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For India, achieving environmental sustainability in the midst of faster growth remains a challenging objective. Therefore, we are revisiting the nature of the Environmental Kuznets Curve (EKC) at different stages of economic growth through both necessary and sufficient conditions under the cubic model specifications in India. Further, we extend the EKC framework by incorporating energy consumption, agricultural value added, trade, the world uncertainty index, and geopolitical risk as additional variables into the three preferred disaggregated greenhouse gas emission (GHG) models. This study employs an auto-regressive distributed lag model (ARDL). The empirical findings show evidence of the valid N-shaped EKC through both necessary and sufficient conditions for carbon dioxide (CO 2) and nitrous oxide (N 2 O) and exhibit the presence of two real and distinct income turning points for both valid EKCs. In contrast, only the necessary condition supports the N-shaped EKC for methane (CH 4) emissions in India. Further, the results highlight that trade has a positive impact, whereas the world uncertainty index has a negative impact on disaggregated GHGs. Similarly, geopolitical risk has a negative effect on CH 4 and N 2 O, whereas energy consumption has a positive impact on CO 2 emissions. Moreover, agricultural value added has a negative effect on CH 4 and a positive effect on N 2 O emissions. Our empirical findings suggest policy recommendations that can collectively work as a roadmap for India to become emission-neutral by 2070. [ABSTRACT FROM AUTHOR]

The modern economic growth paradigm significantly relies on natural endowments. Solar energy as a perpetual source has the potential in reducing the ecological footprint, which has been overlooked in the empirical literature. We assess the dynamic impact of solar energy consumption on ecological footprints by applying quantile on quantile (QQ) regression in the context of the top ten solar energy-consuming countries. Our empirical analysis demonstrates that solar energy use mitigates ecological footprints at various quantiles for all sample countries except India and the United Kingdom. Overall relation is more profound at higher quantiles of solar energy and lower quantiles of ecological footprint. The bidirectional quantile Granger-causality analysis confirms a somewhat feedback effect of the ecological footprint on solar energy. Our empirical evidence emphasizes that solar energy should be integrated into the sustainable growth agenda. Image 1 • This study investigates the dynamic impact of solar energy on ecological footprints. • This study considers the top ten solar energy-consuming countries. • Quantile-on-Quantile (QQ) regression is applied in the presence of the extreme observations. • Solar energy is found to be an effective mitigation measure in reducing ecological footprints. [ABSTRACT FROM AUTHOR]

Several economists assume natural resources as crucial and essential for economic growth. However, the other group of researchers questions the role and states that richness of natural resources does not guarantee economic growth. Therefore, the aim of this study is to examine the effect of natural resources on economic growth using time series data from 1970 to 2018. The current study has applied a novel methodology of quantile-on-quantile regression in top five selected Asian economies which have the most natural resources in the region. The findings confirm that natural resources have a positive and significant impact on economic growth in all countries, except India. The findings confirm that the effect of natural resources on economic growth is negative and significant in the Indian economy. The findings affirm that in most of the countries, the results are significant and positive on the high quantiles of natural resources and economic growth, suggesting that the higher the rent of natural resources leads to the higher the economic performance of five selected Asian economies. Based on the findings, government and policymakers are recommended to formulate the policy that provides a platform to use the NR in a better and efficient manner, which can help the country to boost the economic performance. Image 1 • Natural resources are crucial and essential for economic growth. • The study examines the effect of natural resources on economic growth using time series data from 1970 to 2018. • A novel methodology of quantile-on-quantile regression is applied. • Top five selected Asian economies which have the most natural resources in the region were selected. • The findings confirm that natural resources have a positive and significant impact on economic growth, except India. [ABSTRACT FROM AUTHOR]

Circular economy (CE) focuses on a circular approach to energy and material resources, which provides economic, environmental and social benefits for manufacturing organisations. CE adoption in emerging economies facilitates in substantial economic growth through appropriate utilisation of energy and material resources across manufacturing industries. This study identifies CE indicators in the context of an emerging economy. The study further develops a framework for the adoption of CE and tests it through a hybrid Best Worst Method and Decision-Making Trial and Evaluation Laboratory approach. The framework is validated through an Indian manufacturing case organisation. While Best Worst Method computes the CE related indicator weights, Decision-Making Trial and Evaluation Laboratory analyses the inter-relationship among indicators. Disparate CE related indicators, e.g. strategic, managerial, informational and technological, supply chain and organisational, influence the CE adoption in an emerging economy context. The findings reveal that the strategic and managerial indicators have the strongest influence on developing other indicators. The causal digraph and relationship diagram assist the practitioners in predicting the inter-relationship of indicators in CE adoption. The study outcomes will help the practitioners, policymakers and researchers to draw a framework for adoption of circular and green practices and usage of resources sustainably. Image 1 • Provide 31 circular economy (CE) indicators. • Propose a framework to improve CE adoption process. • Explores a case analysis of an Indian manufacturing industry. • Analyse the proposed framework through hybrid BWM-DEMATEL approach. • Demonstrate intensity and inter-relationships among the CE indicators. [ABSTRACT FROM AUTHOR]

