Land Farm Design and Management in Bolivia: A Case-Study
Bibliographic record
Abstract
Abstract An environmental liability audit of Empresa Petrolera Chaco, S. A. (CHACO), a BP Amoco/Bridas entity and the Bolivian Pension Funds joint venture, identified approximately 55,000 m3 of TPH (Total Petroleum Hydrocarbon) contaminated soils and wastes from prior operations requiring remediation. In addition, ongoing operations required a cost effective approach to oily waste disposal. Operations sites were remote and widely scattered, having a wide range of climatic conditions and limited availability of equipment. Land farming, a well-accepted technique in North America was identified as the most cost effective method for treating these oil-contaminated materials. Land farming had never been done in Bolivia and there were no specific regulations for treatment of oil-contaminated soils. Modified designs from Canada and the United States were used to prepare land farm designs and management guidelines. The first site, Los Cusis Land Farm, was established in the subtropical humid forest region north of Santa Cruz. High rainfall and a shallow ground water table required careful planning and monitoring of soils and near surface ground water. First year results showed reductions of TPH from highs of 15% in applied wastes, to less than 1% in treated soils within a seven-month period. Environmental monitoring of groundwater and soils confirmed treatment areas had little or no impact on shallow groundwater. A second site, Exploration Well #2 Land Farm, was established in the dry temperate forest region south of Santa Cruz. The third site, Camatindi Land Farm, is under construction in a mountainous region in the southern part of the country. The land farming technique has been a success story for CHACO, due to careful design for appropriate environmental conditions and social concerns, proper management of contractors and reliable sampling and laboratory analysis. This paper provides a summary of design parameters, management procedures and bio-remediation volumes and rates, for the Los Cusis and Exploration Well #2 sites.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".