Dodecaaluminium trimolybdenum dodecaoxide

Endpoint summary

Additional information

The environmental fate pathways and ecotoxicity effects assessments for aluminium metal and aluminium compounds as well as for molybdenum metal and molybdenum compounds is based on the observation that adverse effects to aquatic, soil- and sediment-dwelling organisms are a consequence of exposure to the bioavailable ion, released by the parent compound. The result of this assumption is that the ecotoxicological behaviour will be similar for all soluble aluminium and molybdenum substances used in the presented ecotoxicity tests. As aluminium molybdenum oxide has shown to be only slightly soluble in water (pH 4.5, 7d) and poorly soluble in ecotoxicity test media (pH 7.5-8.5, 96h), it can be assumed that under environmental conditions in aqueous media, the components of the substance will be present in a bioavailable form only in minor amounts (Mo) or hardly, if at all (Al). Within this dossier all available data from soluble and insoluble aluminium and molybdenum substances are taken into account and used for the derivation of ecotoxicological and environmental fate endpoints, based on the aluminium ion and molybdenum ion. All data were pooled and considered as a worst-case assumption for the environment. However, it should be noted that this represents an unrealistic worst-case scenario, as under environmental conditions the concentration of soluble Al³⁺and MoO₄^2-ions released from aluminium molybdenum oxide is negligible (Al) or low (Mo), respectively.

Aluminium

The aluminium (Al) toxicity studies compiled in this section represent tests with aquatic organisms conducted over a pH range from 6 – 8 as being representative of conditions in most European surface waters as evaluated in a preliminary exposure assessment (EURAS 2007). Most of the short-term studies included were only those used for purposes of characterization and to evaluate potential effects of water quality on Al toxicity. The long-term chronic studies represent all known studies of sufficient reliability according to Klimisch criteria levels one (reliable without restriction) and two (reliable with restriction; Klimisch et al. 1997). These data are being assessed with a view towards developing a Probable No Effect Concentration (PNEC) principally for use in setting Environmental Quality Standards (EQS) values. We point out that aluminium chloride was not classified for the aquatic environment by the EU Classification and Labeling Committee, therefore other less soluble forms of Al such as the oxides, powders, and massive metal would also not classify for the aquatic environment (see reference below). Therefore, no PNEC is required for REACH purposes. The long term goal of the industry is to develop an aquatic PNEC that covers the pH range of < 6, 6-7, and > 7. These pH ranges reflect that the form of Al present in water changes significantly as a function of pH. PNEC values calculated in this dossier are preliminary and reflect the state of the science to date. Scientists around the world have worked towards a PNEC for Al for the past 30 years. The aluminum industry over the past 3 years has utilized several decades of work to develop a biotic ligand model (BLM)fish, invertebrates and algae for pH values across the range of 5.5-8.0. The state of the model is summarized in this dossier. It is recognized that there is a need to demonstrate that this model applies to a broader range of aquatic organisms. Efforts to date have focused on salmonids, fathead minnows, daphnids and algae. Studies are on-going at pH 6.0 with a wider range of species to achieve a data base that has 8-10 chronic PNEC values as recommended in the London PNEC Workshop. The extent of this work to date is presented in this dossier. Studies that are on-going and envisioned for the future were provided to ECHA, July 2, 2010 for their notification.

 

For all of the aquatic toxicity studies, endpoints are expressed as a function of total Al, rather than as dissolved or monomeric Al. This is because for most test solutions with pH from 6 – 8, Al will be largely insoluble, and so dissolved and monomeric concentrations remain relatively constant even with large increases in total or nominal Al. Thus, dose-dependent responses observed by aquatic organisms can only be reliably quantified using total Al across the full pH range from 5.5-8.0. 

It is important to point out that the substances being registered in this dossier are sparingly soluble forms of aluminium and not soluble metal salts. Therefore the review of the aquatic toxicity literature where aluminium salts were used for assessing the toxicity of the metal ion or hydroxide have limited direct application to the substances represented in this dossier. The use of a PNEC, once derived, has to take into consideration the transformation/dissolution of the sparingly soluble aluminium compounds. There is little or no evidence that aluminium metal, metal powders or metal oxides have ever resulted in aquatic toxicity effects.

