Flare Pollution Loads and Carbon-Dioxide Effect on Rainwater Acidity in Niger-Delta: A Review, Investigation and Model for Safe Living Quarter
Bibliographic record
Abstract
Carbon-dioxide does not only affect climate change, but also contribute tremendously in acidification of rain water. Hazard identification and risk assessment are fundamental components of effective risk management, specifically in sensitive areas where adverse effects can have significant consequences. This study provides novel methodology for environmental and safety assessment of flared gases in sensitive areas such as residential homes. Distancing Sampling Technique (DST) was used to investigate the sensitivity of rain water pH at distances away from flare site in order to develop a Risk Management Model for sensitive regions. First, a review on rain water acidity was made around flaring and non-flaring areas in Niger-Delta states, which revealed Moderate-High acidity effect around flaring zones and no effect on non-flaring zone. Secondly, Flared Gas Quantification, pH Experimental Evaluation (PEE) and Risk Assessment Matrix (RAM) were the three systematic approaches used respectively to quantify, measure and evaluate the effects of CO2 and other flare pollutants around the area of study. An average of 809,300,000 Mscf of associated petroleum gases were flared around the oil and gas producing areas in Delta State, causing a release of around 43x106 tons of CO2 from 2012-2022. Experimental results showed the range of pH from 4.56 ± 0.06 to 5.10 ± 0.06 for the 33 samples of harvested rainwater in Kwale community, Delta state causing a deviation of 16.38 to 30.05% from standard. The developed and validated model suggests 4.81KM radius as the safe distance for human habitation from flare sites. Based on these findings, carbon-capture and sequestration projects must be activated in Niger-Delta to curb the menace.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".