Validation of transfer functions predicting Cd and Pb free metal ion activity in soil solution as a function of soil characteristics and reactive metal content.

According to recent insight, the toxicity of metals in soils is better related to the free metal ion (FMI) activity in the soil solution than to the total metal concentration in soil. However, the determination of FMI activities in soil solution is a difficult and time-consuming task. An alternative is to use empirical equations (so called transfer functions (TFs)) that relate FMI activity in solution to the reactive metal concentration in the solid phase and to soil properties (pH and organic matter content). Here we test the applicability of two sets of TF for Cd and Pb using independent data from a wide range of soil types and regions that are not represented in the datasets used to derive the TFs. From these soils, soil solution was extracted using four different methods. For all these extracts, FMI activities were calculated from total concentrations in solution using the speciation program WHAM VI. In some of the soils, Cd and Pb FMI activities were also measured using a Donnan membrane technique. Most of these FMI activities deviated from the TF predictions by less than one order of magnitude and were within the 95% confidence interval of the TFs, irrespective of the method used to extract soil solution. Predictability was higher for Pb than for Cd and differed also between the two TF sets

Ecological indicators for abandoned mines, Phase 1: Review of the literature

Mine waters have been identified as a significant issue in the majority of Environment Agency draft River Basin Management Plans. They are one of the largest drivers for chemical pollution in the draft Impact Assessment for the Water Framework Directive (WFD), with significant failures of environmental quality standards (EQS) for metals (particularly Cd, Pb, Zn, Cu, Fe) in many rivers linked to abandoned mines. Existing EQS may be overprotective of aquatic life which may have adapted over centuries of exposure. This study forms part of a larger project to investigate the ecological impact of metals in rivers, to develop water quality targets (alternative objectives for the WFD) for aquatic ecosystems impacted by long-term mining pollution. The report reviews literature on EQS failures, metal effects on aquatic biota and effects of water chemistry, and uses this information to consider further work. A preliminary assessment of water quality and biology data for 87 sites across Gwynedd and Ceredigion (Wales) shows that existing Environment Agency water quality and biology data could be used to establish statistical relations between chemical variables and metrics of ecological quality. Visual representation and preliminary statistical analyses show that invertebrate diversity declines with increasing zinc concentration. However, the situation is more complex because the effects of other metals are not readily apparent. Furthermore, pH and aluminium also affect streamwater invertebrates, making it difficult to tease out toxicity due to individual mine-derived metals. The most characteristic feature of the plant communities of metal-impacted systems is a reduction in diversity, compared to that found in comparable unimpacted streams. Some species thrive in the presence of heavy metals, presumably because they are able to develop metal tolerance, whilst others consistently disappear. Effects are, however, confounded by water chemistry, particularly pH. Tolerant species are spread across a number of divisions of photosynthetic organisms, though green algae, diatoms and blue-green algae are usually most abundant, often thriving in the absence of competition and/or grazing. Current UK monitoring techniques focus on community composition and, whilst these provide a sampling and analytical framework for studies of metal impacts, the metrics are not sensitive to these impacts. There is scope for developing new metrics, based on community-level analyses and for looking at morphological variations common in some taxa at elevated metal concentrations. On the whole, community-based metrics are recommended, as these are easier to relate to ecological status definitions. With respect to invertebrates and fish, metals affect individuals, population and communities but sensitivity varies among species, life stages, sexes, trophic groups and with body condition. Acclimation or adaptation may cause varying sensitivity even within species. Ecosystem-scale effects, for example on ecological function, are poorly understood. Effects vary between metals such as cadmium, copper, lead, chromium, zinc and nickel in order of decreasing toxicity. Aluminium is important in acidified headwaters. Biological effects depend on speciation, toxicity, availability, mixtures, complexation and exposure conditions, for example discharge (flow). Current water quality monitoring is unlikely to detect short-term episodic increases in metal concentrations or evaluate the bioavailability of elevated metal concentrations in sediments. These factors create uncertainty in detecting ecological impairment in metal-impacted ecosystems. Moreover, most widely used biological indicators for UK freshwaters were developed for other pressures and none distinguishes metal impacts from other causes of impairment. Key ecological needs for better regulation and management of metals in rivers include: i) models relating metal data to ecological data that better represent influences on metal toxicity; ii) biodiagnostic indices to reflect metal effects; iii) better methods to identify metal acclimation or adaptation among sensitive taxa; iv) better investigative procedures to isolate metal effects from other pressures. Laboratory data on the effects of water chemistry on cationic metal toxicity and bioaccumulation show that a number of chemical parameters, particularly pH, dissolved organic carbon (DOC) and major cations (Na, Mg, K, Ca) exert a major influence on the toxicity and/or bioaccumulation of cationic metals. The biotic ligand model (BLM) provides a conceptual framework for understanding these water chemistry effects as a combination of the influence of chemical speciation, and metal uptake by organisms in competition with H+ and other cations. In some cases where the BLM cannot describe effects, empirical bioavailable models have been successfully used. Laboratory data on the effects of metal mixtures across different water chemistries are sparse, with implications for transferring understanding to mining-impacted sites in the field where mixture effects are likely. The available field data, although relatively sparse, indicate that water chemistry influences metal effects on aquatic ecosystems. This occurs through complexation reactions, notably involving dissolved organic matter and metals such as Al, Cu and Pb. Secondly, because bioaccumulation and toxicity are partly governed by complexation reactions, competition effects among metals, and between metals and H+, give rise to dependences upon water chemistry. There is evidence that combinations of metals are active in the field; the main study conducted so far demonstrated the combined effects of Al and Zn, and suggested, less certainly, that Cu and H+ can also contribute. Chemical speciation is essential to interpret and predict observed effects in the field. Speciation results need to be combined with a model that relates free ion concentrations to toxic effect. Understanding the toxic effects of heavy metals derived from abandoned mines requires the simultaneous consideration of the acidity-related components Al and H+. There are a number of reasons why organisms in waters affected by abandoned mines may experience different levels of metal toxicity than in the laboratory. This could lead to discrepancies between actual field behaviour and that predicted by EQS derived from laboratory experiments, as would be applied within the WFD. The main factors to consider are adaptation/acclimation, water chemistry, and the effects of combinations of metals. Secondary effects are metals in food, metals supplied by sediments, and variability in stream flows. Two of the most prominent factors, namely adaptation/ acclimation and bioavailability, could justify changes in EQS or the adoption of an alternative measure of toxic effects in the field. Given that abandoned mines are widespread in England and Wales, and the high cost of their remediation to meet proposed WFD EQS criteria, further research into the question is clearly justified. Although ecological communities of mine-affected streamwaters might be over-protected by proposed WFD EQS, there are some conditions under which metals emanating from abandoned mines definitely exert toxic effects on biota. The main issue is therefore the reliable identification of chemical conditions that are unacceptable and comparison of those conditions with those predicted by WFD EQS. If significant differences can convincingly be demonstrated, the argument could be made for alternative standards for waters affected by abandoned mines. Therefore in our view, the immediate research priority is to improve the quantification of metal effects under field circumstances. Demonstration of dose-response relationships, based on metal mixtures and their chemical speciation, and the use of better biological tools to detect and diagnose community-level impairment, would provide the necessary scientific information

