Neem Biodiesel - A Sustainability Study
Bibliographic record
Abstract
Azadiractha Indica (Neem) is one of the promising tree species suitable for providing oil for biodiesel production.This paper addresses the life cycle assessment (LCA) with respect to, global warming potential, acidification potential and energy balance of a small scale biodiesel system using Neem oil as feedstock, in rural Karnataka (a southern state in India).The environmental impacts have been bench marked with the life cycle impacts of fossil diesel system and Jatropha.Global warming potential of Neem biodiesel life cycle (338 gCO2-eq Functional Unit -1* ) was found be 1.2 times higher than fossil diesel system (280 gCO2-eq Functional Unit -1 ) and 2.7 times higher than Jatropha biodiesel system(123.7 gCO2-eq Functional Unit -1 ).Acidification potential of Neem system was found to be negligible.It is observed that one hectare of Neem plantation is capable of sequestering the 1.35t of biogenic CO2 released during the Neem biodiesel life cycle, with additional sequestration potential of 8.65 t CO2 ha -1 .Net energy ratio of Neem biodiesel life cycle (22.06)has been found to be 26 times higher than fossil Diesel system and twelve times higher than Jatropha system (1.85).This life cycle study revealed that producing biodiesel from Neem oil is ecologically sustainable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".