dioxide emissions with mixed results. However, since carbon dioxide emissions specifically capture the environmental effects of energy utilization, a change in the level of carbon dioxide emissions cannot be regarded as a comprehensive measure of environmental deterioration. Also, many previous studies use the original form of the Theil index to measure export diversification, and during the interpretation of the results, they disregard the fact that the lower value of the Theil index indicates higher diversification and vice versa. In this context, to address these gaps in the literature, a study on the contribution of export diversification in ecological footprint is necessary to understand the ecological impacts of export diversification. Therefore, this study analyzes the contribution of export diversification in ecological footprint covering the period between 1965 and 2017 using the STIRPAT model in the context of India which is required to fulfill the demands for resources of over 1.3 billion people. The study relied on the environmental Kuznets curve hypothesis framework to understand the role of export diversification in ensuring environmental sustainability. Using the newly developed Augmented ARDL test, the study established that variables of interest are cointegrated. In the long-run estimation, export diversification reduces the ecological footprint of India and helps establish the inverted-U-shaped nexus between ecological footprint and economic growth. Thus, the environmental Kuznets curve hypothesis was evidenced to hold for India. This important finding divulges that India can control the level of environmental footprints, and therefore decrease environmental degradation by continuously increasing export product diversification. Also, India is on the right path to achieve a reduction in ecological footprint associated with more development when accounting for export diversification in the model. Moreover, energy intensity boosts environmental deterioration, while population density reduces it. Finally, the study discusses strategies to achieve environmental sustainability through increasing export diversification., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper compares four prediction methods, namely random forest regressor (RFR), SARIMAX, Holt-Winters (H-W), and the support vector regression (SVR), to forecast the total CO2 emission from the paddy crop in India. The major objective of this study is to compare these four models and suggest an effective model for the prediction of total CO2 emission. Data from 1961 to 2018 has been categorised into two parts: training and test data. The study forecasts total CO2 emission from paddy crops in India from 2019 to 2025. A comparison of mean absolute percentage error (MAPE) and the mean square error (MSE) highlights the differences in accuracy among the four models. The mean absolute percentage eror (MAPE) and the mean square error (MSE) for the four methods are RFR (MAPE: 5.67; MSE: 549,900.02), SARIMAX (MAPE: 1.67; MSE:70,422.35), H-W (MAPE:0.75; MSE:16,648.58), and SVR (MAPE: 0.91; MSE: 17,832.4). The values of MAPE and MSE with the Holt-Winters (H-W) and the support vector regression (SVR) are relatively low as compared to SARIMAX and RFR. Based on these results, it can be inferred that H-W and SVR were found suitable models to forecast the total CO2 emission from paddy crops. Holt-Winters model predicted 14,364.97 for the year 2025, and SVR predicted 13,696.67 for the year 2025. The decision-maker can use these predictions to build a suitable policy for the future. This approach can be contrasted with other forecasting methods, such as the neural network, and train the model to achieve better forecast accuracy., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The objective of this study is to contribute to the existing debate of green economic growth by empirically investigating the role of cleaner energy production, green innovation, and green trade in green economic growth in the context of South Asian countries. For this purpose, the study collects the data of South Asian Economies for 2000-2018 from different sources such as world development indicators (WDI), International Energy Statistics (IES), and Organization for Economic Co-operation and Development (OECD) statistics. The study applied Pesaran's (2007) second-generation unit root test to test the stationarity of the data. Wasteland's (2007) test of cointegration was applied to examine the long-run association among modeled variables. The study confirmed the long-run association among modeled variables that turn to be stationary at the first differences. Moreover, the study applied fully modified least square (FMOLS) and dynamic least square (DOLS) to estimate the empirical results of the study. Results of the study show that the production of clean energy, green innovation, and green trade positively contributes to the green economic growth of South Asian Economies Graphical abstract., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon dioxide (CO 2 ) emissions from the cement industry account for 26% of the total industrial emissions, and the need to develop low-carbon techniques within the cement industry is extremely urgent. Low-carbon projects and technologies for the cement industry in different regions and countries have been thoroughly reviewed in this manuscript, and the low-carbon development concept for each county has been analyzed. For developing countries such as China and India, energy saving and efficiency enhancement are currently the key points, while for developed countries and regions such as Europe, more efforts have been focused on carbon capture, utilization, and storage (CCUS). Global CCUS projects have been previously conducted, and the majority of CCUS projects are currently performed in Europe where major projects such as the CEMCAP, CLEANKER, and IEILAC projects represent the latest research progress in cement production technologies and low-carbon technologies for the global cement industry. The development of low-carbon cement technologies has changed from focusing on the end point to instead focusing on the source and process through the exploration of hydrogen and solar energies, and more disruptive and original technologies are expected to be developed, particularly in the cement industry in China., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