The effect of ocean acidification on organic and inorganic speciation of trace metals

Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. 20 This results in changes to the concentrations of key chemical species such as hydroxide, 21 carbonate and bicarbonate ions. These changes will affect the distribution of different forms 22 of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to 23 the year 2100) we use a chemical speciation model to predict changes in the distribution of 24 organic and inorganic forms of trace metals. Under a scenario where emissions peak after 25 the year 2100, predicted free ion Al, Fe, Cu and Pb concentrations increase by factors of up 26 to approximately 21, 2.4, 1.5 and 2.0 respectively. Concentrations of organically complexed 27 metal typically have a lower sensitivity to ocean acidification induced changes. 28 Concentrations of organically-complexed Mn, Cu, Zn and Cd fall by up to 10%, while those 29 of organically-complexed Fe, Co and Ni rise by up to 14%. Although modest, these changes 30 may have significance for the biological availability of metals given the close adaptation of 31 marine microorganisms to their environment

Dynamic modelling of metals in topsoils of UK and Chinese catchments

Strongly particle–reactive contaminants such as metals may exhibit highly accumulative behaviour when input to soils. This may cause exceedence of threshold concentrations for risk, for example for ecological effects or for crop metal content, if accumulation continues for a sufficiently long period. Since remediation of soils contaminated beyond threshold metal concentrations is likely to be costly and technically difficult, there is a need for tools to predict present and future accumulation of metals given future projections of inputs. The Intermediate Dynamic Model for Metals (IDMM) is an intermediate complexity model for describing and predicting metal accumulation and loss in topsoils over timescales of decades to centuries. The model combines mechanistic and empirical submodels for metal speciation, partitioning and aging in soils to predict solid phase and porewater metal speciation, leaching losses and plant uptake in response to time–varying inputs. The model has been applied both to a set of upland UK catchments, and to the Guanting reservoir catchment of northern China. The latter scenario presents a strongly contrasting environment, in terms of precipitation and soil chemistry, to the UK catchments. The model is driven by time series inputs of metals, starting from a pristine ‘steady state’ where input and output metal fluxes are in balance. Following estimation of historic metal inputs, particularly from atmospheric deposition, the model is able to make robust predictions of present day topsoil metal pools (within a factor of three of observations). The model thus provides a useful tool for predicting future trajectories of metal concentrations in topsoil, allowing assessment of potential risks due to varying scenarios of metal inputs

