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The danger of climate change has over the years become a reality in the public domain. While efforts to mitigate climate change involve energy mix, energy efficiency and cleaner technology, financial development has also been considered as an important factor. Indicator of financial development may draw FDI and advanced degree of research and development which can accelerate economic growth and hence affect dynamism of environmental performance. This study examines the impacts of energy use and financial development indicators by source in the environment-growth-energy model for 90 countries categorized on the basis of income possession over the period 1980–2014. The study applies the panel analysis that accounts for cross-sectional dependence and heterogeneity of series used in the estimation. Results from panel Dynamic Ordinary Least Squares (DOLS) show that in all the categories of countries, fossil fuel energy use and GDP per capita are found to be the major drivers of CO 2 emissions though fossil fuel energy use possesses the bigger elasticities. Population however, displays a sign contrary to expectation regarding economic theory in high income countries. Renewable energy and financial development on the other hand are capable of reducing CO 2 emissions. However, the magnitude of the long-run elasticity of CO 2 emissions with respect to renewable energy use and financial development are much greater in the models with M 2 /GDP than the model with M 2 /Reserve especially in the high income countries. Policies should be geared towards stimulating investments in renewable energy technology. There is need to develop robust financial systems to lend financial credence to research institutes to work towards producing energy that have less carbon or are carbon-free. [ABSTRACT FROM AUTHOR]

Mitigating climate change is driving the need to decarbonize the electricity sector, for which various possible technological options exist, alongside uncertainty over which options are preferable in terms of cost, emissions reductions, and energy security. To reduce this uncertainty, we here quantify two questions for the power system of Great Britain (England, Wales and Scotland): First, when compared within the same high-resolution modeling framework, how much do different combinations of technologies differ in these three respects? Second, how strongly does the cost and availability of grid-scale storage affect overall system cost, and would it favor some technology combinations above others? We compare three main possible generation technologies: (1) renewables, (2) nuclear, and (3) fossil fuels (with/without carbon capture and storage). Our results show that across a wide range of these combinations, the overall costs remain similar, implying that different configurations are equally feasible both technically and economically. However, the most economically favorable scenarios are not necessarily favorable in terms of emissions or energy security. The availability of grid-scale storage in scenarios with little dispatchable generation can reduce overall levelized electricity cost by up to 50%, depending on storage capacity costs. The UK can rely on its domestic wind and solar PV generation at lower renewable shares, with levelized costs only rising more than 10% above the mean of 0.084 GBP/kWh for shares of 50% and below at a 70% share, which is 35% higher. However, for more than an 80% renewable generation share to be economically feasible, large-scale storage, significantly more power imports, or domestic dispatchable renewables like tidal range must be available. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an assessment of global economic energy potentials for all major natural energy resources. This work is based on both an extensive literature review and calculations using natural resource assessment data. Economic potentials are presented in the form of cost-supply curves, in terms of energy flows for renewable energy sources, or fixed amounts for fossil and nuclear resources, with strong emphasis on uncertainty, using a consistent methodology that allow direct comparisons to be made. In order to interpolate through available resource assessment data and associated uncertainty, a theoretical framework and a computational methodology are given based on statistical properties of different types of resources, justified empirically by the data, and used throughout. This work aims to provide a global database for natural energy resources ready to integrate into models of energy systems, enabling to introduce at the same time uncertainty over natural resource assessments. The supplementary material provides theoretical details and tables of data and parameters that enable this extensive database to be adapted to a variety of energy systems modelling frameworks. [Copyright &y& Elsevier]