China, India, and the USA are the countries with the highest energy consumption and CO 2 emissions globally. As per the report of datacommons.org , CO 2 emission in India is 1.80 metric tons per capita, which is harmful to living beings, so this paper presents India's detrimental CO 2 emission effect with the prediction of CO 2 emission for the next 10 years based on univariate time-series data from 1980 to 2019. We have used three statistical models; autoregressive-integrated moving average (ARIMA) model, seasonal autoregressive-integrated moving average with exogenous factors (SARIMAX) model, and the Holt-Winters model, two machine learning models, i.e., linear regression and random forest model and a deep learning-based long short-term memory (LSTM) model. This paper brings together a variety of models and allows us to work on data prediction. The performance analysis shows that LSTM, SARIMAX, and Holt-Winters are the three most accurate models among the six models based on nine performance metrics. Results conclude that LSTM is the best model for CO 2 emission prediction with the 3.101% MAPE value, 60.635 RMSE value, 28.898 MedAE value, and along with other performance metrics. A comparative study also concludes the same. Therefore, the deep learning-based LSTM model is suggested as one of the most appropriate models for CO 2 emission prediction., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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 CO 2 emissions, but HC served as a stimulant for environmental quality enhancement by declining the level of CO 2 emissions. In contrast, GDP growth and URB strengthen the CO 2 emissions levels. Moreover, in VECM framework, estimated findings reveal that the covariables Granger-cause EF and CO 2 emissions, inferring that causality flows asynchronously from its covariables to EF and CO 2 . Impulse response function (IRF) revealed that the responses in EF and CO 2 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., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The current study projects the increase in surface temperature and CO 2 emissions using the EGM (1,1, α, θ) grey model for the six most significant CO 2 contributing countries, namely China, the USA, India, Russia, Japan, and Germany. The study uses time series data for surface temperature (in degree celsius) from 2010 to 2020, and CO 2 emission (metric tons per capita) data from 2009 to 2019. The empirical results show a downward trend in CO 2 emissions from Japan, Germany, the USA, and Russia by 2028. However, in the same time period, CO 2 emissions are expected to increase for India and remain nearly constant for China. This study indicates an increase in surface temperature at a significant rate in all the 6 countries: by 6.70 °C for China, 7.52 °C for Germany, 2.95 °C for India, 2.66 °C for Japan, 3.61 °C for Russia, and 13.48 °C for the USA by the end of 2028. The study compares the EGM (1,1, α, θ) grey model with the general EGM (1,1) grey model and finds that the EGM (1,1, α, θ) model performs better in both in-sample and out-of-sample forecasting. The paper also puts forward policy suggestions to mitigate, manage, and reduce increases in surface temperature as well as CO 2 emissions., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

From the perspective of ecological environmental protection, higher education can not only train a large number of professionals dedicated to environmental protection for the construction of environmental quality, but more importantly, it can promote the improvement of the quality of ecological civilization in the whole society, so as to achieve the effect of indirectly improving environmental quality. BRICS economies, as the most important economies in the world, have an impact on the development of the world in many aspects. However, under the guidance of the concept of sustainable development, whether the environmental quality of BRICS economies meets the standards has also become the focus of scholars. Starting from the sustainable development path, this paper summarizes the model of environmental education in BRICS national higher education. At the same time, through the establishment of the BRICS environmental quality assessment system, the environmental quality of the BRICS countries after the implementation of environmental education was assessed based on the content of the sustainable development system. This paper performs matrix operations on the weight values of the indicators at all levels and the membership vector to obtain a 4 × 4 matrix, that is, the evaluation result Q of each indicator is [0.050, 0.200, 0.113, 0,011], which proves that the evaluation results in this paper are basically reasonable. It can be seen that in terms of forest coverage and environmental protection areas, environmental education in higher education has the deepest impact on Russia. In terms of carbon emissions, South Africa benefits the most from environmental education in higher education, so each country should take corresponding actions according to different environmental assessment results., Competing Interests: The author declares no conflicts of interest., (Copyright © 2022 Miao Guo.)

