Sustainable development and reducing environmental pressure are major issues that concern developed as well as developing countries. Although researchers widely use carbon dioxide emissions and ecological footprint within the scope of environmental degradation, a more comprehensive ecological indicator is needed to assess environmental sustainability. In this context, the load capacity factor enables a comprehensive environmental sustainability assessment through the simultaneous analysis of biocapacity and ecological footprint. However, there are few studies analyzing the determinants of load capacity factor and this study aims to fill this gap for Indonesia. Using the recently developed Fourier quantile causality test, this study investigates the impact of income, export diversification, non-renewable and renewable energy consumption on the load capacity factor for Indonesia during 1965Q1–2014Q4. The results show unidirectional causality from non-renewable energy consumption to the load capacity factor at all quantiles, while income, export diversification, and renewable energy are the causes of environmental quality at middle and higher quantiles (within 0.5, 0.7, and 0.9). Most importantly, renewable energy and export diversification increase the load capacity factor and thus support environmental quality. In contrast, an increase in income and consumption of non-renewable energy reduces the load capacity factor. These results highlight the importance of renewable energy and export diversification for the sustainable development of Indonesia.

An increase in energy consumption indicates increased economic activity; whether it leads to prosperity depends on the sustainability and stability of the energy source. This study has selected the top ten highly carbon emitting countries to assess renewable energy consumption dynamics for 1991 to 2018. The development of renewable energy ventures is not an overnight transformation. Further, it also entails an infrastructure development gestation which may increase CO₂ emissions for the short term. To assess this non-linear pattern with CO₂ and its heterogeneities, renewable energy consumption and its three types (Wind, Solar and Hydropower) are used. The empirical results estimated with a pooled mean group (PMG) method indicate that renewable energy consumption and hydropower follows inverted U-shaped behavior, with wind and solar energy consumption behavior also U-shaped. Forest area and patents are responsible for carbon remissions, while economic growth is responsible for increasing carbon emissions in sampled countries.

Anthropogenic activities are responsible for greenhouse gas emissions, causing extreme events like soil erosion, droughts, floods, forest fires and tornadoes. Fossil fuel consumption produces CO₂, and trapping heat is the major reason for a rapid increase in global temperature, and electricity generation is responsible for 25% of greenhouse gas emissions. Fossil fuel consumption, CO₂ emissions and their adverse impact have become the focus of efforts to mitigate climate change vulnerability. This study explores empirical determinants of vulnerability to climate change such as ecosystem, food, health and infrastructure. The sustainable use of energy is necessary for development, and a source of response to climate change. The present study focuses on renewable energy consumption to determine climate vulnerability in G7 countries between 1995 and 2019. The panel ARDL approach showed that the renewable to non-renewable energy mix showed a quadratic effect on vulnerability, whereby a minimum threshold of renewable energy is required to witness a reduction in food, health and infrastructure vulnerability. Other results indicate that trade openness and development expenditures reduce health vulnerability. Development expenditures also decrease ecosystem vulnerability, while trade openness increases it. However, both of these variables increase infrastructure vulnerability. Avoiding severe food and water crises requires investment to tackle climate change, conserve energy and water resources, reform global trade and food markets, and adapting and adopting climate-resilient responses to change.

The COVID-19 pandemic has a long-lasting influence on global economies. Households are expected to consume more electricity for their usual routine activities due to mandatory stay-at-home restrictions, resulting in greater energy utilization. The proposed study seeks to investigate the most relevant energy consumption factors amid the COVID-19 pandemic. The study employs a structural equation modeling approach to evaluate the responses from 511 Pakistani residents. Empirical results report a positive and significant association among perceived behavioral control (PBC), perceived environmental concern (PEC), perceived monitory benefits (PMB), and intention to save energy (ISE). Positive anticipated emotions (PAE) is found to be a significant predictor of ISE and energy-saving behavior (ESB). As a step further, we extend the analysis to find the moderating effect of perceived COVID-19 disruptiveness (PCD) between the relationship of ISE and ESB. Results reveal that PCD positively moderates this relationship. Based on research findings, policy implications and future research directions are provided for practitioners, researchers, and academicians to fulfill the country’s energy needs on its way to a future of sustainable development.

Sustainable development remains unattainable unless we move to reduce the negative impact of economic factors on environmental quality. It is noteworthy to provide new evidence on whether and how the empirical association between export diversification, agricultural value-addition, renewable energy, and regulatory quality with greenhouse gas (GHG) emissions evolved in Asian countries from 1996 to 2014. The study examines the relationships between these variables using current panel data techniques. The econometric procedure includes second-generation cointegration and unit root tests together with a novel Method of Movements Quantile Regression (MMQR). This approach offers an asymmetric relationship between the variables and is very robust to outliers compared to traditional quantile regression. The empirical outcomes show that export diversification, renewable energy, and regulatory quality are significantly and negatively associated with GHG emissions. In contrast, agricultural value-added in Asia has become a source of increased GHG emissions. Our findings are also robust with alternate specifications, including fully modified, dynamic and fixed effect regressions. This study will help policymakers for diversifying their export portfolio while ensuring a sustainable environment in Asia.