International Journal of Global Environmental Issues
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International Journal of Global Environmental Issues (2 papers in press)
Environmental impacts of industrial ethanol production in Brazil: A life cycle analysis assessment with research data inventory by Flavio Numata Junior, Cassia M. L. Ugaya Abstract: Biofuels are a rich source of energy for the world. First-generation (1G) ethanol has been used for decades, and the potential of second-generation (2G) lignocellulosic ethanol has already been recognized. Now, the productivity of third-generation (3G) ethanol derived from algae is predicted to be ten times higher than current levels. Consequently, industrial technological development is moving at a rapid pace to meet the demands of clean fuel production whose environmental effects are still largely unknown. To help fill this gap, this study aims to measure how future generations of ethanol will impact industrial processes in Brazil up to the year 2050. It analyzes the industrialization of 1G, 2G, and 3G ethanol and uses the Life Cycle Assessment (LCA) technique as a method to measure environmental impact. The data inventory draws from fundamental bioethanol studies that have long considered the anticipated variables involved in industrial manufacturing technology. The results of this study show that the industrialization of ethanol generates acidification, primarily when fermentation produces sulfuric acid in the integrated system of 1G and 2G. Even greater discharges are observed in 3G during an esterification process generated by the glycerin. A general assessment of the landscape indicates that processes adopting thermochemical technological routes have more positive contribution. In fact, employing biochemical processes could minimize environmental effects by producing fewer emissions and pollutant residues. Keywords: environmental impacts; Life-cycle assessment; industrial processes; ethanol.
Factors affecting cyanobacterial blooms and their prediction in a tropical water supply reservoir by Aline Almeida De Jesus Magalhães, Lafayette Dantas Da Luz, Terencio Rebello De Aguiar Junior Abstract: In this study, our objectives were to determine the factors affecting cyanobacterial bloom and predict the abundance and probability of bloom occurrence in the tropical reservoir using generalized linear models (GLMs) with negative and positive binomial distributions. The water quality, weather, and water level data in the reservoir during 2006-2015 were used to develop the models. The results pointed out that 1) Predictive modelling using binomial distribution was the strongest and most parsimonious GLM; 2) Total P and electric conductivity were positive factors, whereas 30-d mean water level and dissolved Al were negative factors; 3) Water level had a strong significant effect on the probability of bloom events, while total phosphorus was not statistically significant and thus was not the major factor. The set of GLMs was not only an effective tool for identifying key contributing factors affecting cyanobacterial blooms, but also to improve the management of eutrophic tropical reservoirs. Keywords: Cyanobacterial blooms; environmental factors; bloom prediction; bloom occurrence probability; tropical reservoir; human supply reservoir; eutrophic reservoir; modelling; generalized linear model; negative binomial distribution; binomial distribution; water level; total phosphorus; South America; Brazil.