This paper conceptualises the factors responsible for water quality change in the aquifer on the basis of a study of flow dynamics, hydro-chemical, and bacteriological processes in a gypsum, lignite, oil, and gas-rich Barmer sedimentary basin in India. The change in colouration, odour, and presence of gases in flowing wells has been analysed. The study revealed that such a change in the quality of the water is mainly occurring in those wells that are located in the transition zone between unconfined and confined parts of the same aquifer. The field and lab analyses have further revealed the presence of pyrites, other iron-rich minerals, hydrogen sulphide (H2S), carbon dioxide (CO2), and methane (CH4) gases in the aquifer. The study suggests that changes in flow dynamics, hydro-chemical equilibrium, and microbiological processes like sulphate reduction, methanogenesis, and reverse methanogenesis are responsible for such changes in groundwater quality. The change in water quality in the unconfined parts of the aquifer is mainly due to in situ pyrite dissolution, bacteria-mediated sulphate reduction, or reverse methanogenesis taking place in the nearby confined parts of the aquifer. The presence of CH4 in non-flowing wells or while drilling new wells appears to be biogenic in nature and has migrated from deeper, confined parts of the same aquifer. The overexploitation of the aquifer has changed the flow dynamics and hydro-chemical equilibrium within the aquifer, and it has prompted the migration of gases from deeper, confined parts of the same aquifer. The water quality change is more prominent in the transitional zone between unconfined and confined parts of the aquifer. [ABSTRACT FROM AUTHOR]

Top-down modeling estimates are among the most reliable information available on the CO 2 fluxes of the earth system. The inadequate coverage of CO 2 observing stations over the tropical regions adds a limitation to this estimate, especially when the satellite XCO 2 is strictly screened for cloud contamination, aerosol, dust, etc. In this study, we investigated the potential benefit of a global ground-based observing station network, 17 newly proposed stations over India, and global satellite XCO 2 in reducing the uncertainty of terrestrial biospheric fluxes of Tropical Asia-Eurasia in TransCom cyclo-stationary inversion. The data from selected 80 global ground-based CO 2 observation stations, together with two additional stations from India (i.e., Cape Rama and Sinhagad) and satellite XCO 2 , helps to reduce the temperate Eurasian terrestrial flux uncertainty by 23.8%, 26.4%, and 36.2%, respectively. This further improved to 54.7% by adding the newly proposed stations over India into the inversion. By separating the Indian sub-continent from temperate Eurasia (as inspired by the heterogeneity in the terrestrial ecosystems, prevailing meteorological conditions, and the orography of this vast region), the inversion evinces the capacity of existing CO 2 observations to reduce the Indian terrestrial flux uncertainty by 20.5%. The largest benefit (70% reduction of annual mean uncertainty) for estimating Indian terrestrial fluxes could be achieved by combining these global observations with data from the newly proposed stations over India. The existing two stations from India suggest Temperate Eurasia as a mild source of CO 2 (0.33 ± 0.57 Pg C yr -1 ), albeit with prominent anthropogenic influences visible in these two stations during the dry seasons. This implies that the proposed new stations should be cautiously placed to avoid such effects. The study also finds that the newly proposed stations over India also have an impact in constraining nearby oceanic CO 2 fluxes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

