Phosphorus and Emerging Micro-pollutants in Surface Waters: Challenges and Prospects for Water Quality Improvements
Bibliographic record
Abstract
An oversupply of Phosphorus in water bodies accelerates growth of algae and higher forms of plant life to produce undesirable impacts on overall water quality. Phosphorus inputs to surface waters arise from a variety of point and nonpoint sources. However much of the P is contributed by agricultural runoff and outfall of treated (or untreated) wastewater in receiving water-bodies. Point sourced-P inputs to waters have considerably decreased in recent years, at least partly driven by regulatory requirements, e.g. the EU Water Framework Directive. This has largely been achieved by removing P from treated wastewaters at sewage treatment works (STWs). Studies have shown that introducing an additional treatment step (“P-stripping”) can significantly reduce P in STW outfalls. Given P deposits are depleting, there is much interest in phosphorus recovery from wastewaters. A few STWs have already started to recover P as struvite (NH4MgPO4.6H2O) mineral – a substitute for commercially produced P-fertilizers. This requires major investment and is not economically viable at small STWs. Nonetheless it is a major breakthrough in terms of P recovery and its use. Effluents from sewage treatment works (STW) can often contain a complex mixture of residual microcontaminants, not removed during wastewater treatment. Organic micro-pollutants have been found in rivers receiving STW effluents. Such residual contaminants have become the focus of an emerging field of water quality study and are collectively referred to as pharmaceuticals and other personal healthcare products, PPHCPs. Many of these chemicals have the ability to effect the hormonal signaling of organisms and are called endocrine disrupting compounds (EDC). Such chemicals have shown some of the most damaging biological effects in aquatic organisms. Biological effects in the aquatic environment are typically related to the development of intersex in fish. Recent research shows the use of STW practices such as upgrading from using a combined trickling filter contact process to activated sludge treatment, ozonation, membrane filtration and use of suspended biofilm reactors reduces the amount of EDCs in waste effluent. It is thus possible to remove contaminants from STW effluents, but it will not be possible without major infrastructure improvements. This paper presents the challenges and prospects of P and micro-organic pollutants in surface waters.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".