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Record W2088025776 · doi:10.1007/s11356-014-2508-5

Nano-silver in drinking water and drinking water sources: stability and influences on disinfection by-product formation

2014· article· en· W2088025776 on OpenAlexaffabout
Anca-Maria Tugulea, D. Bérubé, M. Giddings, France Lemieux, Joan Hnatiw, Jessica Priem, Mary‐Luyza Avramescu

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsHealth Canada
Fundersnot available
KeywordsChlorineEnvironmental chemistryChemistrySilver NanoWater treatmentSurface waterDisinfectantPortable water purificationChloramineSodium hypochloriteEnvironmental sciencePulp and paper industryEnvironmental engineeringNano-Chemical engineering

Abstract

fetched live from OpenAlex

Nano-silver is increasingly used in consumer products from washing machines and refrigerators to devices marketed for the disinfection of drinking water or recreational water. The nano-silver in these products may be released, ending up in surface water bodies which may be used as drinking water sources. Little information is available about the stability of the nano-silver in sources of drinking water, its fate during drinking water disinfection processes, and its interaction with disinfection agents and disinfection by-products (DBPs). This study aims to investigate the stability of nano-silver in drinking water sources and in the finished drinking water when chlorine and chloramines are used for disinfection and to observe changes in the composition of DBPs formed when nano-silver is present in the source water. A dispersion of nano-silver particles (10 nm; PVP-coated) was used to spike untreated Ottawa River water, treated Ottawa River water, organic-free water, and a groundwater at concentrations of 5 mg/L. The diluted dispersions were kept under stirred and non-stirred conditions for up to 9 months and analyzed weekly using UV absorption to assess the stability of the nano-silver particles. In a separate experiment, Ottawa River water containing nano-silver particles (at 0.1 and 1 mg/L concentration, respectively) was disinfected by adding sodium hypochlorite (a chlorinating agent) in sufficient amounts to maintain a free chlorine residual of approximately 0.4 mg/L after 24 h. The disinfected drinking water was then quenched with ascorbic acid and analyzed for 34 neutral DBPs (trihalomethanes, haloacetonitriles, haloacetaldehydes, 1,1 dichloro-2-propanone, 1,1,1 trichloro-2-propanone, chloropicrin, and cyanogen chloride). The results were compared to the profile of DBPs obtained under the same conditions in the absence of nano-silver and in the presence of an equivalent concentration of Ag(+) ions (as AgNO3). The stability of the nano-silver dispersions in untreated Ottawa River water, with a dissolved organic carbon concentration of 6 mg/L, was significantly higher than the stability of the nano-silver dispersions in distilled, organic-free water. Nano-silver particles suspended in the groundwater agglomerated and were quickly and quantitatively removed from the solution. Our data confirm previous observations that natural dissolved organic matter stabilizes nano-silver particles, while the high-ionic strength of groundwater appears to favor their agglomeration and precipitation. As expected, nano-silver was not stable in Ottawa River water through the chlorination process, but survived for many days when added to the Ottawa River water after treatment with chlorine or chloramines. Stirring appeared to have minimal effect on nano-silver stability in untreated and treated Ottawa River water. The profile of DBPs formed in the presence of nAg differed significantly from the profile of DBPs formed in the absence of nAg only at the 1 mg/L nAg concentration. The differences observed consisted mainly in reduced formation of some brominated DBPs and a small increase in the formation of cyanogen chloride. The reduced formation of brominated congeners may be explained by the decrease in available bromide due to the presence of Ag(+) ions. It should be noted that a concentration of 1 mg/L is significantly higher than nAg concentrations that would be expected to be present in surface waters, but these results could be significant for the disinfection of some wastewaters with comparably high nano-silver concentrations.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.279
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations47
Published2014
Admission routes2
Has abstractyes

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