This paper scrutinizes the asymmetric impact of education and education expenditure on clean energy consumption and CO2 emissions in the BRICS economies using annual data for the period 1991-2019. The analysis employs a nonlinear autoregressive distributed lag (ARDL) framework. Findings unfold that a positive change in education contributes to increasing clean energy consumption in Brazil, Russia, India, and China. This finding implies that a negative change in education contributes to reducing clean energy consumption in Brazil, Russia, and India in the long run. Nonetheless, a positive change in education expenditure increased the clean energy consumption in Brazil, Russia, and India, while it has decreased in South Africa. On the dark side, a negative change in education expenditure degrades clean energy consumption in India, China, and South Africa in the long run. The asymmetric empirical results of CO2 emissions are mixed, economy-specific, and vary across group countries in the long run. We find that the education and education expenditure has long-run asymmetric effects in BRICS industries. Thus empirical findings give us robust policy implications for BRICS economies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The role of government size and digitization in the process of environmental quality is a matter of considerable debate in the field of environmental economics. BRICS economies have suffered from environmental pollution. This paper scrutinizes that how CO 2 emissions respond to government size and digitization in BRICS economies. Empirical estimates of the ARDL approach show that government size has a positive impact on CO 2 in Brazil, India, and China, while negative impact on CO 2 in Russia in the long run. The long-run estimates reveal a negative and significant effect of digitization on CO 2 in Brazil, India, and China. Education and e-learning activities have a favorable and crucial role played in environmental quality in Brazil, India, and China. Based on these findings, BRICS authorities should improve the efficiency of government expenditures and invest more in digitization to improve the quality of the environment., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The development of globalization has separated the production and consumption of products spatially, and the international trade of products has become a carrier of embodied carbon trade. This paper adopted the perspective of value-added trade to calculate the amount of embodied carbon trade of China from 2006 to 2015 and perform a structural decomposition analysis of the changes in China's embodied carbon trade. This study found that: (1) China's embodied carbon exports are much larger than its embodied carbon imports, and there are differences between countries. China imported the largest amount of embodied carbon from South Korea, and it exported the largest amount of embodied carbon to the United States. (2) The structural decomposition analysis shows that changes in the value-added carbon emission coefficient during the study period would have caused China's embodied carbon trade to decrease, and changes in value-added trade would have caused China's embodied carbon trade to increase. Therefore, countries trading with China need to strengthen their cooperation with China in energy conservation, emission reduction, and product trade. In order to accurately reflect China's embodied carbon trade, it is necessary to calculate embodied carbon trade from the perspective of value-added trade., Competing Interests: The authors have declared that no competing interests exist.

Finding the essential factors driving carbon emissions is vital for the carbon reduction policy-making. Different from the existing research, this paper studied the separate influence of internal and external input structural changes on global carbon emissions. We applied structural decomposition analysis (SDA) to decompose the global carbon emission change into six factors: namely, the carbon emission intensity, the domestic input structure, the international input structure, consumption pattern, consumption volume and population. The results firstly showed that the contributions of different factors to global carbon emissions changed over time. In recent five years, structural changes of domestic inputs became the principle driver of decrease in global carbon emissions. Secondly, the results showed that there were significant differences for countries in their factors for carbon emissions. In India and Russia, domestic input structural change was the major contributor to the decrease in carbon emissions. In Japan and Germany, the most important factor for the increase in carbon emissions was the international input structure. Finally, the results showed the factors for carbon emission changes were correlated to economic development. The international input structural changes significantly increased carbon emissions in high-income countries. Our findings suggested that some countries such as India and Russia, improving the usage efficiency of domestic carbon-intensive products would help reducing carbon emissions. For most high-income countries such as Japan and Germany, they should reduce the dependence on the imported carbon-intensive products by turning the external input sources to countries with technology advantages. In addition, technology exportation of high-income countries would also be beneficial for the global carbon reduction., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Devising effective national-level climate action plans requires a more detailed understanding of the regional distribution of sources and sinks of greenhouse gases. Due to insufficient observations and modelling capabilities, India's current carbon source–sink estimates are uncertain. This study uses a high-resolution Lagrangian transport model to examine the potential of available CO 2 observations over India for inverse estimation of regional carbon fluxes. We use four different sites in India that vary in the measurement technique, frequency and spatial representation. These observations exhibit substantial seasonal (7.5 to 9.2 ppm) and intra-seasonal (2 to 12 ppm) variability. Our modelling framework, a high-resolution Weather Research and Forecasting Model combined with the Stochastic Time-Inverted Lagrangian Transport model (WRF–STILT), performs better in simulating seasonal (R2=0.50 to 0.96) and diurnal (R2=0.96) variability (for the Mohali station) of observed CO 2 than the current-generation global models (CarboScope, CarbonTracker and ECMWF EGG4). The seasonal CO 2 concentration variability in Mohali, associated with crop residue burning, is largely underestimated by the models. WRF–STILT captures the seasonal biospheric variability over Nainital better than the global models but underestimates the strength of the CO 2 uptake by crops. The choice of emission inventory in the modelling framework alone leads to significant biases in simulations (5 to 10 ppm), endorsing the need for accounting for emission fluxes, especially for non-background sites. Our study highlights the possibility of using the CO 2 observations from these Indian stations for deducing carbon flux information at regional (Nainital) and suburban to urban (Mohali, Shadnagar and Nagpur) scales with the help of a high-resolution model. On accounting for observed variability in CO 2 , the global carbon data assimilation system can benefit from the measurements from the Indian subcontinent. [ABSTRACT FROM AUTHOR]