 

Review of Data Leading to Development of an Aluminium Chronic BLM: Toxic effects of aluminium have been observed in several types of aquatic organisms under certain exposure conditions. Factors that influence aluminium toxicity are consistent with the factors that influence aluminium speciation (discussed in Section 4.2). These factors include pH, dissolved organic matter concentration (DOC), and water hardness (see Roy and Campbell 1997; and Gensemer and Playle 1999 for relevant reviews). Fluoride has also been shown to influence aluminium toxicity (Hamilton and Haines 1995), though fluoride is not commonly found at elevated levels in the environment. Several studies have demonstrated that some forms of aluminium are only bioavailable and potentially toxic in freshly prepared solutions, and that this toxicity declines or is eliminated after several minutes of aging (e.g. Exely et al. 1996 [others too]; Witters et al. 1996; Teien et al. 2006). Toxicity in these cases may depend on short-lived transient chemical forms of aluminium hydroxide whose environmental relevance would be restricted to mixing zones where aluminium-rich acidic waters mix with a more alkaline water.

 

A biotic ligand model (BLM) was developed to address the bioavailability and toxicity of dissolved, particulate, and transient forms of aluminium. Application of the BLM framework to understanding aluminium toxicity was reasonable because many of the factors that influence aluminium bioavailability are consistent with the factors that influence aluminium speciation or forms in the environment. As with BLMs for other metals, the Al BLM combines information about chemical speciation and interaction with gill surfaces to explain and predict aluminium bioavailability and toxicity (DiToro et al, 2001; Santore et al 2001; Paquin et al 2002). Factors that affect aluminium bioavailability by altering the chemical speciation of the metal (such as DOC, pH, and fluoride) are directly considered by the speciation model (Tipping 1994; Santore and Driscoll, 1996).  Other factors (such as hardness cations), affect aluminium bioavailability by competing with gill binding sites in a manner similar to what has been observed for other metals (Playle et al 1992; Meyer et al, 1999) and are considered by including interactions for these cations with the BL sites on the gill. The detailed speciation within the aluminium BLM allows the model to predict bioavailability for a number of different aluminium fractions. Depending on available input data, the model can be run with monomeric, dissolved, or total aluminium as the primary input parameter, and the distribution among dissolved species and precipitated forms can be simulated by the model. Comparison of predicted and measured distribution of aluminium fractions in waters where aluminium toxicity has been extensively studied typically shows very good agreement (Figure7.1.1-1).

Factors that are known to affect speciation have also been shown to affect bioavailability and toxicity in both acute and chronic exposures, and the consistency of these affects in different exposure durations allows a common model framework for prediction of both acute and chronic affects. Acute data were useful in model development due in part to the large amount of available data that combined coincident measurement of detailed speciation measurements, measures of Al accumulation in gills, and observation of lethal and sub-lethal effects over wide ranges of water chemistry. Data for development of the Al BLM included Atlantic salmon (Salmo salar) and brown trout (Salmo trutta) from studies performed by NIVA and collaborators from UMB (Kroglund et al. 1997; Kroglund et al. 1998a,b,c,d; Erstad et al. 2002; Teien et al. 2004a,b; Teien et al. 2006; Andren et al. 2006). These studies typically investigated the effects of water chemistry on the accumulation of Al on/in the gills of S. salar and S. trutta, but in some cases, mortality was reported. Many of these studies purposefully investigated the effects of water chemistry on the level of Al accumulation in S. salar and S. trutta gills. The pH conditions varied from approximately pH 5 (Andren et al. 2006) to pH 10 (Erstad et al. 2002). The total organic carbon concentrations (TOC) ranged from approximately 0.5 mg/L to 16 mg/L (Kroglund et al. 1998a,b, and Erstad et al. 2002, respectively). Calcium concentrations ranged from approximately 1 mg/L to 11 mg/L (Kroglund et al. 1998a,b, and Erstad et al. 2002, respectively).

From these data it was clear that observed toxicity was strongly related to aluminium accumulation on the gill (Figure 7.1.1.-2). The calibrated Al BLM was able to reasonably predict the level of Al accumulation on the gills of S. salar and S. trutta, with one consistent set of BLM parameters (Figure 7.1.1.-3) over a range of approximately 2 orders of magnitude. This wide range in gill accumulation was primarily due to the diverse water chemistry conditions tested, and suggests that the BLM is relatively robust over this wide range of conditions. These data were also used to estimate critical Al accumulation levels for those datasets that reported associated mortality data (i.e. Suldal Fall 1997 – Kroglund et al. 1998a). For example, from Figure 7.1.1-2, critical accumulation levels corresponding to the LC10 and LC50 values for mortality could b derived as 2995 and 4225 nmol/g wet weight, respectively.   

