Assessment of the Characteristics of the Municipal Solid Waste Compost in Lebanon
Bibliographic record
Abstract
Waste management is crucial due to the fast increase of human population, causing an increase in solid waste generation which if not properly managed causes environmental problems. Around 57% of the wastes generated from homes are made up of green material (fruits, vegetables…). Thus, reusing and recycling green wastes through composting is one way of reducing the waste load to landfills. Composting is the transformation of raw organic materials into organic soil amendments that provide nutrients to crops and enhance the tilth, fertility, and productivity of soils. Aerobic windrow composting system at Sukomi Greensite facility located at Karantina is performed, where materials biodegrade under controlled conditions to produce compost. However, assessment of the quality of the compost is fundamental in order to determine its usages. Thus, regular testing of physical, chemical and biological parameters was performed for adequate monitoring purposes. The basic objective of this study was to determine the characteristics of the Lebanese municipal solid waste compost on a yearly basis and compare these characteristics amongst the years. Hence, each parameter was tested and compared to the BNQ international Canadian standards for proper classification of the compost and adequate identification of its usages. The preliminary data obtained were statistically diagnosed through principal component analysis by Spadv55 software. All the data reflected the normal content value of the studied parameters with minor differences between the years except for year 2007 which demonstrated higher levels of Potassium, Phosphate, Lead and Cadmium. The characteristics of the compost enabled it to be used as a soil amendment on all types of agricultural and landscape commodities at the adequate dosages and proper timing. This data will additionally reflect the efficiency of the solid waste management practices adopted via highlighting the importance of the implementation of the integrated solid waste management practices.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".