Modeling of SO2 and CH4 Emission Distribution in the Area Mataloko Geothermal Power Plant, East Nusa Tenggara, Indonesia
Bibliographic record
Abstract
The Mataloko geothermal system in Ngada-Flores Regency, East Nusa Tenggara, is located in three active volcanic mountains (Inerie, Ebulobo, and Inielika). The contribution of high levels of CH4 and exhaust emissions of SO2 due to its utilization as a geothermal power plant (GPP) impacts the environment. This study aims to analyze and spatially model the distribution and impact of SO2 and CH4 gas levels in the Mataloko GPP area. The quantitative descriptive method was used through direct measurement at gas wells and laboratory testing. The results showed a tendency to increase SO2 levels in the MT-4 gas-well with levels of 8.00 ppm exceeding the quality standard, which could disturb the environment in the Mataloko-GPP area. Impact of high SO2 will experience dry sediment because it is not combustible in the air, then it will drop slowly to be absorbed by soil and plants. Droplets of acid gas blown by the wind and left on trees and buildings are even inhaled into the breath. In addition, the advantages of model with surfer 12 software can help identify the distribution of SO2 and SO4 emissions in the generating area.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".