Environmental, economic and social impact of aviation biofuel production in Brazil

Cremonez, Paulo André; Feroldi, Michael; Oliveira, Carlos de; Teleken, Joel Gustavo; Alves, Helton José; Sampaio, Sílvio César

doi:10.1016/j.nbt.2015.01.001

Cited by 25 publications

(8 citation statements)

References 91 publications

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“…As the development of energy crops changes prior to land operation, indirect land-use changes occur [97]. The transition to land use is the most important one for the development of palm oil biodiesel for net GHG emissions, which could have been reduced by 80% if depleted soil could have been used instead of natural rainforest or converted to tourism [98,99]. The land use change results in soil carbon sequestration to increase the mitigation of biofuel.…”

Section: Impact On Land Usagementioning

confidence: 99%

Biodiesel and green diesel generation: an overview

Vignesh¹,

Kumar

Ganesh

et al. 2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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First, second, third, and fourth-generation biofuels are continuously evolving as a promising substitute to petrodiesel catalyzed by energy depletion, economic and environmental considerations. Bio-diesel can be synthesized from various biomass sources, which are commonly divided into FAME and renewable biodiesel. FAME biodiesel is generally produced by the transesterification of vegetable oils and fats while renewable diesel is produced by hydro-deoxygenation of vegetable and waste oils and fats. The different generation, processing technologies and standards for FAME and renewable biodiesel are reviewed. Finally, the life cycle analysis and production cost of conventional and renewable biodiesel are described.

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Section: Impact On Land Usagementioning

confidence: 99%

Biodiesel and green diesel generation: an overview

Vignesh¹,

Kumar

Ganesh

et al. 2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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“…Cremonez et al . () recognize the three major outcomes that inclined from the production of biofuels, that is, economic impact, environmental preservation, and societal benefits in Brazil. The results derive that there is substantial need to improved the production routes of biofuel energy with lowering cost of production, as the raw material used in biofuels production mostly linked with the nitrous oxide emissions that may affect on agricultural productivity loss, threatened wildlife, and intensive water usage that impact on the productivity loss, environmental degradation, and social problems in the society.…”

Section: Introductionmentioning

confidence: 99%

Utilizing biofuels for sustainable development in the panel of 17 developed and developing countries

Öztürk

2015

GCB Bioenergy

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This study investigates the dynamic linkages between biofuels production and sustainable indicators in the panel of 17 developed and developing countries, over the period of 2000-2012. The study emphasized the role of biofuels production in the sustainable development of the region. For this purpose, the study utilized four main sustainable indicators including carbon dioxide emissions, energy intensity, renewable energy generation, and total population that have a significant impact on the biofuels production. The study used dynamic heterogeneous panel econometric technique -Generalized Method of Moments and found that carbon dioxide emissions increase along with the increase in biofuels production. Therefore, the caution should be applied when burning the biofuels during the production process. In addition, renewable electricity generation also increases the biofuels production in the region. The results of robust least square regression confirmed that all of the sustainable indicators have a significant association with the biofuels production, as total primary energy consumption increases the biofuels production, while total population significantly decreases the biofuels production in the region. The results derived to the conclusion that for sustainable development in the region, the policymakers should have to formulate carbon free policies that coupled with the renewable energy sources for emphasizing the life cycle of bioenergy during the production process.

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“…For the validation of the predictive power of the ANN model, two basic principles (internal validation and external validation) are available. In this study, the internal validation was used to evaluate the internal predictive ability of the developed models, and its result was defined as Q 2 LOO (see Eq. (9)) 27 and the external validation to determine both the generalizability and the true predictive ability of the ANN models for new chemicals, by splitting the available dataset into a training set and an external prediction set, and its result was defined as Q 2 ext (see Eq.…”

Section: Internal and External Validationmentioning

confidence: 99%

“…Over the last 10 to 20 years, these environmental concerns have led to the intensification of studies inherent to the search for alternatives to conventional fuels. 2 Among the developed alternatives that have significantly lower greenhouse gas emissions than conventional fuel, biofuels are presented as an attractive renewable energy source that is environmentally friendly. 3 The raw materials used for the production of biofuels are of biological origin and are therefore renewable.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Models for Prediction of Density and Kinematic Viscosity of Different Systems of Biofuels and Their Blends with Diesel Fuel. Comparative Analysis

et al. 2020

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In the present article, two models based on the artificial neural network methodology (ANN) have been optimised to predict the density (ρ) and kinematic viscosity (μ) of different systems of biofuels and their blends with diesel fuel. An experimental database of 1025 points, including 34 systems (15 pure systems, 14 binary systems, and 5 ternary systems) was used for the development of these models. These models use six inputs, which are temperature (T) in the range of −10 – 200 °C, volume fractions (X1, X2, X3) in the range of 0–1, and to distinguish these systems, we used kinematic viscosity at 20 °C in the range of 0.67–74.19 mm2 s–1 and density at 20 °C in the range of 0.7560–0.9188 g cm–3. The best results were obtained with the architecture of {6-26-2: 6 neurons in the input layer – 26 neurons in the hidden layer – 2 neurons in the output layer}. Results of comparison between experimental and simulated values in terms of the correlation coefficients were: R2 = 0.9965 for density, and R2 = 0.9938 for kinematic viscosity. A 238 new database experimental of 4 systems (2 pure systems, 1 binary system, and 1 ternary system) was used to check the accuracy of the two ANN models previously developed. Results of prediction performances in terms of the correlation coefficients were: R2 = 0.9980 for density, and R2 = 0.9653 for kinematic viscosity. Comparison of validation results with those of the other studies shows that the neural network models gave far better results.

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Environmental, economic and social impact of aviation biofuel production in Brazil

Cited by 25 publications

References 91 publications

Biodiesel and green diesel generation: an overview

Biodiesel and green diesel generation: an overview

Utilizing biofuels for sustainable development in the panel of 17 developed and developing countries

Artificial Neural Network Models for Prediction of Density and Kinematic Viscosity of Different Systems of Biofuels and Their Blends with Diesel Fuel. Comparative Analysis

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