A review of properties, occurrence, fate, and transportation mechanisms of contaminants of emerging concern in sewage sludge, biosolids, and soils: recent advances and future trends
Bibliographic record
Abstract
Treated sewage sludge, or biosolids, are used worldwide to improve soil quality and fertility due to their high organic matter content and micro- and macronutrients. However, biosolids also introduce contaminants into the environment. This review assessed recent publications on the occurrence, environmental fate, and transportation mechanisms of 419 contaminants of emerging concern (CEC) across four matrices: sewage sludge, biosolids, soils, and dust. Among these, 229 CECs were positively detected at least once. The review focuses on various CECs, including 18 therapeutical classes of pharmaceutical products, personal care products (parabens and chlorophenolic antimicrobials), hormones, plastic-related compounds (bisphenols and phthalates), rubber antioxidants (substituted diphenylamines and para-phenylenediamines), and neonicotinoid insecticides. Phthalates dominate biosolid composition, accounting for over 97% of the total weight of CECs investigated, followed by pharmaceuticals (1.87%), personal care products (0.57%), hormones (0.09%), antioxidants (0.07%), and bisphenols (0.05%). The 50 most prevalent contaminants include phthalates [e.g., di (2-ethylhexyl) phthalate-DEHP, butyl benzyl phthalate-BBzP], antifungals (e.g., miconazole-MCZ, ketoconazole-KTZ), chlorophenolic antimicrobials (e.g., triclocarban-TCC, triclosan-TCS), fluoroquinolone antibiotics (e.g., ofloxacin-OFL, ciprofloxacin-CPF), cardiovascular medications (e.g., telmisartan-TMS, propafenone-PPF), analgesics (e.g., salicylic acid-SA, naproxen-NPX), hormones (e.g., mestranol-EEME, progesterone-P), antidepressants (e.g., sertraline-SRT, amitriptyline-AMT), and lipid regulators (e.g., fenofibrate-FNF). Analytical techniques like matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) have emerged as a valuable tool for qualitative analysis, allowing for identifying CECs in biosolids. The environmental fate and transport dynamics of studied CECs are influenced by their physicochemical properties (water solubility, volatility, degradation time, sorption capacity, and bioaccumulation potential) and environmental conditions (temperature, pH, and moisture content). Furthermore, soil characteristics, such as composition, organic matter, and microbial activity, play key roles in their adsorption, degradation, and persistence in soil environments. Additionally, wastewater treatment processes impact the transformation and removal of CECs, affecting their degradation and partitioning between treated effluents and sewage sludge.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".