Protocol for the Derivation of Environmental and Human ... - CCME

Part B, Section 7
7.5.2.1 Using Microbial (Nutrient and Energy Cycling) Data for Derivation of Soil Contact
Guidelines for Agricultural and Residential/Parkland Land Uses. Once the TEC is calculated, it
is compared with selected microbial process (nutrient cycling) data following the procedure outlined in
Appendix A. If the microbial value determined in Appendix A is lower than the TEC calculated using
any of the soil contact methods, microbial nutrient and energy cycling processes may experience
adverse effects at the level of the TEC. In this case, the geometric mean of the two values is taken and
is used as the soil quality guideline for soil contact (SQG SC ). The geometric mean is used assuming that
the data are log-normally distributed. However, if the TEC is lower than the microbial value, then the
TEC is considered to be protective of microbial nutrient and energy cycling processes and is adopted
directly as the SQG SC .
7.5.2.2 Weight of Evidence Method. This method is a modification of an approach used for
calculating sediment quality guidelines for the National Status and Trends Program (NSTP) (Long and
Morgan, 1990), and an approach proposed by Smith and MacDonald (1993) for deriving Canadian
Sediment Quality Guidelines. These methods use a percentile of the effects data set, or combined
effects and no effects data set, to estimate a concentration in the sediment expected to cause no adverse
biological effects.
Minimum Data Requirements
All selected "effects" and "no observed effects" data are collected and a frequency distribution using the
empirical distribution function with averaging is created. Effects data should include lowest observable
effect concentration (LOEC), median effective concentration (EC 50 ), and median lethal concentration
(LC 50 ) data. Other types of selected "effects" data (e.g., E(L)C 75% LOEC and NOEC data), additional concerns are raised about the uncertainty of
this data set (see Section 6.1). While a normal distribution would best suit the guidelines derivation
using this method, asymmetric distributions predominate in biological effects data. Expert judgement
should determine if the degree of bias in the data makes this method inappropriate for guidelines
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