Inhibition of soil microbial activity by nitrogen-based energetic materials
Bibliographic record
Abstract
Abstract We investigated individual toxicities of the nitrogen-based energetic materials (EMs) 2,4-dinitrotoluene (2,4-DNT); 2-amino-4,6-dinitrotoluene (2-ADNT); 4-amino-2,6-dinitrotoluene (4-ADNT); and nitroglycerin (NG) on microbial activity in Sassafras sandy loam (SSL) soil, which has physicochemical characteristics that support very high qualitative relative bioavailability for organic chemicals. Batches of SSL soil for basal respiration (BR) and substrate-induced respiration (SIR) assays were separately amended with individual EMs or acetone carrier control. Total microbial biomass carbon (biomass C) was determined from CO2 production increases after addition of 2500 mg/kg of glucose–water slurry to the soil. Exposure concentrations of each EM in soil were determined using US Environmental Protection Agency method 8330A. Basal respiration was the most sensitive endpoint for assessing the effects of nitroaromatic EMs on microbial activity in SSL, whereas SIR and biomass C were more sensitive endpoints for assessing the effects of NG in soil. The orders of toxicity (from greatest to least) were 4-ADNT > 2,4-DNT = 2-ADNT > NG for BR; but for SIR and biomass C, the order of toxicity was NG > 2,4-DNT > 2-ADNT = 4-ADNT. No inhibition of SIR was found up to and including the greatest concentration of each ADNT tested in SSL. These ecotoxicological data will be helpful in identifying concentrations of contaminant EMs in soil that present acceptable ecological risks for biologically mediated processes in soil. Environ Toxicol Chem 2017;36:2981–2990. Published 2017 Wiley Periodicals Inc. on behalf of SETAC.This article is a US government work and, as such, is in the public domain in the United States of America.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".