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EC number: 243-957-1 | CAS number: 20667-12-3
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
![](https://echa.europa.eu/o/diss-blank-theme/images/factsheets/A-REACH/factsheet/print_environmental-fate-and-pathways.png)
Additional information on environmental fate and behaviour
Administrative data
- Endpoint:
- additional information on environmental fate and behaviour
- Type of information:
- calculation (if not (Q)SAR)
- Remarks:
- modelling removal Ag from water column using TICKET-UWM
- Adequacy of study:
- key study
- Study period:
- 2013
- Reliability:
- 1 (reliable without restriction)
- Rationale for reliability incl. deficiencies:
- test procedure in accordance with generally accepted scientific standards and described in sufficient detail
Data source
Reference
- Reference Type:
- study report
- Title:
- Unnamed
- Year:
- 2 013
Materials and methods
- Principles of method if other than guideline:
- The model builds on previous screening-level calculations that have been developed for organic contaminants. Unlike previous models, however, the UWM for Metals in Lakes explicitly considers the effects of chemical speciation on metal partitioning, transport and bioavailability in the lake water column and underlying sediments. The numerical engine for the model calculations is the Tableau Input Coupled Kinetics Equilibrium Transport (TICKET) model (Farley et al., 2008). Specific processes considered in the UWM for Metals in Lakes (hereafter referred to as the TICKET-UWM) include:
1. dissolved and particulate phase transport between the overlying water and sediment;
2. metal binding to inorganic ligands, DOC and POC (using information from WHAM V (Tipping and Hurley, 1992; Tipping, 1993; Tipping, 1994), HFO (Dzombak and Morel, 1990), and HMO (Tonkin et al., 2004);
3. metal binding to biological receptors using information from the Biotic Ligand Model (Di Toro et al., 2001a; Santore et al., 2001);
4. metal precipitation as (hydr)oxides, carbonates and sulfides using information from MINEQL+ software (Schecher and McAvoy, 2003);
5. dissolution kinetics for metal powders, massives, etc.;
6. average-annual cycling of organic matter and sulfide production in the lake; and
7. simplified hydrous ferric oxide (HFO) and hydrous manganese oxide (HMO) cycles (HydroQual and Manhattan College, 2010).
Currently, the TICKET-UWM domain consists of a single oxic water column layer and a single sediment layer. The redox state of the sediment (oxic or anoxic) is specified by the user and refers to the set of metal binding phases included in the sediment compartment. For oxic sediment, sulfide production and metal sulfide precipitation are not considered. Metals sorb to POC, HFO, and HMO in the sediment and can precipitate as carbonates, hydroxides, and/or sulfates. For anoxic sediment, metal binding to HFO and HMO is not considered. Metals sorb to POC and can precipitate as sulfides, carbonates, hydroxides, and/or sulfates.
The TICKET-UWM algorithm was constructed as a general solver, with all information on chemical species, chemical equilibrium constants and kinetic rate coefficients stored in external databases. This allows for easy updating of model coefficients (e.g., the WHAM V and BLM binding constants).
Concerning hazard assessment, the TICKET-UWM is capable of assessing removal of soluble metal(loid)s from the water column resulting from changes of speciation and subsequent precipitation. This entails simulation of two sets of processes:
• Removal of soluble metal(loid) salts from the water column through speciation transformations and sedimentation of particulate metal; and
• metal(loid) fate in sediments including metal speciation transformations and remobilization potential in sediments (as indicated by sediment feedback and diffusive fluxes). - GLP compliance:
- no
Test material
- Reference substance name:
- Silver
- EC Number:
- 231-131-3
- EC Name:
- Silver
- Cas Number:
- 7440-22-4
- Molecular formula:
- Ag
- IUPAC Name:
- Silver
- Test material form:
- solid: nanoform
- Details on test material:
- PVP COATED
Particles of nanosilver from NanoAmor Inc., Houston, Texas were coated in 0.2 % polyvinylpyrrolidone. Silver nanoparticles were dissolved at a nominal concentration of 100 µg/L in moderately hard reconstituted water by constant stirring. The suspension was sonicated for 10 minutes, stirred at allowed for 5 minutes to settle before the top three quarters of the solution were drawn off into a clean beaker and stirred again. The manufacturer's description indicated a particle size of 35 nm and this was confirmed by transmission electron microscopy (TEM) images. The hydrodynamic diameter was 156 ± 2 nm by nanoparticle tracking analysis (NTA) indicating aggregation when dispersed in moderately reconstituted hard water (MRHW), with 11.3 ± 2.2 % of silver nanoparticles undergoing dissolution to silver ions.