Added global carbon emissions have mainly come from China and India since 2012, which indicates importance of two countries in curbing global CO 2 emissions. Thus, their respective mitigation lessons have more realistic significance in developing more effective mitigation strategy. This study compared the dynamic evolution of their CO 2 emissions and driving factors behind changes, in order to find similarities and differences of two countries, and provide available policy implications to further reduce carbon emissions. Firstly, both China's and India's carbon emissions have been increasing during 2000-14: 3.4–9.9 Gt and 0.9–2.0 Gt, respectively. However, tendency of two countries varied differently: growth of China 's CO 2 have slowed down after the 2008 financial crisis, while India 's emissions were still accelerating at a high level on account of growing share of carbon-intensive energy in the whole energy structure. From the national and sectoral perspectives, both trends of carbon emissions from two countries have been analyzed. According to structural decomposition analysis, efficiency gains and slowdown of economic growth in China contributed to most decline of CO 2 but both production and consumption structures urged emissions up, while structure effects in India slightly reduced its CO 2 but low emission efficiency and expansion of trade scales caused growth of emissions. On this basis, firstly, China should optimize production structures by upgrading industries, while India should promote energy transformation and improve energy efficiencies. Secondly, strengthening cooperation and communications with developed countries with advanced technology and experience may make more progress in climate change for two countries. Experience and lessons of emission reduction deriving from the two would also provide references for other regions. Image 1 • Investigating CO 2 emissions of China and India for 2000–2014. • Explore main sources and sectors that dominated CO 2 emissions. • Improving efficiency and optimizing energy structure offset China's emission growth. • Optimizing its consumption structure offset India's emission growth. • Optimizing their consumption structure should be considered in China and India. [ABSTRACT FROM AUTHOR]

A boom in renewable energy consumption as a percentage of final energy consumption (REC) has a significant impact on cleaner production and environmental sustainability. However, studies on REC as for an individual country-case and panel case approach for top emitters are rare. Against this backdrop, this study investigates the long-run drivers of REC by using a time series data from 1990 to 2015. The FMOLS-grouped results indicate that economic growth and trade openness increase REC whereas population growth has a negative but significant impact on REC. To check for causal links, the innovating accounting approach using variance decomposition analysis is applied. The results show that there is a unidirectional causality running from economic growth, trade openness, and population growth to REC. Further, the predictive accuracy of the FMOLS based econometric output and the bi-directional long short-term memory (Bi-LSTM) is analyzed. The Bi-LSTM formulated algorithm outperformed the econometric output. The Bi-LSTM is utilized to forecast REC to the year 2030. The output from the Bi-LSTM shows that China, the US, India, the Russian Federation's, and Japan's REC will hit ∼11.3395, ∼11.1245, ∼34.6969, ∼2.9097, and ∼7.4859, respectively. The US and Japan's REC levels will increase while that of China, India, and Russia Federation will decrease. As a policy implication, new policy directives for China, India, and the Russian Federation are required to boost REC levels. [ABSTRACT FROM AUTHOR]

This study evaluates the potential impact of promoting non-fossil fuel energy on India's economic growth in a regime based non-linear asymmetric framework. The empirical outcomes affirm regime-shift and asymmetric cointegrating links of the non-fossil fuel energy usage represented by combustible renewables & waste (CREW) and alternative & nuclear energy (ANEN) with the gross domestic product (GDP). The study establishes the existence of threshold cointegration between CREW and GDP. The causal links between CREW and GDP are regime variant and asymmetric, whereas the dynamics between ANEN and GDP are proven to be asymmetric and regime invariant. CREW and GDP supports a feedback hypothesis in a normal regime and a conservation hypothesis in a rare regime. The asymmetric causality between CREW and GDP validates an inverse feedback hypothesis and a negative growth hypothesis. A negative growth hypothesis is also ascertained between ANEN and GDP. The empirical findings convey meaningful insights for government and policymakers. • Examines the link between non-fossil fuel energy and economic activity in India. • Regime shifts, threshold and asymmetric cointegration found. • Feedback hypothesis in a normal regime is demonstrated in long run. • Positive change in combustible renewables & waste causes economic growth adversely. • Negative changes in alternative & nuclear energy drives positive economic growth. [ABSTRACT FROM AUTHOR]