Guidance

Data Compilation

Figure 2

The data on the toxicity of nickel to soil organisms were compiled from three main sources: open literature, internationally recognized databases (e.g., Science Direct, Web of Science), and industry-sponsored research programs. A large dataset on the ecotoxicity of nickel to soil organisms was compiled. All gathered data were further screened using the criteria as outlined in Data Quality Screening. 

Data Quality Screening

 Each individual ecotoxicity data point was screened for quality before incorporation in the nickel ecotoxicity database based on the following criteriai

  • the data were retained for the following groups of organisms:  higher plants, invertebrates, and micro-organisms; 
  • the data on soil higher plants & invertebrate organisms covered the following relevant endpoints: survival, growth, reproduction, litter breakdown, and abundance;
  • the data on soil micro-organisms covered the following relevant endpoints: respiration, nitrification, mineralization, growth, and enzyme activity;
  • toxicity tests for plants, invertebrates, and microbial processes were conducted in natural and artificial soils only, and tests performed under hydroponic conditions were rejected;
  • toxicity tests for microbial enzyme activity were rejected if the pH of the test was substantially different from the pH of the undisturbed soil;
  • the results reported measured pH and cation exchange capacity (CEC);
  • Nickel-only exposure data were considered relevant (studies were rejected if indications of impurities or other substances might have an effect on the toxic properties of nickel);
  • the range of the physico-chemistry of the test media (pH and CEC) were within the range of the developed/validated soil regression models (see Fact Sheet 5);
  • the tests were performed according to approved international standard test guidelines; however, data from non-standardized tests were also assessed;
  • only long-term or chronic toxicity data, involving endpoints that are realized over periods of several days to years depending on the organism, were used;
  • the tests were performed according to standard operational procedures, with a detailed description of the methods employed during toxicity testing;
  • the toxicity tests were performed with soluble nickel salts (e.g., NiCl2 and NiSO4);
  • preference was clearly given on the use of measured nickel concentrations in the test concentrations;
  • the toxicity data were related to the total concentration of  nickel in soils (defined as strong acid extraction without further confinement) and the test results were expressed as mg Ni/kg dry weight;
  • a clear concentration-response was observed;
  • toxicity threshold values calculated as L(E)C10 (the concentration that causes 10% effect during a specified time interval) values were preferred; however, NOEC values (No Observed Effect Concentration) were also seen as equivalent; and,
  • ecotoxicity threshold values data were derived using the proper statistical method.

Only the identified ecotoxicity data fulfilling the above mentioned criteria were used for the soil PNEC derivation.

Database Development

Applying the above mentioned quality screening criteria to the identified ecotoxicity data resulted in the selection of an extensive high quality database on the ecotoxicity of nickel to soil organisms. Indeed, the Nickel database contains a total of 42 different “species/process mean” values. This includes 52 individual EC10/NOEC values for the microbial processes, 16 individual EC10/NOEC values for enzymatic processes, 68 individual NOEC values for the plants, and 37 individual values for the invertebrates.

An overview of all accepted individual high quality chronic ecotoxicity data is presented in the Environmental Risk Assessment of Nickel and Nickel Compounds (see EU Risk Assessments).

Incorporation of Bioavailability (Data Normalization)

When considering the bioavailability of nickel in soils, different factors are important in determining the ecotoxicity of nickel to soil organisms:

  • Nickel-form: Nickel can enter the soil environment as soluble, associated with a high bioavailability, or as sparingly soluble, associated with a low bioavailability species.
  • Ageing: The larger toxicity of nickel in spiked soils compared to corresponding field contaminated soils is highly dependent on the time between the addition of soluble nickel to soils and the measurement of toxicity. The bioavailability and toxicity of nickel in spiked soils tend to decrease with time in a manner that is dependent on soil pH.
  • Normalization: The toxicity of nickel is highly dependent on soil type. Specifically, nickel toxicity to plants, invertebrates, and microbial processes decreases as the CEC of the soil increases.

For further guidance, see Fact Sheet 5 on bioavailability models for the soil compartment.

Data Aggregation

Aged and/or normalized high quality ecotoxicity data are grouped/aggregated in order to avoid over representation of ecotoxicological data from one particular species/process. The following major rules were used to aggregate data:

  • If several chronic NOEC/L(E)C10 values based on the same toxicological endpoint were available for a given species, the values were averaged by calculating the geometric mean, resulting in the “species mean” NOEC/L(E)C10.
  • If several (geometric mean) chronic NOEC/L(E)C10 values based on different toxicological endpoints were available for a given species, the lowest (geometric value) value was selected.

After the data aggregation step, only one ecotoxicity value (i.e., the geometric mean for the most sensitive endpoint) was assigned to a particular species.

Calculation of PNEC Using Statistical Extrapolation Methods

Estimation of the HC5 from the species sensitivity distribution

When a large data set for different taxonomic groups is available, the PNEC can be calculated using a statistical extrapolation method. In this approach, the ecotoxicity data were ranked from low (most sensitive species/process) to high (least sensitive species/process).  A species sensitivity distribution (SSD) was then constructed by applying an appropriate curve fitting distribution, usually a log-normal distribution, to the (aged and normalized) high quality aggregated chronic toxicity data (Aldenberg & Jaworska, 2000). From the SSD, a 5th percentile value (at the median confidence interval) is calculated (i.e., median HC5) using the software program ETx as described by Van Vlaardingen et al. (2004).

Selection of appropriate assessment factor and derivation of the PNEC

To account for uncertainty, an assessment factor (AF) may be applied to the median HC5. In general, such AFs vary between 1 and 5 and are determined on a case-by-case basis. The soil PNEC would therefore be calculated as follows:

soil PNEC = median HC5/AF

Based on the available chronic NOEC/L(E)C10 data, the following points were considered when determining the AF:

  • The overall quality of the database and the endpoints covered (e.g., are all the compiled data representative of “true” chronic exposure?)
  • The diversity of the taxonomic groups (Table 1) covered by the database [e.g., do the databases contain, at a minimum, organisms belonging to the six taxonomic groups as defined by the MERAG (Metals Environmental Risk Assessment Guidance) document (2006)?]
  • The number of species (e.g., does the SSD cover at least 10 different L(E)C10/NOECs and preferably more than 15?)
  • Use of bioavailability models and approach for bioavailability correction [e.g., do the bioavailability models (see Fact Sheet 5) allow the toxicity data for all species to be corrected for to ageing/normalizing?]
  • Statistical extrapolation (e.g., how well does the SSD fit the toxicity data?)
  • Comparisons between field and mesocosm studies and the PNEC (e.g., is the PNEC value protective for the effects observed in mesocosm/field studies?)

In the Nickel EU RA, no mesocosm/field data were available that allowed the determination of threshold concentrations of nickel in soils under field conditions. In addition, increased uncertainty was attributed to the limited number of species and life-strategies for which the bioavailability models have been developed and validated. All other identified criteria were fulfilled. Therefore, based on the weight of evidence, the Danish Rapporteur proposed to use an AF of 2.

 

Table 1:  Taxonomic Group Requirements According to the
Criteria Developed in the MERAG Document (ICMM, 2007)

Taxonomic Groups

1. Microbe mediated processes (e.g., respiration, denitrifica-tion, N- mineralization, etc.)
2. An insect (e.g., Collembola)
3. An oligochaete (e.g., Eisenia, Enchytreus)
4. A family in any order of oligochaete or any phylum not already presented
5. Higher plants (monocotyle)
6. Higher plants (dicotyle)