• Energy Research

The adoption of Sustainable Development Goals (SDG) in 2015 shifted the attention towards sustainability-related concerns in both developing and developed counties. The aim of this paper is to examine how agricultural productivity – a key driver in achieving many of these SDGs – is affected by carbon emissions, deforestation, renewable energy consumption, natural resources, and regional integration for the ten Association of Southeast Asian Nations (ASEAN) countries. Using the Mean Group (MG) class estimators, able to tackle the cross-sectional dependence in the data, empirical findings reveal that environmental degradation (in the form of CO2 emissions) reduces agricultural productivity in the region. Both the forest area and natural resource variables negatively affect the productivity of the agricultural sector, while the use of renewable energy sources positively contributes to the agricultural sector. However, despite being one of the highest integrated regions in the world, regional integration among the ASEAN members does not boost their agricultural productivity. The causality tests confirm the existence of bidirectional causality between agricultural productivity and renewable energy consumption, and unidirectional causality across a few other variables. Accordingly, the study provides policy recommendations for the governments of ASEAN economies on improving the environmental performance of agriculture and achieving the SDGs by 2030.

China is one of the largest emitters of carbon dioxide (CO2) emissions in the world. Therefore, it is essential to explore the determinants of CO2 emissions in China. But previous studies so far have not examined how the political risk of this country can affect its CO2 emissions due to the lack of a long-term dataset. Hence, this study aims to capture the effect of political risk on China's CO2 emissions while controlling renewable energy consumption, technological innovation, and the economy's economic growth. We employ Bayer and Hanck cointegration, FMOLS, DOLS, CCR, and frequency domain causality tests to establish the relationship among the variables mentioned above. The outcome of the study reveals that political stability is an important predictor of environmental degradation in China. Moreover, political stability is helpful to lower CO2 emissions, while technological innovation and renewable energy consumption can reduce CO2 emissions, economic growth further deteriorates environmental quality by increasing its carbon emissions. Therefore, the present study recommends that policymakers in China should control political tension in the country to control CO2 emissions and, at the same time, promote technological innovation and renewable energy consumption.

Foreign direct investment (FDI) and the consumption of non-renewable energy have been on the increase in the coastal Mediterranean countries (CMCs) over the last few decades. Both trigger growth, but the environmental impact could be far-reaching as environmental distortions are mainly human-induced. This study examines the environmental issues facing CMCs. Specifically, we investigate whether the pollution haven hypothesis holds for CMCs. We employ a quantile panel data analysis for CMCs to account for heterogeneity and distributional effects of socioeconomic factors. The result reveals that the influence of FDI on environmental degradation is a function of the indicators utilized and also depends on the initial levels of environmental degradation. The results suggest that the pollution haven hypothesis does not hold for CMCs. However, we also find that energy consumption significantly increases environmental degradation for all indicators and across the observed quantiles. The effects of economic growth and urbanization on the environment were mixed for the different indicators and across quantiles. We recommend that it is pertinent for CMCs to limit their "dirty" energy sources and substitute them with renewables to promote environmental sustainability.

The loss of biodiversity has profound implications for nature's contributions to people and their health. This study intends to examine the factors responsible for biodiversity loss as well as the coping mechanisms to address this crisis in the context of 35 European economies covering the 2009-2018 period. The study utilises both the static and dynamic panel estimation techniques to examine the above issue. Specifically, the study applied Driscoll and Kraay (1998a), Driscoll and Kraay (Rev Econ Stat 80:549-560, 1998b) and Panel Corrected Standard Approach (PCSE) for the static panel models. As for dynamic panel models, the study employs linear dynamic panel model by Arrelano and Bond (Rev Econ Stud 58:277-297, 1991) and Arrelano and Bover (J Econom 68:29-51, 1995)/Blundell and Bond (J Econom 87:115-143, 1998) system generalised methods of moments (GMM). Morandeover for robustness purposes, fixed and random effect models are also applied. The findings indicate that renewable energy use increases biodiversity crisis whereas organic farming is beneficial for biodiversity preservation in Europe. Corruption and gender gap were found to increase the biodiversity crisis. The evidence also suggests a positive and significant effect of forest area, e-governance and social progress on biodiversity. Finally, the study provides insightful implications for stakeholders and practitioners associated with energy and biodiversity conservation in Europe.