Global warming necessitates urgent action to reduce carbon dioxide (CO2) emissions and remove CO2 from the atmosphere. Biochar, a type of carbonized biomass which can be produced from crop residues (CRs), offers a promising solution for carbon dioxide removal (CDR) when it is used to sequester photosynthetically fixed carbon that would otherwise have been returned to atmospheric CO2 through respiration or combustion. However, high‐resolution spatially explicit maps of CR resources and their capacity for climate change mitigation through biochar production are currently lacking, with previous global studies relying on coarse (mostly country scale) aggregated statistics. By developing a comprehensive high spatial resolution global dataset of CR production, we show that, globally, CRs generate around 2.4 Pg C annually. If 100% of these residues were utilized, the maximum theoretical technical potential for biochar production from CRs amounts to 1.0 Pg C year−1 (3.7 Pg CO2e year−1). The permanence of biochar differs across regions, with the fraction of initial carbon that remains after 100 years ranging from 60% in warm climates to nearly 100% in cryosols. Assuming that biochar is sequestered in soils close to point of production, approximately 0.72 Pg C year−1 (2.6 Pg CO2e year−1) of the technical potential would remain sequestered after 100 years. However, when considering limitations on sustainable residue harvesting and competing livestock usage, the global biochar production potential decreases to 0.51 Pg C year−1 (1.9 Pg CO2e year−1), with 0.36 Pg C year−1 (1.3 Pg CO2e year−1) remaining sequestered after a century. Twelve countries have the technical potential to sequester over one fifth of their current emissions as biochar from CRs, with Bhutan (68%) and India (53%) having the largest ratios. The high‐resolution maps of CR production and biochar sequestration potential provided here will provide valuable insights and support decision‐making related to biochar production and investment in biochar production capacity. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO 2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO 2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (<15%) uncertainties. However, as the constellation of CO 2 -observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the relationship between financial instability and carbon dioxide (CO2) emissions in India from 1980 to 2020. The Autoregressive Distributed Lag (ARDL) model is used to measure long-run and short-run dynamics, followed by the Vector Error Correction Model (VECM) to determine the causal direction. As per the findings of the study, financial instability has an insignificant effect on CO2 emissions. However, economic development, energy use, and urbanization have a detrimental effect on environmental quality because it releases a significant amount of CO2 emissions into the environment. Our empirical findings confirmed the presence of an environmental Kuznets curve. The outcomes of the VECM show that the long-run causality can be noticed in CO2 emissions, financial instability, energy use, and urbanization. Furthermore, the validity and reliability of the results were verified by using a variety of diagnostic tests. This research presents novel results that add to the current literature and may be of particular importance to the country's policymakers regarding the financial system and its importance in environmental problems. [ABSTRACT FROM AUTHOR]

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[Display omitted] • Water-fluxed melting leads to the development of amphibole + biotite migmatite. • Muscovite dehydration melting leads to formation of sillimanite-bearing migmatite. • Peak P–T conditions of 770–790 °C, 9.3–10.5 kbar for the amphibole + biotite migmatite. • Necking, hook, and stretching inclusions developed during isothermal decompression. • Selective leakage of the H 2 O phase from the H 2 O-CO 2 inclusions. Migmatites exposed within the North Himalayan Domes result from the reworking and partial melting of different structural levels of the Indian continental crust during a major Himalayan tectonic event. Although their petrologic investigation is potentially a powerful method to unravel the anatectic and tectono-thermal processes related to the Himalayan orogeny, petrological studies of the migmatites from North Himalayan Domes are virtually lacking. This paper presents the results of a petrological and fluid inclusion study in order to understand the partial melting processes, the P–T conditions of migmatitization, and the fluid evolution of the migmatites from one of the North Himalayan Domes, the Leo Pargil Dome, exposed in central Himalaya. Phase equilibria calculated in the MnO–Na 2 O–CaO–K 2 O–FeO–MgO–Al 2 O 3 –SiO 2 –TiO 2 –H 2 O (MnNCKFMASTH) system suggest peak P–T conditions of 770–790 °C, 9.3–10.5 kbar for the amphibole + biotite migmatite and of 780–820 °C, 9.3–9.8 kbar for the sillimanite-bearing migmatite, followed by an early nearly isothermal decompression. The formation of these migmatites was related to water-fluxed melting and muscovite dehydration melting. At peak metamorphic conditions, aqueous-carbonic (H 2 O-CO 2) fluids were present in the system. Subsequently, the H 2 O phase was preferentially leached out from the biphase aqueous-carbonic inclusions to form primary CO 2 inclusions and directly went into the anatectic melt during migmatization. The exhumation of LPD followed an early nearly isothermal decompression path and a later isochoric cooling driven by the Kaurik-Chango normal fault. [ABSTRACT FROM AUTHOR]

