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This paper studies the development of renewable energy (RE) in the U.S. by examining the capacity to generate electricity from renewable sources. RE capacity exhibits a U-shaped relationship with per capita income, similar to other metrics for environmental quality (EQ). To explain this phenomenon, I consider several of the environmental Kuznets curve theories that describe the relationship between income and environmental quality (Y-EQ), including evolving property rights, increased demand for improved EQ, and changing economic composition. The results fail to provide support for the Y-EQ theories. I further consider the alternative hypothesis that increases in unemployment lead to increases in relative RE capacity, suggesting that promoting RE projects as a potential job creator is one of the main drivers of RE projects. The results imply that lagged unemployment is a significant predictor of relative RE capacity, particularly for states with a large manufacturing share of GDP. [ABSTRACT FROM AUTHOR]

In Europe, ethanol is blended with gasoline fuel in 5 or 10% volume (E5 or E10). In USA the blend is 15% in volume (E15) and there are also pumps that provide E85. In Brazil, the conventional gasoline is E27 and there are pumps that offer E100, due to the growing market of flex fuel vehicles. Bioethanol production is usually by means of biological conversion of several biomass feedstocks (first generation sugar cane in Brazil, corn in the USA, sugar beet in Europe, or second-generation bagasse of sugarcane or lignocellulosic materials from crop wastes). The environmental sustainability of the bioethanol is usually measured by the global warming potential metric (GWP in CO2eq), 100 years time horizon. Reviewed values could range from 0.31 to 5.55 gCO2eq/LETOH. A biomass-to-ethanol industrial scenario was used to evaluate the impact of methodological choices on CO2eq: conventional versus dynamic Life Cycle Assessment; different impact assessment methods (TRACI, IPCC, ILCD, IMPACT, EDIP, and CML); electricity mix of the geographical region/country for different factory locations; differences in CO2eq factor for CH4 and N2O due to updates in Intergovernmental Panel on Climate Change (IPCC) reports (5 reports so far), different factory operational lifetimes and future improved productivities. Results showed that the electricity mix (factory location) and land use are the factors that have the greatest effect (up to 800% deviation). The use of the CO2 equivalency factors stated in different IPCC reports has the least influence (less than 3%). The consideration of the biogenic emissions (uptake at agricultural stage and release at the fermentation stage) and different allocation methods is also influential, and each can make values vary by 250%. [ABSTRACT FROM AUTHOR]