Updated species sensitivity distribution evaluations for acute and chronic lead toxicity to saltwater aquatic life.

The US Environmental Protection Agency's (USEPA's) ambient water quality criteria (AWQC) for lead (Pb) in salt water were developed in 1984. The acute and chronic criteria are 210 and 8.1 µg/L dissolved Pb, respectively. Because data were limited in 1984, the chronic criterion was derived using an acute-to-chronic ratio, but there are now sufficient toxicity data such that an acute-to-chronic ratio is no longer needed. Based on the data now available, the proposed updated acute and chronic salt water Pb AWQC (following USEPA methods) are 100 and 10 µg/L, respectively. In the European Union, a chronic salt water predicted no-effect concentration based on the median 5th percentile hazardous concentration (HC5-50) was developed in 2008 for the Registration, Evaluation, Authorisation, and Restriction of Chemicals program, which forms the basis for deriving chronic environmental quality standards for Pb in European marine waters. The salt water HC5-50 previously derived for Pb was 6.1 µg/L, whereas the proposed, updated chronic salt water HC5-50 derived following European Union methods is 11.0 µg/L. Thus, despite differences in derivation methodologies, the proposed AWQC and HC5-50 values are very consistent. Studies evaluating the effect of water quality factors on bioavailability and toxicity of Pb in salt water are limited; the effect of water quality on Pb toxicity in salt water should be considered in future studies. Environ Toxicol Chem 2017;36:2974-2980. © 2017 SETAC.

The derivation of effects threshold concentrations of lead for European freshwater ecosystems.

The main objective of the present study was to derive ecologically relevant effect threshold concentrations of (dissolved) Pb for selected European Union (EU) freshwater rivers, using the 2008 EU Voluntary Risk Assessment Report as a starting point and more advanced methodologies than those used in the Voluntary Risk Assessment Report. This included 1) implementing more robust quality criteria for selecting chronic toxicity data; 2) the conversion of total to dissolved Pb concentrations using a combination of an empirical equation relating inorganic Pb solubility and geochemical speciation modeling to account for effects of dissolved organic matter; 3) the use of bioavailability models for chronic toxicity for species belonging to 3 different trophic levels; and 4) the use of robust methods for large data set handling (such as species sensitivity distribution [SSD] analysis). The authors used published bioavailability models for an algal species (Pseudokirchneriella subcapitata) and a daphnid (Ceriodaphnia dubia) and developed a new model for the fathead minnow (Pimephales promelas). The research has shown that these models are also useful for, and reasonably accurate in, predicting chronic toxicity to other species, including a snail, a rotifer, midge larvae, and an aquatic plant (read-across). A comprehensive chronic toxicity data set for Pb was compiled, comprising 159 individual high-quality toxicity data for 25 different species. By applying the total dissolved conversion and the bioavailability models, normalized toxicity values were obtained, which were then entered into a SSD analysis. Based on the parametric best-fitting SSDs, the authors calculated that ecological threshold concentrations of Pb protecting 95% of freshwater species for 7 selected European freshwater scenarios were between 6.3 µg dissolved Pb/L and 31.1 µg dissolved Pb/L.

An intelligent data collection tool for chemical safety/risk assessment.

REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals) is the new European chemical legislation which aims to assess risk or safety of tens of thousands of chemicals to improve the protection of human health and the environment. The chemical safety assessment process is of an iterative nature. First, an initial, worst-case assessment is conducted after which refinements are made until no risk has been estimated or the risk is adequately controlled. Wasting time and resources on additional testing and implementing risk management measures with low effect on risk conclusions should be avoided as much as possible. This paper demonstrates the usefulness of an intelligent data collection strategy based on a sensitivity (and uncertainty) analysis on the risk assessment model EUSES to identify and order the most important "within-EU-TGD-reducible" input parameters influencing the local and regional risk characterisation ratios. The ordering can be adjusted for the costs involved in additional testing (e.g. ecotoxicity, physico-chemical properties, emission estimates, etc.). The risk refinement tool therefore reduces the resources needed to obtain a realistic risk estimate (both less conservative and less uncertain) as efficient as possible.

Improving uncertainty analysis in European Union risk assessment of chemicals.

Handling uncertainty in curren European Union (EU) risk assessment of new and existing substances is problematic for several reasons. The known or quantifiable sources of uncertainty are mainly considered. Uncertainty is insufficiently, explicitly communicated to risk managers and decision makers but hidden and concealed in risk quotient numbers that appear to be certain and, therefore, create a false sense of certainty and protectiveness. The new EU chemical policy legislation, REACH, is an opportunity to learn from interdisciplinary thinking in order to evolve to smart risk assessment: an assessment in which awareness and openness to uncertainty is used to produce better characterizations and evaluations of risks. In a smart risk assessment context, quantifying uncertainty is not an aim but just a productive means to refine the assessment or to find alternative solutions for the problem at stake. Guidance and examples are given on how to differentiate, assess, and use uncertainty.

