Pathogen Survey of Pulp and Paper Mill Biosolids Compared with Soils, Composts, and Sewage Biosolids
Bibliographic record
Abstract
Regulatory policies to manage land application of organic materials are risk based, with focus on the quality of these residuals. The Ontario Ministry of the Environment and Climate Change (MOECC) determined that limited information was available on pulp and paper biosolids (PPB) with respect to human enteric pathogens. To address this data gap, MOECC conducted an extensive survey (2005–2006) across Ontario to characterize the microbiological quality of PPB. Quantitative testing was performed for fecal indicators ( Escherichia coli , enterococci, Clostridium perfringens ) and enteric pathogens ( Salmonella , Campylobacter , Shigella , Cryptosporidium, and Giardia ) using matrix‐validated methods. Comparative benchmark materials (soils and soil amendments) were analyzed concurrently for risk comparison. Results showed that detection rates in PPB were low, 5 to 25% for pathogens and <55% for E. coli . Salmonella , Cryptosporidium, and Shigella were found at low frequency (6–8% of samples) and at low mean concentrations (2 most probable number g −1 dry wt., 9 oocysts g −1 dry wt., and 7 cells g −1 dry wt., respectively). Giardia was more frequently observed (19% of samples), with a mean of 30 cysts g −1 dry wt. Pathogen concentrations in PPB were generally equivalent to or higher than those in soils, composts, and pelletized sewage biosolids but significantly lower than in sewage biosolids. Escherichia coli levels exceeded standards (1000 colony‐forming units g −1 dry wt.) in one‐third of samples, most often in fresh PPB rather than stored and lagoon solids. Microbial quality of PPB across all surveyed mills tended to be variable and sector‐ and/or site‐specific but in many cases would not consistently meet Canadian federal fertilizers standards. These findings were important to inform Ontario's nutrient management regulations, supporting classification of PPB as higher pathogen risk than compost and commercial fertilizers. Core Ideas Pathogens were found at low frequency in PPB but higher than in compost and soil. Bacterial prevalence is higher in recycled mill PPB compared with virgin fiber mills. E. coli is a poor indicator of fecal inputs in PPB; C. perfringens may be useful. PPB would not routinely meet E. coli , Salmonella standards of federal Fertilizers Regulations. Giardia were found in most mills, but molecular methods need improvement to inform risk.
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 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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".