Although data from acute exposures were extensively used to parameterize the prediction of gill-accumulation over a wide range of conditions, the goal in model development is the evaluation of the ability of the Al BLM to predict effects in chronic exposures. The use of data from both acute and chronic exposures in model development is justified by the consistency of the observed effects of changing water chemistry (such as pH, NOM, and hardness) in both acute and chronic exposures. Adjustment of the Al BLM for different exposure durations (acute versus chronic) and endpoints (lethal or sub-lethal) is primarily accomplished by adjustment of the critical accumulation level for each endpoint and exposure condition. Application to chronic data will be further discussed in the sections that follow

Soluble aluminium salts are not classified, therefore less soluble forms of aluminium are not classified.

Available data indicate that aluminium salts are relatively non toxic in most waters with circumneutral pH and this was sufficient for the EU Classification and Labelling Committee (1999) to determine that there was no need for classification of aluminium chloride. Therefore it was also concluded that aluminium massive and sparingly soluble forms of aluminium are highly insoluble and non-hazardous. Studies reported in the literature have extensively used test solutions (soluble salts) with aluminium concentrations above that of its solubility limit. Due to physical effects of precipitated material most of these studies are meaningless for the investigation of intrinsic toxicity. Aluminium ions released to surface waters quickly form insoluble aluminium hydroxides in mixing zones. These colloids can sorb to fish gills resulting in asphyxiation and mortality in rare circumstances. Formation of the complex hydroxide causes the aluminium to drop out of solution very rapidly in neutral and alkaline waters. The accumulation of aluminium on fish gills or other organism respiratory membranes may result in physical effects. These conditions however are not typical of most ambient conditions and are more representative of specific mixing zones. The dissolved natural background concentrations of aluminium, in most cases, are at equilibrium therefore an addition of aluminium would lead to the precipitation of aluminium compounds from solution and not result in effects to aquatic life. It is concluded that a PNEC is not required for REACH. However, the aluminium industry is continuing its efforts to develop a PNEC for freshwater ecosystems for purposes of the Water Framework Directive.

References:

Andren C.M., Kroglund F., Teien H.C. 2006. Controlled exposure of brown trout to humic water limed to different pH and inorganic aluminium concentrations. Verh. Internat. Verein. Limnol. 29:1548-1552.

Di Toro D.M., Allen H.E., Bergman H.L., Meyer J.S., Paquin P.R., Santore R.C.. 2001. Biotic ligand model of the acute toxicity of metals. 1. Technical basis. Environmental Toxicology and Chemistry 20:2383-2396.

ECO DOC 99/48. 1999.Draft Summary Record Commission Working Group on the Classification  and Labelling of Dangerous Substances, Environment, Ispra 15-17 September 1999.

Erstad K.J., Teien H.C., Kroglund F., Havardstun J., Sorlie L., Salbu B. 2002. Testing av halvbrent dolomittmjol til innsjokalking med saerlig vekt pa aluminiums- og jernkjemi. ISBN 82-7963-006-6. ISSN 1501-2735. Radgivande Agronomar Rapport

EURAS. 2007. Development of a High Quality Aquatic Ecotoxicity Database for Al Metal, Al Oxide, and Al Hydroxyde: Effects Assessment. Report prepared for the European Aluminum Association.

Exley C., Wicks A.J., Hubert R. B., Birchall D. 1996. Kinetic constraints in Acute aluminium toxicity in the rainbow trout (Oncorhynchus mykiss). Journal of Theoretical Biology 179:25-31

Gensemer R. W. and R.C. Playle 1999. The bioavailability and toxicity of aluminum in aquatic environments. Critical Reviews of Environmental Science and Technology 29(4): 315-450.

 Hamilton S. J., Haines T. A. 1995. Influence of fluoride on aluminum toxicity to Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences 52:2432-2444

Klimisch, H.J. M. Andreae, and U. Tillman. 1997.A systematic approach for the evaluating the quality of experimental toxicological and ecotoxicological data. Regulatory Toxicology and Pharmacology25: 1-5.