Ambient copper concentrations in agricultural and natural European soils: an overview.

Copper concentrations in soil are affected by a large number of processes related to the natural spatial variability (geochemistry), the amount released, the spatial and temporal distributions of these releases, and the large number of transportation, complexation, and dissolution processes. The present study reports the generated country-specific and land use-specific environmental concentration distributions of ambient copper exposure levels in European soils that were used for the derivation of "reasonable worst-case" predicted environmental copper concentrations (RWC-ambient copper PEC) for three types of soil uses: Agricultural soils, forest soils, and undefined grassland soils. Only recent and high-quality monitoring data (Q1) that comply with a number of criteria (i.e., sampling strategy, land use, digestion method, and absence of point sources) were selected for this purpose. Data treatment procedures used in the present study were based on the methods and concepts laid down in the European Union Technical Guidance Document on Risk Assessment and in the "combined monitoring-based and modeling-based priority setting" procedure. The derived median RWC-ambient copper PEC for European agricultural soils is 31.1 mg/kg dry weight, with the lowest and highest RWC-ambient copper PEC found in Belgium (16.1 mg/kg dry wt) and northern Italy (57.5 mg/kg dry wt), respectively. The high value for Italian soils probably is related to the (recent) volcanic origin of these soils. Similarly, RWC-ambient copper PECs were derived for forest soils and undefined grassland soils (24.4 and 35.3 mg/kg, respectively). Observed differences between the diifferent soil uses could be related to various parameters and processes that determine the copper levels in soil (e.g., soil type associated with specitic soil uses, addition of fertilizers and pesticides, and presence of cattle).

Development of a chronic zinc biotic ligand model for Daphnia magna.

The individual effects of the cations Ca(2+), Mg(2+), Na(+), and H(+) on the chronic toxicity of Zn to the waterflea Daphnia magna were investigated in different series of univariate experiments, resulting in the development of a chronic Zn biotic ligand model (BLM) for this species. Using the mathematical approach based on a linear relationship between cation activity and metal activity at the EC(x) level, the following stability constants for binding of competing cations to the biotic ligand (BL) were derived: logK(CaBL) = 3.22, logK(MgBL) = 2.69, logK(NaBL) = 1.90, and logK(HBL) = 5.77. With the derived constants and a logK(ZnBL) of 5.31, two different BLMs that predict chronic zinc toxicity (EC(50), no observed effect concentration (NOEC)) for D. magna as a function of water characteristics were developed. Fractions of binding sites occupied by Zn at the considered effect levels EC(50) and NOEC were 0.127 and 0.084, respectively. The NOEC-based model predicts the Zn toxicity within a factor of 2, while the chronic EC(50) could be predicted within a factor of 1.5. In the future, these chronic Zn BLMs for D. magna can improve the ecological relevancy of zinc risk assessments by decreasing the bioavailability-related uncertainty of zinc toxicity.

Probabilistic environmental risk assessment of zinc in Dutch surface waters.

In the framework of the European Union (EU) New and Existing Chemicals Policy, a regional risk assessment for Zn according to the current technical guidance documents and a probabilistic approach, by mathematically integrating both best-fitting exposure concentrations and species-sensitivity distributions into a probabilistic risk quotient distribution using Monte Carlo analysis, was explored for The Netherlands. Zinc is an essential element, and the current probability distributions may not adequately deal with this property. The threshold Pareto distribution provided the best fit to the chronic Zn toxicity data, resulting in a predicted-no-effect concentration (PNECadd) for dissolved Zn of 34.2 microg/L, whereas use of the conventional normal distribution resulted in a PNECadd for dissolved Zn of 14.6 microg/L. The extracted exposure data resulted in a regional predicted environmental concentration (PEC) for dissolved Zn in the Dutch surface waters of 20.1 microg/L and in PECadd values for dissolved Zn of between 15.5 and 17.3 microg/L, depending on the background correction used. The conventional deterministic risk characterization identified a regional risk for Zn in the Dutch surface waters. The more comprehensive probabilistic approach used in the present study, however, identified only very limited potential risks for the Dutch region. A probabilistic median risk, that the environmental concentration is greater than the no-observed-effect concentration of a species in Dutch surface waters (0.5-0.6%), depending on the inclusion of background correction, was obtained from the best-fitting distributions. Because probabilistic approaches provide a quantifiable and improved assessment of risk and quantification of the uncertainty associated with that assessment, these techniques may be considered as a way to improve the EU risk assessment procedures for data-rich substances.