Climate change has been a global challenge and BRICS countries are not excluded from these challenges which affect weather conditions and subsequently lead to disasters. Climate change is regarded as a change in climate patterns that are caused by the increase in the levels of atmospheric carbon dioxide produced by the use of fossil fuels. Because of the awareness of this challenge, the purpose of the study was to look at possible ways to reduce pressure on the climate, particularly in BRICS countries. The objective of this study was to convince BRICS countries to use trade agreements to look at business models that would not put much pressure on the climate. Secondly, to ensure that companies do not produce carbon dioxide that is toxic to the climate. This study aimed to find ways to protect BRICS countries from various disasters that are caused by climate change. Business agreements between BRICS countries should, therefore, have terms and conditions that seek to protect the climate and natural resources. Because of the availability of data concerning the causes of climate change, this study applied a secondary research design. Reports, findings of the previous study, and conference findings data assisted in reaching the findings of the study. In conclusion, BRICS countries have to quickly do something about climate change. The floods that South Africa and India have experienced in 2022 should be the main reason why BRICS countries must prioritize the agreement. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate opportunities to mitigate CO 2 emission from the power and industry sectors of India by carbon capture and storage. Results show that the total CO 2 emission from 630 power and industrial plants is 1.7 Gtpa. Of this, 0.9 Gtpa comes from power plants and 0.8 Gtpa from industry plants. There is 416.2 Gt of CO 2 storage capacity (mid case scenario) in India, enough to store 237 years of emission. Of this, 412.7 Gt (99%) comes from saline aquifers in 22 sedimentary basins, 1.9 Gt (0.44%) from six major gas fields, and 1.7 Gt (0.41%) from 37 major oil fields. The total mid CO 2 -enhanced oil recovery potential in India is 500 × 106 m3 with the biggest potential found in the following oil fields: Mumbai High (231 × 106 m3), Gandhar (13 × 106 m3), Mangala (17 × 106 m3) and Nahorkatiya (24 × 106 m3) in the states of Gujarat, Maharashtra, Rajasthan and Assam, respectively. Results of a CO 2 source-sink mapping exercise show that in most cases, CO 2 source-sink distance is less than 500 km, and many cases less than 100 km. • India's CO 2 emission is 1.7 Gtpa from the power and industry sectors. • There is 416.2 Gt of subsurface CO 2 storage capacity in India. • There is a total of CO 2 -enhanced oil recovery potential of 5.01 × 108 m3. • A CO 2 -EOR pilot is recommended for the offshore Mumbai High oil field. • Most CO 2 sources can be stored in sinks within a 500 km distance. [ABSTRACT FROM AUTHOR]

India has the largest dairy industry in the world and accounts for a significant share of the global emission of livestock methane ( CH 4 ), a potent greenhouse gas (GHG). While previous works have examined the large-scale livestock CH 4 emissions in India, bottom-up studies are essential to account for the diverse farm conditions and practices across the subcontinent. We developed a Methane Calculator for Indian livestock sector using the Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology for estimating methane emissions from enteric fermentation and manure management. Using this calculator, we undertook a study of emissions from four dairy farms in the tropical coastal district of Thiruvananthapuram, Kerala, in June 2019. Livestock population and milk production data were collected from the four farms, to compute a mean CH 4 emission of 0.7183 kg CO 2 equivalents/kg of fat and protein corrected milk (kg CO 2 e/kg FPCM), with a notable farm-to-farm variability (63.3%). Having implemented the latest available guidelines outlined by the IPCC, our results are a valuable new addition to the existing body of knowledge in the measurement of dairy farm GHG emissions. We present this as a pilot study, demonstrating a simple method to perform bottom-up investigations of dairy GHG emissions and further formulate policy interventions and mitigation strategies at the farm level. [ABSTRACT FROM AUTHOR]

