Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and ...bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.
Understanding metal and proton toxicity under field conditions requires consideration of the complex nature of chemicals in mixtures. Here, we demonstrate a novel method that relates streamwater ...concentrations of cationic metallic species and protons to a field ecological index of biodiversity. The model WHAM-
F
TOX postulates that cation binding sites of aquatic macroinvertebrates can be represented by the functional groups of natural organic matter (humic acid), as described by the Windermere Humic Aqueous Model (WHAM6), and supporting field evidence is presented. We define a toxicity function (
F
TOX) by summing the products: (amount of invertebrate-bound cation)
×
(cation-specific toxicity coefficient,
α
i
). Species richness data for Ephemeroptera, Plecoptera and Trichoptera (EPT), are then described with a lower threshold of
F
TOX, below which all organisms are present and toxic effects are absent, and an upper threshold above which organisms are absent. Between the thresholds the number of species declines linearly with
F
TOX. We parameterised the model with chemistry and EPT data for low-order streamwaters affected by acid deposition and/or abandoned mines, representing a total of 412 sites across three continents. The fitting made use of quantile regression, to take into account reduced species richness caused by (unknown) factors other than cation toxicity. Parameters were derived for the four most common or abundant cations, with values of
α
i
following the sequence (increasing toxicity) H
+
<
Al
<
Zn
<
Cu. For waters affected mainly by H
+ and Al,
F
TOX shows a steady decline with increasing pH, crossing the lower threshold near to pH 7. Competition effects among cations mean that toxicity due to Cu and Zn is rare at lower pH values, and occurs mostly between pH 6 and 8.
The present study investigated to what extent measured dissolved metal concentrations, WHAM-predicted free metal ion activity and modulating water chemistry factors can predict Ni, Cu, Zn, Cd and Pb ...accumulation in various aquatic insects under natural field conditions. Total dissolved concentrations and accumulated metal levels in four taxa (Leuctra sp., Simuliidae, Rhithrogena sp. and Perlodidae) were determined and free metal ion activities were calculated in 36 headwater streams located in the north-west part of England. Observed invertebrate body burdens were strongly related to free metal ion activities and competition among cations for uptake in the biota. Taking into account competitive effects generally provided better fits than considering uptake as a function of total dissolved metal levels or the free ion alone. Due to the critical importance and large range in pH (4.09 to 8.33), the H+ ion activity was the most dominant factor influencing metal accumulation. Adding the influence of Na+ on Cu2+ accumulation improved the model goodness of fit for both Rhithrogena sp. and Perlodidae. Effects of hardness ions on metal accumulation were limited, indicating the minor influence of Ca2+ and Mg2+ on metal accumulation in soft-water streams (0.01 to 0.94mM Ca; 0.02 to 0.39mM Mg). DOC levels (ranging from 0.6 to 8.9mgL−1) significantly affected Cu body burdens, however not the accumulation of the other metals.
Our results suggest that 1) uptake and accumulation of free metal ions are most dominantly influenced by competition of free H+ ions in low-hardness headwaters and 2) invertebrate body burdens in natural waters can be predicted based on the free metal ion activity using speciation modelling and effects of H+ competition.
•Strong relations were observed between body burdens and free metal ion activities.•The effect of H+ ions on insect body burdens was most clearly revealed.•Effects of major hardness ions on metal accumulation were rather limited.•Insect body burdens in natural waters can be predicted using speciation modelling.
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•The variability of nanomaterials makes case-by-case risk assessment impractical.•Read-across and machine learning approaches are required to ensure consumer safety.•Access to ...harmonized and integrated datasets for modelling is a current bottleneck.•Risk prediction requires integration of models covering release, exposure and hazards.•NanoSolveIT integrates multi-scale models into an in silico risk assessment framework.
Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational ‘safe-by-design’ approaches to facilitate NM commercialization.
Dialysis and chemical speciation modelling have been used to calculate activities of Fe
3+
for a range of UK surface waters of varying chemistry (pH 4.3–8.0; dissolved organic carbon 1.7–40.3 mg l
−1
...) at 283 K. The resulting activities were regressed against pH to give the empirical model:
. Predicted Fe
3+
activities are consistent with a solid–solution equilibrium with hydrous ferric oxide, consistent with some previous studies on Fe(III) solubility in the laboratory. However, as has also sometimes been observed in the laboratory, the slope of the solubility equation is lower than the theoretical value of 3. The empirical model was used to predict concentrations of Fe in dialysates and ultrafiltrates of globally distributed surface and soil/groundwaters. The predictions were improved greatly by the incorporation of a temperature correction for
, consistent with the temperature dependence of previously reported hydrous ferric oxide solubility. The empirical model, incorporating temperature effects, may be used to make generic predictions of the ratio of free and complexed Fe(III) to dissolved organic matter in freshwaters. Comparison of such ratios with observed Fe:dissolved organic matter ratios allows an assessment to be made of the amounts of Fe present as Fe(II) or colloidal Fe(III), where no separate measurements have been made.
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