Conventional Water Filter (Sand and Gravel) for Ablution Water Treatment, Reuse Potential, and Its Water Savings
Bibliographic record
Abstract
Ablution process consumes a huge amount of water especially in mosques for cleaning certain part of the body before performing prayers. The high volume of ablution water produced in mosques and its low strength in quality makes it a feasible option to be reused. This paper introduced an assessment of conventional filtration (sand and gravel) in treating ablution water for reuse purposes and its water savings potential in mosques. The treatment system has assessed its capability for reuse and its water savings potential. A pilot scale of filtration system was developed and was run with the ablution water from the Parit Raja mosque and the Pintas Puding mosque. The samples were taken during Friday noon prayer between January to March 2013. The efficiency of the conventional filtration system was tested for the effluent quality of NH3, TSS, COD, and BOD. The case study of water savings estimation for the proposed system was undertaken at Pintas Puding mosque. It was determined based on the quantity of ablution water, water consumption, water demand, and water bills record. The results deduced that the conventional sand filtration can improve the water quality parameters; 0.60-0.05mg/L reduction of nitrogen ammonia (NH3), 6.0-1.53mg/L of suspended solids (TSS), 3.12-0.15mg/L of chemical oxygen demand (COD), and 27.67-4.16mg/L of biochemical oxygen demand (BOD). The treatment system was projected to save water consumption by 41.73% and RM180.16 of water saving per month. Water consumption was estimated to be further reduced to 50.83% if reused activities such as irrigation and toilet flushing were applied. Hence, annual water savings could reach up to RM2161.92 per year. With the current instability of water resources, the implementation of the conventional filtration system for ablution water in the mosques provides water security and water resources conservation option for the country.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".