Monitoring Organic Contaminant Concentrations and Carbon Mineralization in Field Soils Receiving Alkaline-Stabilized Biosolids
Bibliographic record
Abstract
The application of municipal sewage biosolids to agricultural land is a common practice worldwide. Increasing attention is being directed at the presence of organic contaminants bound to the organic phase during wastewater treatment, which end up in the biosolids. The goal of this study was to investigate the decomposition of an alkaline-stabilized biosolid being used as an agricultural soil amendment containing unknown organic contaminants. A two year field trial and a 120 day laboratory soil incubation using increasing rates (0, 7, 14, 28, and 42 Mg ha-1) of an alkaline-stabilized biosolid (ASB) were set up to monitor biosolid decomposition and concentrations of selected contaminants over time. The seven contaminants selected for monitoring (p-cresol, indole, 4-t-octylphenol, phenanthrene, triclosan, carbamazepine, and benzo[a]pyrene) represent a wide range of physico-chemical properties and fall under several different chemical classes. The decomposition of ASB in soil was examined in the incubation study. Almost half of the CO2-C evolved from ASB amended soils occurred within the first 6 days, indicating that a relatively labile pool of carbon remains in ASB following the sewage treatment process. By day 121, between 71 to 78% of the total carbon added to soil had been evolved as CO2-C. A new model developed during this study to describe carbon mineralization, a first order plus logistic function (FLOG), performed better than other commonly used models. The method chosen to analyze organic contaminants in soil was only able to determine four out of seven compounds reliably, with recoveries greater than 50% for 4-t-octylphenol, phenanthrene, triclosan, and benzo[a]pyrene. In treated soils, only triclosan was able to be detected and quantified. Average triclosan concentration in the incubation study ranged from a high of 143 ng g-1 on day 3 to a low of 26 ng g-1 by day 121, representing an 81% decrease over a roughly 4 month period under idealized conditions. In the field, triclosan concentrations following a Fall biosolids application in Oct. 2008 increased to detectable levels (29 to 47 ng g-1) in all three plots measured in Nov. 2008, which remained elevated (29 to 66 ng g-1) over the winter period in two out of three plots when sampled in May 2009. Following the Spring application in June 2009, measured triclosan concentrations in July 2009 samples from these same two plots were lower than predicted (33 to 48 ng g-1) and eventually decreased to levels below the detection limit by the Oct. 2009 sampling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".