CITRATE COATED
Particles of citrate coated nanosilver were prepared by adding 1 mM trisodium citrate to deionised water containing 1 mM AgNO3 at 70°C and heating until translucent green (approximately 2.5 hours). The resulting nanoparticles were washed several times in deionised water and three aliquots of the suspesion were analysed. Nanoparticles were determined to be ~40 nm by TEM images, with a hydrodynamic diameter of 65 ± 10 nm by nanoparticle tracking analysis (NTA) and 8.9 ± 1.6 % of silver nanoparticles underwent dissolution to silver ions.
CHARACTERISATION:
The size of the nanoparticles in suspesion were characterised using Transmission Electron Microscopy (TEM) and the extent of aggregation in moderately hard reconstituted water was determined by Nanoparticle Tracking Analysis (NTA), with the suspensions filtered for dissolution analysis.
Constituent 1
Results and discussion
Any other information on results incl. tables
Linear Partitioning Method
Based on the suspended solids concentration of 15 mg/L and the empirical log KD of 5.28, approximately 74% of the Ag added to the water column was bound to suspended particles. Thus, according to Approach 1 for calculating removal, the rapid removal benchmark was met immediately by virtue of equilibrium partitioning. Under the more conservative approach where removal is based on total Ag (Approach 2), the rapid removal benchmark was met 2.0 days after Ag addition. The time for rapid removal using Approach 3 was essentially equal to that for Approach 2.
Speciation Model Method
The key particulate Ag species in these simulations were precipitated Ag (AgCl(s)) and Ag sorbed to POC. Silver interaction with the carboxylic and phenolic functional groups comprising organic matter is generally weak (Carbonaro and Di Toro, 2007; Paquin and Di Toro, 2008). These functional groups are the dominant sites considered by WHAM V and, accordingly, Ag binding to DOC and POC in the TICKET-UWM simulations was limited. At the acute and chronic ERV values, where all Ag solids were undersaturated, model-predicted log KD were low (2.93 – 3.22), much lower than the empirical value of 5.28. Nevertheless, simulations with initial Ag concentrations at the chronic cutoff showed >70% removal withing 28 days for Approaches 1 and 2 and all three pH values. The precipitation of AgCl(s) resulted in approximately constant dissolved phase Ag concentrations. A 70% removal was not achieved according to Approach 3 (approach not relevant for Ag because of its strong binding to (in)organic ligands).
As a potential solution, the impact of Ca/Mg competition for DOC/POC binding sites was excluded from the speciation calculation. In general, with less competition for site on POC, log KD and removal rate increased and removal times decreased. The rapid removal benchmark was met for several cases for which it had not been met previously under the default WHAM V parameters. These cases include pH 7 and 8 simulations with starting Ag concentrations at the ERV values and 100 μg/L. However, at pH 6, greater than 28 days was still required to attain 70% removal. At the upper chronic cutoff value, greater than 70% removal in 28 days was achieved when considering Approaches 1 and 2. However, because of presence of AgCl(s) and its sustaining effect on dissolved Ag, rapid removal was not achieved at the upper chronic cutoff loading according to Approach 3 (approach not relevant for Ag because of its strong binding to (in)organic ligands).
At the acute and chronic ERV values, where all Ag solids were undersaturated, model-predicted log KD values (without Ca/Mg competition) ranged between 3.40 and 4.18. While this range represents an increase from the default case, it is still >=1 order of magnitude lower than the empirical water column log KD of 5.28. It is likely that at lower Ag concentrations, where silver precipitates are undersaturated, Ag binding is the result of multiple binding mechanisms including, but not limited to, sorption to POC. A series of sensitivity analyses were performed to test the impact of additional binding phases. In these simulations, additional binding phases were incorporated into the speciation submodel in addition to POC.
Model results indicate that the impact of HFO as an additional water column binding phase was negligible: the fraction of Ag bound to particles was essentially the same as with just POC. Another potential binding mechanism for Ag in the water column is complexation with inorganic and organic reduced sulfur, S(II−) which has been shown to be present in oxic waters (Bowles et al., 2003). The strong binding of Ag to dissolved phase sulfur ligands has been incorporated in the Ag biotic ligand model (BLM) (Paquin and Di Toro, 2008). The quantity chromium reducible sulfide (CRS) has been used as an estimate for the concentration of reduced sulfur ligands. Kramer et al. (2007) observed moderate correlation between CRS and TOC (r2 = 0.50) and parameterized a linear relationship between the two quantities :
CRS {nM} = 14.5 × TOC {mg/L}.