Carbon capture and storage is a necessary action for the reduction of CO2 emissions, and thereby mitigation of climate change and its impacts. Especially, in India, with its growing fuel needs and very little attention paid towards carbon capture and storage, mineral carbonation technology is a suitable option as it is cost-effective and could be retrofitted to existing plants that emit CO2. Given the development of carbon capture and storage technology, this study attempts direct mineral carbonation of steelmaking slag with flue gas. Response surface methodology was employed to design gas-solid and slurry phase aqueous carbonation experiments. A maximum reduction of about 36.1% was achieved through aqueous carbonation at 61.1 °C, 46.24 bar, and a liquid-to-solid ratio of 14.5, corresponding to a sequestration capacity of 127.4 g of CO2/kg of slag. The temperature was found to be the most vital parameter in both the aqueous and gas-solid carbonation processes. Regression models used to study the carbonation process were found to be statistically significant. The carbonated slag consisted of mineral phases, namely, calcite and dolomite. The results demonstrated the sequestration potential of Indian steelmaking slag with flue gas. Carbonation of steelmaking slag with flue gas poses to be a promising option for the development of carbon capture and storage technology in the country. [ABSTRACT FROM AUTHOR]

India's CO 2 emissions have risen at a compounded annual growth rate of 3.1% over the last three decades, primarily from an increase in consumption of fossil fuels. Carbon capture, utilization, and storage (CCUS) is considered one of the most effective strategies to counter these trends by reducing the carbon footprint of existing and upcoming infrastructure. Utilization of captured CO 2 (CCU) to produce valuable green chemicals is an economically viable proposition. On the other hand, storage of CO 2 (CCS) reduces the carbon footprint by sequestering the captured CO 2 in geological formations, which in some cases, facilitates hydrocarbon recovery. This paper showcases how a multifaceted approach of combining CCU and CCS in an economically viable manner is a key factor in the maintaining of sustainable development. We discuss at a systems level, the benefits of the implementation of CCUS for India's energy security, positive path dependency, and resiliency. This is followed by a bottom-up review of the symbiotic relationship between the capture and utilization/storage. We provide an assessment of sustainable CCUS implementation by pairing state-of-the-art technologies in the field of carbon storage/utilization with possible future directions in India. We also suggest pathways for the potential and the impact of India's carbon-intensive sources in different CCUS chains such as markets for large-scale utilization of CO 2 in emerging methanol economy. Finally, we provide research and policy recommendations that would facilitate a sustainable collaborative effort across sectors in mitigating the increasing carbon dioxide in the atmosphere. [ABSTRACT FROM AUTHOR]

The reported incidence of shoulder tip pain after laparoscopic cholecystectomy was 30%–50%. The aim of the present randomized controlled study was to compare the effects of low-pressure (08–10 mm Hg) vs. standard-pressure (13–15 mm Hg) pneumoperitoneum in patients undergoing laparoscopic cholecystectomy. One hundred patients between 18 and 70 years undergoing laparoscopic cholecystectomy were included. Group A and group B patients underwent low-pressure and standard-pressure pneumoperitoneum laparoscopic cholecystectomy respectively. Post-operative shoulder tip pain and post-operative abdominal pain were measured using visual analogue scale score at 2 h, 8 h, 24 h and 48 h after surgery. The primary outcome measures were the incidence and severity of post-operative shoulder tip pain, whereas secondary outcome measures were the incidence and severity of abdominal pain. Intergroup comparison of categorical and continuous variables was done using the chi-square test/Fisher's exact test and unpaired 't' test respectively. The incidence and severity of post-operative shoulder tip pain at 2 h, 8 h, 24 h and 48 h was significantly higher in group B as compared to group A. The incidence of post-operative abdominal pain at 48 h was significantly higher in group B as compared to group A. The severity of post-operative abdominal pain at 24 h and 48 h was significantly higher in group B as compared to group A. Low-pressure laparoscopic cholecystectomy significantly decreases the incidence and severity of post-operative shoulder tip and abdominal pain. Routine use of low-pressure pneumoperitoneum for the alleviation of post-operative pain following laparoscopic cholecystectomy is recommended. [ABSTRACT FROM AUTHOR]