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Transitions to renewable energy sources have begun in several countries in an effort to decrease the impact of solid fossil waste. The paper examines the connection between renewable energy consumption, FDI, and CO2 emissions using econometric analysis of data from France, Germany, and Italy. The purpose of this research is to examine the correlation between the use of renewable energy sources, FDI, CO2 emissions from energy sources, and GDP growth in France, Germany, and Italy from 1971 to 2021. The data is analysed using many different tests, including those for stationarity, Granger causality, and the Toda-Yamamoto method. According to the findings, the utilisation of renewable energy sources is a driving factor in cutting CO2 emissions in France, whereas in Italy, emissions are the result of foreign direct investment. In Germany and Italy, the lack of a correlation between consumption of renewable energy, FDI, and CO2 emissions over the long term suggests that renewable energy does not play a significant role in driving economic development in those countries. Our results add to the existing body of knowledge and imply that investments in renewable energy are crucial to achieving sustainable development. Governments should take action to mitigate the negative effects of FDI on the environment and promote investments in renewable energy.

Energy is among the key drivers of economic growth. As the attainment of sustainable development becomes the major goal of modern economies, energy resources must, however, be appraised not only based on their capacity to fuel growth but also on their ability to sustain the same. This paper adds to the growing research on the growth-energy nexus by incorporating the dynamics of sustainability alongside the traditional growth factors of capital and labor using France’s yearly series from 1980 to 2019. The newly developed dynamic autoregressive distributed lag (ARDL) simulation was adopted to explore the nature of the long-run dynamics among the variables. The empirical findings support the notion that energy consumption significantly impacts gross domestic product (GDP) positively whereas, in the case of the adjusted net savings (ANS) which is an index of sustainable development, its long-run impact is positive but insignificant. The results also show that the counterfactual effects of shocks to energy usage are smaller on economic growth than sustainable development. France is recommended to promote green growth by boosting the contribution of renewables in the energy mix to fully optimize and sustain growth from energy resources.

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc.

The paper is concerned with predicting energy consumption in the production and product usage stages and searching for possible changes in product design to reduce energy consumption. The prediction of energy consumption uses parametric models based on regression analysis and artificial neural networks. In turn, simulations related to the identification of improvement opportunities for reducing energy consumption are performed using a constraint programming technique. The results indicate that the use of artificial neural networks improves the quality of an estimation model. Moreover, constraint programming enables the identification of all possible solutions to a constraint satisfaction problem, if there are any. These solutions support R&D specialists in identifying possibilities for reducing energy consumption through changes in product specifications. The proposed approach is dedicated to products related to high-cost energy use, which can be manufactured, for example, by companies belonging to the household appliance industry.

Russia's competitiveness and productivity encounter the intense environmental challenges due to the reckless fossil fuel consumption, putting this country's long-run sustainability at risk. Despite this, this country intends to achieve the sustainable development goal by cutting greenhouse gas (GHG) emissions to 70% of its 1990 level as pledged in the Paris Agreement in 2016. This research assesses the relationship between disaggregate (renewable and non-renewable) energy consumption and sustainable development within the purview of financial, demographic and country risk indicators using annual time-series data from 1990 to 2020. This paper utilizes an augmented ARDL approach to co-integration and a dynamic ARDL simulation model to detect counterfactual forecasting shocks to the predictor variables and their effects on the predicted indicator. The study's findings divulge that renewable energy consumption escalates the sustainable development in the long run, whereas non-renewable energy consumption declines. Then again, urbanization and political terror scale (PTS) have a long-term adverse effect on sustainable development. On the other hand, financial openness substantially exerts a favorable long-term influence on sustainable development. Therefore, this study suggests shifting to generous renewable energy usage to ease the adverse effect of non-renewable energy consumption on the sustainable development in Russia.

In recent years, there has been an upsurge of studies on sustainable development. The majority of research focuses on developed countries and issues that are incompatible with developing nations. This study addresses a gap in the literature by reviewing the research on developed and developing economies, as well as their social and environmental boundaries, under the renewable energy and sustainable development (RESD) nexus. It also explores how RESD may be applied in extreme situations such as population increase, energy supply disruptions, and transportation shortfalls. The fundamental contribution of this paper is to provide detailed debate from the perspective of economic growth hypotheses and their relationship with energy usage and renewable energy solutions for sustainable growth and development.