They suggest that in the absence of direct CRS determination, the linear relationship can be used to estimate CRS from TOC. The approach was used to obtain an estimate of the CRS for the TICKET-UWM. Based on the default DOC and POC values of 2 and 1.5 mg/L, dissolved and particulate CRS value of 29 and 22 nmol/L, respectively were estimated. Thus according to this approach, 43% of the CRS is particulate. In an alternate approach, available total and filtered CRS data were collected. Particulate CRS was taken as the difference between total and filtered CRS. These data indicate that, on average, approximately 28% of the CRS is particulate. For this approach, the TOC of the generalized lake system (3.5 mg/L) was used to estimate a total CRS of 51 nM based on Equation 3-3. According to the data from natural waters, 28% or 14 nM of the total CRS was specified as particulate with remainder of 37 nM as dissolved. Simulations were made using both approaches to estimate CRS. Binding of Ag to CRS was modeled using the same reaction stoichiometry and formation constant as the AgHS0 aqueous complex in the TICKET-UWM database. The formation constant value used was 13.6. This value is slightly greater than the value used in the HydroQual, Inc. BLM software (13.38), but still consistent with values in the literature as summarized in Richard and Luther (2006).
For the simulations with Ag binding to CRS, rapid removal is achieved using Approaches 1 and 2 at all initial Ag concentrations tested and for both methods of estimated CRS. With initial Ag at the chronic and acute ERVs, Ag binding to CRS increased the log KD relative to the default TICKET-UWM simulations and decreased 70% removal time to below 28 days. Although consideration of Ag-CRS binding increased the log KD values (from 3.22 to 4.41 – 4.70), there is still considerable discrepancy between calculated values and the empirical value of 5.28. In simulations with initial Ag at the upper chronic cutoff, precipitation as AgCl(s) remains the primary reason for rapid removal using Approach 1 and 2. In simulations with initial Ag at 100 μg/L, both precipitation and binding to CRS contributed to removal. Precipitation again prevented rapid removal according to Approach 3 (approach not relevant for Ag because of its strong binding to (in)organic ligands).
Silver Water Column Sensitivity Analysis Results
A sensitivity analysis was conducted to evaluate the critical depth at which exactly 70% removal was achieved in 28 days using Approach 1 for a system with an initial Ag at the acute ERV of 220 ng/L.
For the linear partitioning method, 70% removal occurs instantly via initial solid-solution equilibrium partitioning. Because of the relatively large empirical Ag surface water log KD of 5.28, 70% removal can still be attained in 28 days (under the more conservative Approach 2) at a depth that is more than ten times greater than the default generalized lake depth of 3 meters.
For the speciation model method simulations considering Ag interaction with water column DOC and POC only, relatively weak binding at the three water chemistries resulted in limited Ag removal such that depths less than 3 meters were required to produce 70% removal in 28 days. Preliminary assessments of silver binding to particulate CRS produced log KD values larger enough to facilitate 70% removal in 28 days for lake depths more than seven times the default value.
Another sensitivity analysis was conducted to assess removal with settling velocity decreased from the EUSES value of 2.5 m/d to 0.24 m/d. A settling rate of 0.24 m/d represents the lower end of the POC range from Burns and Rosa (1980). The simulation with linear partition method and the calculation with the high particulate CRS are the only cases where the log KD in the surface water was larger enough to counteract the slower settling velocity and allow for 70% removal within 28 days based on Approach 1.
Applicant's summary and conclusion
- Conclusions:
- In summary, model simulations indicated disparate behavior depending on the method chosen to quantify Ag partitioning to particles. Linear partitioning calculations using empirical log KD values indicate rapid loss of Ag from the water column in all scenarios and all conditions (i.e., greater than 70% in 28 days). However, in simulations where Ag speciation and partitioning to DOC/POC were calculated with WHAM V within TICKET-UWM, predicted log KD values were significantly lower than the empirical value and, as a result, removal in many cases was not rapid. Precipitation of Ag as AgCl(s) did in some cases hasten removal based on Approaches 1 and 2. Omission of the competitive effects of Ca/Mg and inclusion of Ag binding to CRS did increase predicted log KD values and resulted in rapid removal of silver under all relevant conditions (i.e., greater than 70% in 28 days).
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