Summary of public comments received on the draft Federal environmental quality guideline for copper

Comments on the draft Federal Environmental Quality Guideline for Copper were submitted by the Copper Development Association, Canadian Copper and Brass Development Association, American Chemet Corporation, REACH Copper Compound Consortium, American Chemistry Council Center for Biocide Chemistries Copper Task Force, International Copper Association,

Ontario Ministry of Environment, Conservation and Parks, Nova Scotia Environment, and British Columbia Ministry of Environment and Climate Change Strategy.

Summarized public comments and responses are provided below, organized by topic:

Topic 1: Editorial

Summarized commentSummarized response
Many editorial comments were received on factsheet and BLM manual to improve the clarity and flow of information.    All editorial suggestions were incorporated into factsheet and manual. More details, such as what are FEQGs, why and when they are developed and how they differ from CEQGs are available online (  

Topic 2: Dataset

Summarized commentSummarize response
Provide FWQGs of copper across a range of pH, hardness and DOC concentrations.A FWQG calculator is provided as a conservative screening tool where users can enter a range of temperature, pH, DOC and hardness values. 
Access to test water chemistry data for toxicity endpoints used in SSD and surface water monitoring data. Water chemistry parameters for all 83 toxicity endpoints used in SSD are provided in Appendix 1. Alkalinity value for one of the Lemna minor tests has been corrected. The surface-water monitoring data were sourced from ECCC and Canadian provinces and territories. ECCC ( can direct users toward these sources. The monitoring data were only summarized for Canadian provinces and ecozones because the focus of our work is for Canada. 
Update the chronic toxicity dataset and correct the identified test water chemistry. The updated toxicity database now includes 355 acceptable chronic endpoints for 33 species, an increase of 13 endpoints and one species. Toxicity endpoints were re-evaluated. Vardy et al. (2011) endpoint for white sturgeon is replaced by Wang et al. (2014), Besser et al. (2009, 2006) endpoint for pond snail is replaced by Brix et al. (2011), and Muyssen and Janssen (2007) endpoint for D. magna is replaced by Bossuyt and Janssen (2004). The evaluation and selection of toxicity endpoints for copper FWQG followed CCME protocol (2007). Alkalinity value for one of the Lemna minor test in Antunes et al. (2012) has been corrected.

Topic 3: Methodology

Summarized commentSummarized response
Clarify the prescribed ranges for BLM input water chemistry and measures taken if the site water chemistry falls out side the defined range.The input water chemistry ranges are based on the actual values used in toxicity tests for model evaluation. The BLM tool checks that each of the chemistry input values are within the range of conditions that correspond to the calibration and validation data used in the development and evaluation of the model. When the input value for a chemical parameter is higher than the upper limit, the WQG is determined with that parameter at the upper limit. Values below the lower limits are similarly replaced with the lower limit before deriving the WQG. Users are advised to be cautious when inputting extremely low or high input variables. 
Provide guidance for using full versus simplified chemistry in copper BLM tool. The BLM tool has an option to use simplified chemistry that uses hardness and geochemical ion ratios to estimate most of the major ions, with alkalinity estimated from pH. A section on “simplified versus full BLM” chemistry has been added with recommendation that users should use the full chemistry calculation whenever possible, but if data availability does not support the full calculation, the simplified calculation option can be used to overcome data limitations. 
Consider different pCO2 values for animals and plants when using simplified BLM.A detail explanation on pCO2 values has been added in BLM tool manual. A pCO2 of 3.2 best represents the relationship between pH and alkalinity in natural waters and we suggest using this value for most default calculations. However, for plants and algae a somewhat higher CO2 concentration, corresponding to a pCO2 of 3.0 is recommended when using simplified BLM. The reason for this difference is that plants and algae are more sensitive to the impact of pCO2 on the toxicity of copper and a value of 3.0 is more protective. For this reason, the software uses pCO2 values that will be protective for each taxa and does not allow these default values to be changed.
Expand the discussion on BLM approach, including model bounds and input of simplified versus full chemistry in BLM tool user manual.The revised BLM User Manual provides very detailed discussion on BLM approach, including expanded text on model bounds and input water chemistry. A section on simplified versus full BLM chemistry has been added with recommendation for inputting the site water chemistry. For the application of BLM guidelines, users are expected to follow the approaches they use for hardness and MLR based FEQG and CCME metal guidelines. The BLM approach is based on sound science and has been used by regulators in both North America and Europe.
Provide a description of BLM binding constants (log K) and strength of BLM model in predicting copper toxicity. Specific BLM model details are given in Bioavailability section along with references. On the question of missing log K values in Table 3, revised text explains that log K values are not given for certain reactions because bioavailability relationships for those taxonomic groups do not require specific interactions. Observed vs. BLM-predicted toxicity results for 83 endpoints (Fig. 4) clearly show that 92% BLM predictions are within the factor of 2. This is an improvement of 4% from the earlier analysis for 78 endpoints. 
Predicting toxicity for soft water organisms and default assumptions for DOC.Toxicity data selected for characterizing the SSD represent diverse water chemistry, including pH and DOC, and for each individual species, relative sensitivity was compared to all available data. DOC is one of the most studied toxicity-modifying factor and the BLM overall makes good predictions for the default assumption that 100% of measured DOC in the test water is Cu reactive and is represented by 90% fulvic and 10% humic acids. The observed vs. BLM-predicted toxicity results (Fig. 4) clearly demonstrate predictive success of copper BLM approach.
Clarify the lower HC5 cap of “0.2*”μg/L.Setting the lower HC5 cap of “0.2*”μg/L was necessary because calculated FWQGs were extremely low for waters of very high Cu bioavailability (e.g., low DOC). It is to be noted that for these waters, the BLM calculated HC5 value are still presented in SSD plots and users can consider them on case-by-case basis. The relevant text has been revised for clarity.
Improvements in SSD plot and Excel ouput file of BLM tool.The 5th percentile line is now clearly marked in SSD plot. The Excel BLM ouput file now includes upper and lower confidence intervals of HC5.
Protectiveness of BLM-based FWQG for copper.Protectiveness assessment now presents ratios of effect concentrations to FWQGs (Fig. 8). These results identified that 96% of acceptable toxicity data were protected. Among the 355 endpoints of 33 species, only 13 (4%) endpoints of 7 species had a ratios of <1. Species names and number of toxicity endpoints with >1 and <1 ratios of each of these 7 species are presented in the text. It is to be also noted that the mean ratios for all 33 species in dataset were more than 1. The selection of toxicity endpoints for SSD followed the CCME (2007) protocol. As suggested by the reviewer, the protectiveness of copper guideline was evaluated for olfactory effects using the freshwater fish database compiled by Meyer & Deforest (2018). The analysis identified that FWQG is fully protective to olfactory toxicity endpoints. Relevant text has been added in protectiveness section. Consistent with the CCME protocol no assessment factor was applied to SSD based HC5. Both CCME and FWQGs do not apply assessment factors to SSD based guidelines.
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