Kroglund, F., H.C. Teien, J. Håvardstun, A. Kvellestad, B. Salbu, B.O. Rosseland, B. Finstad. 1997. Betydningen av lave aluminiumskonsentrasjoner for laksesmolt. Norwegian Institute for Water Research, ISBN No.: ISBN 82-577-xxxx-x. Draft Report. NIVA xxxx-xx. 

 

Kroglund, F; H.C. Teien,E. Lucassen, B.O. Rosseland, B. Salbu, and Å. Åtland.1998a. Detoxification of aluminum in clearwater rivers by use of chemical mitigation methods. Experiments with Atlantic salmon smolts in River Suldalslågen. Norwegian Institute for Water Research, ISBN No.: ISBN 82-577-3564-7. NIVA 3970-98. 

Kroglund, F., H.C.Teien, J.Håvardstun, B.O.Rosseland, B.Salbu and A.Kvellestad. 1998b. The duration of unstable toxic forms of aluminium after liming and the importance of pH in reducing the mixing zone toxicity for parr of Atlantic salmon (Salmo salar). Norwegian Institute for Water Research, ISBN No.: ISBN 82-577-3393-8. NIVA 3815-98.

 

Kroglund, F., H.C.Teien, E. Lucassen, J.Håvardstun, B.O.Rosseland, B.Salbu,M.N.Pettersen. 1998c.Endring i giftighet til aluminium i en humøs elv ved ulike kjemiske tiltak.Norwegian Institute for Water Research, ISBN No.: ISBN 82-577-xxxx-x. Draft Report. NIVA xxxx-xx.

Kroglund F, H.C. Teien, E. Lucassen, J. Havardstun, B.O. Rosseland, B. Salbu, M.N. Petersen. 1998d. Reetablering av laks i forbindelse med kalking-reetablering av laks i Tovdals og Mandalselva; avgiftingsrater til aluminium i humusrike vannkvaliteter og effecter pa fisk. NIVA report.

Meyer, J. S., R. C. Santore, J. P. Bobbitt, L. D. Debrey, C. J. Boese, P. R. Paquin, H. E. Allen, H. L. Bergman, and D. M. Ditoro. 1999. Binding of nickel and copper to fish gills predicts toxicity when water hardness varies, but free ion activity does not. Environmental Science and Technology 33:913-916.

Paquin, P., J. W. Gorsuch, S. Apte, G. E. Batley, K. C. Bowles, P. G. C. Campbell, C. Delos, D. M. DiToro, R. Dwyer, F. Galvez, R. W. Gensemer, G. G. Goss, C. Hogstrand, C. R. Janssen, J. C. McGeer, R. B. Naddy, R. C. Playle, R. C. Santore, U. Schneider, W. A. Stubblefield, C. M. Wood, and K. B. Wu. 2002. The biotic ligand model: A historical overview. Comparative Biochemistry and Physiology C 133:3-35.

Playle, R. C. (1998). "Modelling metal interactions at fish gills."The Science of the Total Environment219: 147-163.

 

Roy R.L., Campbell P.G.C. 1997. Decreased toxicity of Al to juvenile Atlantic salmon (Salmo salar) in acidic soft water containing natural organic matter: a test of free-ion model. Environmental Toxicology and Chemistry 16: 1962-1969

Santore R. C., DiToro D.M., Paquin P.R., Allen H.E., Meyer J.S. 2001. Biotic ligand model of the acute toxicity of metals. 2. Application to acute copper toxicity in freshwater fish and Daphnia. Environmental Toxicology and Chemistry 20: 2397-2402.

Santore R.C., Driscoll C.T. 1995. The CHESS model for calculating chemical equilibria in soils and solutions.InChemical Equilibrium and Reaction Models. R Loeppert, AP Schwab,S Goldberg, editors. American Society of Agronomy, Madison, WI.

Teien H.C., Salbu B., Kroglund F., Rosseland B.O. 2004. Transformation of positively charged aluminium-species in unstable mixing zones following liming. Science of the Total Environment 330:217-232.

 

Teien Hans-Christian, Kroglund F., Salbua B., Rosseland B. O. 2006. Gill reactivity of aluminium-species following liming. Science of the Total Environment 358:206-220.