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.

The countries in the Middle East and North Africa (MENA) region have the greatest potential for renewable energy consumption in the world and is likely to be the most vulnerable to the horrendous effects of climate change. Unfortunately, only a few of the countries have tapped into this potential, as non-renewable energy still dominates the total energy mix of these countries. This study explores the effect of renewable and non-renewable energy consumption on the environment in MENA countries from 1990 to 2016 by applying the Augmented Mean Group algorithm while accounting for urbanization, financial development, and economic growth. The panel result suggests that financial development, economic growth, and urbanization add to environmental degradation. Also, findings reveal that renewable energy does not contribute meaningfully to environmental quality, while non-renewable energy consumption significantly adds to environmental degradation. A uni-directional causality flows from urbanization, economic growth, and energy use to environmental degradation. One way to abate this damage is for countries in this region to embrace and promote the consumption of clean energy sources.

Abstract In the past decade, researchers have shifted their interests to explore different ways to mitigate environmental degradation. In that context, the present study explores the role of solar energy and eco-innovation in reducing environmental degradation in China. The study utilized data for the period 1990–2018 and applied the latest available econometric technique, a quantile autoregressive distributed lag model, to determine the impacts of solar energy and eco-innovation on improving China's environmental quality. According to the empirical results, in the long term, solar energy is negatively and significantly associated with CO2 emissions at higher quantiles. Eco-innovation has proven to be the most important channel to mitigate CO2 emissions in China. Eco-innovation is exerting a negative and significant influence on CO2 emissions at all quantiles in the long term. In addition, the population size is causing CO2 emissions to surge significantly at lower quantiles. The empirical analysis reveals that per capita income (PI) is positively associated with CO2 emissions at all quantiles, but it is significant only at higher quantiles in China. We found evidence of unidirectional causality for eco-innovation to CO2 emissions and solar energy to CO2 emissions. However, for population and CO2 emissions, per capita income, and CO2 emissions, we found bidirectional causality. As indicated by our empirical results, solar energy and eco-innovation are the two most effective channels to control CO2 emissions in China. Therefore, policies based on the promotion of eco-innovation and the initiation of new solar energy projects can control emissions and improve environmental quality in China. Integr Environ Assess Manag 2022;18:555–571. © 2021 SETAC KEY POINTS The present study explores the role of solar energy and eco-innovation in reducing environmental degradation in China. In the long term, solar energy is negatively and significantly associated with CO2 emissions at higher quantiles. Eco-innovation has proven to be the most important channel to mitigate CO2 emissions in China.

Agriculture and the food system emit a considerable amount of Greenhouse Gas (GHG) emissions in the atmosphere. Hence, current researchers, policymakers, and other stakeholders are calling for improving the environmental performance of agriculture. This study utilizes the countries of The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) to investigate the effect of agriculture value-added, pesticide use, renewable energy adoption, human capital, and economic growth on greenhouse gas emissions. The moderation effect of renewable energy use and human capital is also introduced to see whether they can offset agriculture's emissions in these BIMSTEC economies. Having reported a state-of-the-art literature review, the econometric procedure applies the second-generation unit root tests, panel cointegration and panel quantile regression for three preferred model specifications. The result from the Panel quantile regression method reveals a U-shaped relationship between agriculture value-added and greenhouse gas emissions, suggesting the significance of a small farming system. Human capital has a negative effect, whereas pesticide use has a positive effect on greenhouse gas emissions. Furthermore, the moderation effect of human capital and pesticide use suggests that human capital is not significant enough to offset the effect of pesticide use on the greenhouse gas emissions, whereas the interaction of renewable and pesticide use suggests that renewable energy adoption in the agriculture sector can mitigate the effect of pesticide use on GHG emissions. Finally, the conclusions of the study support the achievement of few sustainable development goals.