Prediction of accumulation and leaching of fungicide copper in agricultural soils

Copper is applied extensively to protect a number of crops, including vines/grapes, citrus and other fruits, against fungal attack. In contrast to biodegradable organic chemicals, metals such as copper cannot be degraded in the environment and so can potentially remain as contaminants in the environment for extended periods of time. Metals can undergo processes such as ‘aging’ in certain environmental compartments, such as soils, that reduce their bioavailability and toxicity, but typically a significant proportion of the metal remains in a potentially bioavailable form for extended periods. There is thus a need to assess the potential ecological risks of the ongoing use of copper as a fungicide. This study has been commissioned by the European Copper Task Force (ECTF) to assess the potential risks of the current and future use of copper as a fungicide. Using a set of typical copper application rates, and a set of scenarios covering a representative range of soil types across Europe, we have simulated copper accumulation in soils, surface waters and sediments using an intermediate complexity dynamic model (the IDMM) designed specifically for the long term behaviour of metals. Predicted copper concentrations over time have been compared with Predicted No Effect Concentrations for soil, waters and sediments to assess the current potential risks, and the prospects for the future development of risk under a scenario of continued copper application have been assessed

Terrestrial ecosystem health under long-term metal inputs: modeling and risk assessment

Metal contamination of soils may pose long-term risks to ecosystem health if not properly managed. Future projection of contamination trends, coupled with ecological assessment, is needed to assess such risks. This can be achieved by coupling dynamic models of soil metal accumulation and loss with risk assessment on the basis of projected metal levels. In this study, we modeled the long-term dynamics of Cu, Zn, and Cd in agricultural topsoils of a northern Chinese catchment (Guanting reservoir) and related projected metal levels to 2060 to ecological risk. Past metal dynamics were simulated using historical metal inputs from atmospheric deposition, irrigation, fertilizers, and animal manures. Modeling future dynamics was done using scenarios of projected metal input rates. Ecological risk assessment was done using the Potentially Affected Fraction (PAF) approach to estimate the combined toxic pressure due to the three metals. Modeled labile soil metals agreed well with measurements from monitoring in 2009 following adjustment of the porewater dissolved organic concentration. Metals were predicted to be largely retained in the topsoil. Projections were sensitive to changes in imposed soil pH, organic matter, and porewater dissolved organic carbon. Modeling suggests that decreases in input rates to between 5% and 7.5% of 2009 levels are required to prevent further accumulation. Computed PAFs suggest zinc makes the greatest contribution to ecological risk. Under the most conservative estimate of PAF, the threshold of potential ecological risk was reached before 2060 in two of the three future input scenarios

WHAM-FTOXβ – An aquatic toxicity model based on intrinsic metal toxic potency and intrinsic species sensitivity

We developed a model that quantifies aquatic cationic toxicity by a combination of the intrinsic toxicities of metals and protons and the intrinsic sensitivities of the test species. It is based on the WHAM-FTOX model, which combines the calculated binding of cations by the organism with toxicity coefficients (αH, αM) to estimate the variable FTOX, a measure of toxic effect; the key parameter αM,max (applying at infinite time) depends upon both the metal and the test species. In our new model, WHAM-FTOXβ, values of αM,max are given by the product αM* × β, where αM* has a single value for each metal, and β a single value for each species. To parameterise WHAM-FTOXβ, we assembled a set of 2182 estimates of αM,max obtained by applying the basic model to laboratory toxicity data for 76 different test species, covering 15 different metals, and including results for metal mixtures. Then we fitted the log10 αM,max values with αM* and β values (a total of 91 parameters). The resulting model accounted for 72% of the variance in log10 αM,max. The values of αM* increased markedly as the chemical character of the metal changed from hard (average αM* = 4.4) to intermediate (average αM* = 25) to soft (average αM* = 560). The values of log10 β were normally distributed, with a 5–95 percentile range of -0.73 to +0.56, corresponding to β values of 0.18 to 3.62. The WHAM-FTOXβ model entails the assumption that test species exhibit common relative sensitivity, i.e. the ratio αM,max / αM* is constant across all metals. This was tested with data from studies in which the toxic responses of a single organism towards two or more metals had been measured (179 examples for the most-tested metals Ni, Cu, Zn, Ag, Cd, Pb), and statistically-significant (p < 0.003) results were obtained