Teien H.C., Kroglund F., Atland A., Rosseland B.O., Salbu B. 2006b. Sodium silicate as alternative to liming-reduced aluminium toxicity for atlantic salmon (Salmo Salar L.) in unstable mixing zones. Science of the Total Environment 358:151-163.

 

Tipping, E., 1994. WHAM—a chemical equilibrium model and computer code for waters, sediments, and soils incor- porating a discrete siteyelectrostatic model of ion-binding by humic substances. Comput. Geosci. 20, 973–1023.

 

Witters H.E., Van Puymbroeck S., Stouthart A.J.H.X., and Wenderlaar Bonga S.E. 1996. Physicochemical changes of aluminum in mixing zones: mortality and physiological disturbances in brown trout (Salmo truttaL.). Environmental Toxicology and Chemistry 15: 986-996.

Molybdenum

Acute freshwater data

For fish, the lowest reliable data point for ammonium molybdate was put forward for hazard assessment purposes:

- 96h-LC₅₀of 237 mg Mo/L for the fish O. mykiss (HRC, 1994); Mo-salt was (NH₄)₂Mo₂O₇.

For invertebrates (test organism: Daphnia magna) the lowest reliable data point for ammonium molybdate was put forward for hazard assessment purposes:

- 48h-LC₅₀of 79 mg Mo/L for the cladoceran D. magna (HRC, 1994); Mo-salt was (NH₄)₂Mo₂O_7.

For algae, data that were generated with sodium molybdate were considered. For the most sensitive strain of P. subcapitata that was used in reliable study reports, 4 acute data points were availabe. The geometric mean of those 4 data points was 333.1 mg/L. This value is considered as a reliable acute algal toxicity reference value for hazard assessment purposes (e.g. classification).

Chronic freshwater data

A Species Sensitivity Distribution (SSD) has been developed for the assessment of molybdenum in the freshwater compartment, using the reliable species-specific chronic toxicity effect levels that have been identified. An overview of these species-specific data is given below. All toxicity tests were performed using sodium molybdate as test substance.

Overview of most sensitive species-specific K1-NOEC/EC₁₀-values for molybdenum in the freshwater environment

Species	Trophic level	NOEC/EC10-value (mg Mo/L)	Reference studies
Oncorhynchus mykiss	Fish	43.2	Parametrix, 2008
Pimephales promelas	Fish	60.2	Parametrix, 2007; GEI, 2009
Ceriodaphnia dubia	Crustacea	63.0	De Schamphelaere et al, 2008; GEI, 2009
Pseudokirchneriella subcapitata -CIMM strain	Algae	74.3	Rodriguez, 2008; De Schamphelaere and Janssen, 2008
Daphnia magna	Crustacea	89.5	De Schamphelaere et al, 2008 Rodriguez, 2007 ; GEI, 2009
Xenopus laevis	Amphibia	115.9	De Schamphelaere et al, 2008
Chironomus riparius	Insecta	121.4	De Schamphelaere et al, 2008
Brachionus calyciflorus	Rotifera	193.6	De Schamphelaere et al, 2008
Lymnaea stagnalis	Gastropoda	221.3	De Schamphelaere et al, 2008
Lemna minor	Aquatic plant	241.5	De Schamphelaere et al, 2008

 

 

No-effect levels for dissolved molybdenum were situated between 43.2 mg Mo/L and 241.5 mg Mo/L, i.e. a difference of a factor of 5.6 between the most and least sensitive species. Fish appear to be the most sensitive trophic level, representing the two lowest no-effect concentrations, followed by the algal species P. subcapitata and the two cladocerans D. magna and C. dubia.  The lowest sensitivity was found with duckweed (L. minor).

 

As mentioned before, these data have been used for the construction of a Species Sensitivity Distribution (SSD) from which the following parameter was derived:

-the median 5^thpercentile, i.e. the HC_5,50%with 5%-95%-confidence interval. The confidence interval is calculated using a Monte Carlo analysis on the log-normal distribution that was fitted through the 10 data points. The outcome of this analysis allows the derivation of the HC_5,50%with 5%-95% confidence interval. The HC_5,50%(± 95% CL) that was associated with this distribution was 38.2 mg Mo/L (95%CL: 18.7 – 57.3 mg Mo/L).  

