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Record W1606309688 · doi:10.5772/16452

Can Biofuels be an Engine for Growth in Small Developing Economies – The Case of Paraguay

2011· book-chapter· en· W1606309688 on OpenAlexafffund
Anil Hira

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversityUniversity of Illinois at Urbana-ChampaignInternational Development Research CentreGovernment of CanadaAlfred P. Sloan Foundation
KeywordsBiofuelEconomicsBusinessEngineeringWaste management

Abstract

fetched live from OpenAlex

This analysis examines the feasibility of setting up a biofuels sector in Paraguay. As a small agriculturally-based country, Paraguay can serve as an interesting test case for the feasibility of creating ethanol in other small developing countries, such as those in Central America. Our analysis is inspired by previous work on the remarkable success of Brazil's ethanol industry More than 80% of Brazil's cars can run on a spectrum of gas and alcohol blends based on local sugarcane supply and processing. Ethanol reduces dependency on politically volatile and expensive petroleum imports. The International Energy Administration, along with other recognized international energy institutions, states that while demand will continue to increase over the long-term, prospects for supply meeting that demand "are extremely uncertain (IEA, 2008, 3)." A viable biofuels sector could help Paraguay to improve energy security and reliability, spur economic growth and reduce external dependence, improve employment and rural development, possibly create a new export industry, and reduce greenhouse gas emissions. We focus here on sugarcane ethanol. Sugarcane ethanol is the most attractive option, the only feedstock currently providing an economically feasible substitute at an estimated oil price of $70/barrel, and is more environmentally friendly than other feedstocks as waste is burned for electricity cogeneration. Sugarcane ethanol also produces less carbon emissions than petroleum. As a recent report states, there is no explicit policy at present for biofuels in Paraguay (IICA, 2007, 54). This report is based on secondary analysis and field research conducted during July 2009. We note here the severe constraints on primary data, requiring a more qualitatively-oriented approach. We organize our analysis around an examination of the following factors: agricultural, economic, and governance. The problem of sustainability must be addressed by any plan along with economic/financial feasibility, however, we believe that this question is adequately answered in a number of analyses that demonstrate that sugarcane ethanol, if conducted with safeguards, is a net reducer of carbon emissions

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.221
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2011
Admission routes2
Has abstractyes

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