The use of WHAM-FTOX, parameterized with laboratory data, to simulate zooplankton species richness in acid- and metal- contaminated lakes

The WHAM-FTOX model quantifies cation toxicity towards freshwater organisms, assuming an additive toxic response to the amounts of protons and metals accumulated by an organism. We combined a parameterization of the model, using data from multi-species laboratory toxicity tests, with a fitted field species sensitivity distribution, to simulate the species richness (nsp) of crustacean zooplankton in acid- and metal-contaminated lakes near Sudbury, Ontario over several decades, and also in reference (uncontaminated) lakes. A good description of variation in toxic response among the zooplankton species was achieved with a log-normal distribution of a new parameter, β, which characterizes an organism’s intrinsic sensitivity towards toxic cations; the greater is β, the more sensitive is the species. The use of β assumes that while species vary in their sensitivity, the relative toxicities of different metals are the same for each species (common relative sensitivity). Unbiased agreements between simulated and observed nsp were obtained with a high correlation (r2 = 0.81, p < 0.0001, n = 217). Variations in zooplankton species richness in the Sudbury lakes are calculated to be dominated by toxic responses to H, Al, Cu and Ni, with a small contribution from Zn, and negligible effects of Cd, Hg and Pb. According to the model, some of the Sudbury lakes were affected predominantly by acidification (H and Al), while others were most influenced by toxic heavy metals (Ni, Cu, Zn); for lakes in the latter category, the relative importance of heavy metals, compared to H and Al, has increased over time. The results suggest that, if common relative sensitivity operates, nsp can be modelled on the basis of a single set of parameters characterizing the average toxic effects of different cations, together with a species sensitivity distribution

Determination and prediction of zinc speciation in estuaries

Lowering of the estuarine Environmental Quality Standard for zinc in the UK to 121 nM reflects rising concern regarding zinc in ecosystems and is driving the need to better understand its fate and behaviour and to develop and parameterise speciation models to predict the metal species present. For the first time, an extensive dataset has been gathered for the speciation of zinc within an estuarine system with supporting physico-chemical characterisation, in particular dissolved organic carbon. WHAM/Model VII and Visual MINTEQ speciation models were used to simulate zinc speciation, using a combination of measured complexation variables and available defaults. Data for the five estuarine transects from freshwater to seawater endmembers showed very variable patterns of zinc speciation depending on river flows, seasons, and potential variations in metal and ligand inputs from in situ and ex situ sources. There were no clear relationships between free zinc ion concentration [Zn2+] and measured variables such as DOC concentration, humic and biological indices. Simulations of [Zn2+] carried out with both models at high salinities or by inputting site specific complexation capacities were successful, but overestimated [Zn2+] in low salinity waters, probably owing to an underestimation of the complexation strength of the ligands present. Uncertainties in predicted [Zn2+] are consistently smaller than standard deviations of the measured values, suggesting that the accuracy of the measurements is more critical than model uncertainty in evaluating the predictions

Modelling trace metal transfer in large rivers under dynamic hydrology: a coupled hydrodynamic and chemical equilibrium model

Trace metals (TMs) in rivers experience a complex chemistry that affects their partitioning between the dissolved and particulate fractions. Predictive modelling of this partitioning is challenging, particularly under variable hydrodynamic conditions in rivers. This paper presents a coupled hydrodynamic–geochemical model for trace metal dynamics in rivers, to highlight key parameters and set a basis for developing simplified models. A coupled model based on the hydrodynamic model MOHID and the chemical speciation model WHAM was applied to the middle part of the Garonne River (SW-France). The predictions of the coupled model are compared to those of a fixed Kd partitioning model. The model accurately simulates trace metal behaviour under varying hydrological conditions. The importance of the riverbed geomorphology and the diurnal variations in pH on TM concentrations in the water column are underlined. The sensitivity analysis ranked all physico-chemical parameters according to their influence on TM behaviour