 

Composition of the test media that were used for the development of the Mo-effects database

Species	Test duration	Endpoint	pH	Hardness^(1) mg/L as CaCO3	mg Ca/L	mg Mg/L
Pimephales promelas	34 d	Biomass	7.5±0.05	98.4	22.3	10.4
Oncorhynchus mykiss	78/84 d	Biomass	7.4±0.1	81.0	18.3	8.6
Pseudokirchneriella subcapitata -CIMM strain	72 h	Growth rate	8.0-8.1	24.1	4.9	2.9
Ceriodaphnia dubia	7 d	Reproduction	7.6-7.9	180	Not specified
Daphnia magna	21 d	Reproduction	7.4-8.2	168 - 250	27.9-80.1	12.2-24.2
Xenopus laevis	4 d	Malformation	7.8	110.7	19.4	15.1
Chironomus riparius	14 d	Growth	6.9-7.1	84.7	14	12.1
Brachionus calyciflorus	48 h	Reproduction	7.5	84.7	14	12.1
Lymnaea stagnalis	28 d	Length	7.8-8.2	140	40.1	9.7
Lemna minor	7 d	Growth rate	6.5-6.7	54.9	9.8	7.4

⁽¹⁾: derived from nominal/measured Ca/mg content

  

Marine freshwater data

A Species Sensitivity Distribution (SSD) has been developed for the assessment of molybdenum in the marine compartment, using the reliable species-specific chronic toxicity effect levels that have been generated in various research studies. An overview of these species-specific data is given in the table below. All toxicity tests were performed using sodium molybdate as test substance.

Overview of most sensitive species-specific K1-NOEC/EC₁₀-values for molybdenum in the marine environment

Species	End parameter	Endpoint	Value (mg Mo/L)	Reference
Mytilus edulis	Embryonal development	48h-EC10	4.4	Morgan et al, 1986
Acartia tonsa	Development	20d-EC10	7.96	Aquasense, 2009
Cyprinodon variegatus	Larval dry weight	28d-EC10	84.1	Parametrix, 2010
Americamysis bahia	Reproduction	28d-NOEC	116	Lehman, 2010
Phaeodactylus tricornutum	Growth rate (cells)	72h-ErC10	170	Aquasense, 2009
Dendraster excentricus	Larval development	48h-EC10	223.6	Parametrix, 2008a
Strongylocentrotus purpuratus	Larval development	48h-EC10	421.3	Parametrix, 2008b
Ceramium tenuicorne	Growth rate (length)	7d-NOEC	641	Le Page et al, 2010
Dunaliella tertiolecta	Growth rate (cells)	72h-ErC10	881	Le Page and Hayfield, 2010
Crassostrea gigas	Larval development	48h-EC10	1174	Aquasense, 2009

No-effect levels for dissolved molybdenum were situated between 4.4 mg Mo/L and 1174 mg Mo/L, i.e., a difference of a factor of 267 between the most and least sensitive species. The mussel M. edulis and the copepod A. tonsa were the most sensitive trophic level. The least sensitive species were the oyster C. gigas and two algal species (microalga D. tertiolecta and macroalga C. tenuicorne).

As mentioned before, these data have been used for the construction of a Species Sensitivity Distribution (SSD) from which the median 5^thpercentile was derived, i.e. the HC_5,50%with 5%-95%-confidence interval. Using the RIVM software package ETX, a Log-Normal Distribution was plotted through this data set. The HC_5,50%(± 95%CL) that was associated with this distribution was 5.74 mg Mo/L (95%CL: 0.58 – 21 mg Mo/L), respectively.

Conclusion

The effect values derived from analogue aluminium compounds are considerably lower than those derived from analogue molybdenum substances. However, these values were not considered for the assessment as it can be assumed that under environmental conditions in aqueous media, aluminium will predominantly be present as insoluble species (Al(OH)₃) and hence, will be present in a bioavailable form only in minor amounts, if at all. Therefore, it was concluded to put forward the most sensitive and reliable results derived from analogue molybdenum compounds for assessment purposes. Still, it should be noted that his represents an unrealistic worst-case scenario as under environmental conditions in aqueous media, the components of the sparingly soluble substance will be present in a bioavailable form only in minor amounts, and hence, the concentration of soluble MoO₄^2-ions released is low.