POSSMs: a parsimonious speciation model for metals in soils

Mechanistic geochemical models are useful for detailed study of the speciation of metals in well-characterised soils, but can be challenging to apply when driving soil compositional data are sparse, for example, at large scales. Empirical models, using minimal driving data, have been developed either for prediction of solid–solution partitioning or for the computation of the free metal ion from the total or geochemically active metal. This work presents an empirical speciation model, POSSMs (ParsimOniouS Speciation of Metals in soils), which predicts the free, solution-bound and sorbed metal in a soil in a single calculation, using a minimal set of soil parameters. The model has been parameterised for Ni, Cu, Zn, Cd and Pb using datasets of geochemically active soil metal and solution phase composition. The parameterised model can also be used to compute the free metal ion from the solution metal. The model was tested by applying it to literature datasets on the speciation of metals in soil solutions and extracts, and on the metal solid–solution partitioning. The performance of the model was comparable to other empirical models of similar complexity. Some test datasets produced biased predictions, particularly in the underestimation of measured free ion at circumneutral and alkaline pH, where the model predicted low free ion concentrations. The model is not a replacement for mechanistic geochemical models, but is a useful tool for soil metal speciation where comprehensive driving data are not available

Relating metal exposure and chemical speciation to trace metal accumulation in aquatic insects under natural field conditions

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 0.94 mM Ca; 0.02 to 0.39 mM Mg). DOC levels (ranging from 0.6 to 8.9 mg L− 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

Using WHAM-FTOX to understand proton and metal mixture toxicity in the laboratory and field

It is a well-attested fact that the uptake and toxicity of cationic metals to organisms are dependent on the chemistry of the exposure medium. Considerable research effort has been devoted to development of modelling tools to understand, explain and predict these medium effects. Predominant among the developed models is the Biotic Ligand Model (BLM), which considers exposure to be directly related to metal bound to specific uptake sites (biotic ligands) on the target organism, with chemical speciation in the medium and competition for binding to the biotic ligand(s) accounted for. Similarly to the BLM, WHAM-FTOX is based around the concept of computing amounts of metal bound to the organism. However, rather than computing amounts of metals bound to assumed specific biotic ligands, WHAM-FTOX assumes that exposure to metals is proportional to the amount of metal bound by all weak-acid coordination sites on or in the organism, in equilibrium with the surrounding medium. An overall toxic response for mixtures of cations (metals and protons) is quantified as a toxicity function FTOX, given by FTOX = ∑ αi ϴi where the exposure to each cation is given by ϴi (the fractional occupancy of binding sites) and αi is a toxicity coefficient specific to each cation. Amounts of bound cations are computed using the WHAM chemical speciation model, taking the amounts bound to humic acid (HA) as proxies for amounts bound to organisms. This approach has the advantage that constants for cation binding are already available, rather than needing to be derived as with the BLM, and that mixture effects are readily computed. Furthermore, the toxic effects of proton binding can be included in the mixture exposure modelling. Initial applications of WHAM-FTOX focused on describing field community effects in freshwaters impacted by acidification and metal contamination in a number of locations including the UK and North America. Subsequent work has focused on modelling accumulation and mixture effects in laboratory toxicity tests. Most recently, the model has been used in a meta-analysis of single metal–single species laboratory toxicity data with the aim of providing a unifying picture of toxic effects through time and across metals and organisms. Collectively, this body of work demonstrates the utility of WHAM-FTOX as a unifying tool for understanding and predicting the toxicity of cation mixtures from the laboratory to the field, from single species to whole communities. Prospects for the future include the use of the model to predict mixture field effects based on calibration to laboratory data

Effects of aging and soil properties on zinc oxide nanoparticle availability and its ecotoxicological effects to the earthworm Eisenia andrei

To assess the influence of soil properties and ageing on the availability and toxicity of Zn applied as nanoparticles (ZnO NPs) or as Zn2+ ions (ZnCl2), three natural soils were individually spiked with either ZnO NPs or ZnCl2 and incubated for up to 6 months. Available Zn concentrations in soil were measured by pore water extraction (ZnPW), while exposures of earthworms (Eisenia andrei) were performed to study Zn bioavailability. ZnPW was lower when Zn was applied as nanoparticles than as ionic form, and decreased with increasing soil pH. ZnPW for both Zn forms were affected by ageing, but varied among the tested soils, highlighting the influence of soil properties. Internal Zn concentration in the earthworms (ZnE) was highest for the soil with high organic carbon content (5.4%) and basic pH (7.6) spiked with ZnO NPs, but the same soil spiked with ZnCl2 showed the lowest increase in ZnE compared to the control. Survival, weight change, and reproduction of the earthworms were affected by both Zn forms, but differences in toxicity could not be explained by soil properties or ageing. This shows that ZnO NPs and ZnCl2 behave differently in soils depending on soil properties and ageing processes, but differences in earthworm toxicity remain unexplained

The role of sediment properties and solution pH in the adsorption of uranium(VI) to freshwater sediments

Uranium (U) can enter aquatic environments from natural and anthropogenic processes, accumulating in sediments to concentrations that could, if bioavailable, adversely affect benthic organisms. To better predict the sorption and mobility of U in aquatic ecosystems, we investigated the sediment-solution partition coefficients (Kd) of U for nine uncontaminated freshwater sediments with a wide range of physicochemical characteristics over an environmentally relevant pH range. Test solutions were reconstituted to mimic water quality conditions and U(VI) concentrations (0.023–2.3 mg U/L) found downstream of Canadian U mines. Adsorption of U(VI) to each sediment was greatest at pH 6 and 7, and significantly reduced at pH 8. There were significant differences in pH-dependent sorption among sediments with different physicochemical properties, with sorption increasing up until thresholds of 12% total organic carbon, 37% fine fraction (≤50 μm), and 29 g/kg of iron content. The Kd values for U(VI) were predicted using the Windermere Humic Aqueous Model (WHAM) using total U(VI) concentrations, and water and sediment physicochemical parameters. Predicted Kd-U values were generally within a factor of three of the observed values. These results improve the understanding and assessment of U sorption to field sediment, and quantify the relationship with sediment properties that may influence the bioavailability and ecological risk of U-contaminated sediments

Effect of soil organic matter content and pH on the toxicity of ZnO nanoparticles to Folsomia candida

Organic matter (OM) and pH may influence nanoparticle fate and effects in soil. This study investigated the influence of soil organic matter content and pH on the toxicity of ZnO–NP and ZnCl2 to Folsomia candida in four natural soils, having between 2.37% and 14.7% OM and pHCaCl2pHCaCl2 levels between 5.0 and 6.8. Porewater Zn concentrations were much lower in ZnO–NP than in ZnCl2 spiked soils, resulting in higher Freundlich sorption constants for ZnO–NP. For ZnCl2 the porewater Zn concentrations were significantly higher in less organic soils, while for ZnO–NP the highest soluble Zn level (23 mg Zn/l) was measured in the most organic soil, which had the lowest pH. Free Zn2+ ion concentrations were higher for ZnCl2 than for ZnO–NP and were greatly dependent on pH (pHpw) and dissolved organic carbon content of the pore water. The 28-d EC50 values for the effect of ZnCl2 on the reproduction of F. candida increased with increasing OM content from 356 to 1592 mg Zn/kg d.w. For ZnO–NP no correlation between EC50 values and OM content was found and EC50 values ranged from 1695 in the most organic soil to 4446 mg Zn/kg d.w. in the higher pH soil. When based on porewater and free Zn2+ concentrations, EC50 values were higher for ZnCl2 than for ZnO–NP, and consistently decreased with increasing pHpw. This study shows that ZnO–NP toxicity is dependent on soil properties, but is mainly driven by soil pH