Duke Energy Corporation 

526 South Church Street 

Charlotte, NC 28202 

Mailing Address: 

EC13K / P.O. Box 1006 

Charlotte, NC 28201-1006 

May 15, 2012 

Via Electronic Mail 

Ronald P. Jordan 

U. S. EPA Headquarters 

Engineering & Analysis Division (4303T) 

Ariel Rios Building 

1200 Pennsylvania Avenue, N.W. 

Washington, DC 20460 

RE: Miami Fort Data: Monthly Sampling Events

Dear Mr. Jordan: 

Thank you for the opportunity to comment on the draft data from the samples taken at 

the Duke Energy Miami Fort Station in September, November, and December 2010, 

and January 2011. We have done our best, given the amount of data provided and the 

relatively short time frame for review, to thoroughly review the data. These comments 

should be considered preliminary, as we may, upon further consideration of the data, 

have additional comments. 

I. General Comments 

Data Usability 

Duke Energy agrees with EPA’s efforts to identify and flag potentially erroneous (outlier) 

data points in the Miami Fort data set. If a value is an outlier, however, then it should be 

discarded from the data set and not used for any purpose. Also, there is no discussion 

of how flagged data points will be used (or excluded) from consideration in calculating 

the new steam electric effluent limitations guidelines. For example, data points flagged 

B, Est, F and T indicate potentially significant inaccuracy (bias) in the associated data. 

Duke Energy also questions the validity and use of the 4-set averages EPA calculated 

using the four monthly data sets (see Tables C5-1 - C5-3). The use of averages in 

some cases may obscure important differences among data points. EPA should explain 

how it intends to use the averages. 

Also, the EPA uses the following approach when calculating averages: “If at least one 

result was above the quantitation limit, then 1⁄2 the quantitation limit was used in the 

average calculation for all results that were less than the quantitation limit and the result 

is reported with a less than sign (“<”)”. This approach is not justified because it 
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introduces arbitrarily estimated data into the calculations. A more consistent, justifiable 

and conservative approach would be to use the quantitation limit in the calculations as 

is done when all results are below the quantitation limit. 

II. Inadequate Treatment System Design and Operational Descriptions and Data 

We noted several instances of inadequate treatment system design and operational 

descriptions and data in our earlier comments on the draft Sampling Episode Report 

(SER) for Miami Fort. All of those comments also apply to the additional data set. 

However, we reiterate here an essential point: 

• EPA’s study plan should have included a comprehensive study of the coal feed 

stock during each sampling event. It is clear that coal characteristics have a very 

significant impact on FGD chemistry and wastewater treatment. While EPA 

gathered some information about coal constituents during the sampling events, it 

should have collected full information about levels of sulfur, metals, and chlorides 

in the coal, as well as the heating value of the coal being burned during the 

relevant period for the sampling event. 

III. Analytical Methods Descriptions 

Also, as we stated in our earlier comments, the analytical descriptions in the SER and 

the analytical narratives omit some basic information that should be included and would 

be helpful in making data evaluations and comparisons. We reiterate our request for 

basic analytical information, as follows: 

1. How were the trace metals samples digested? Was a heated strong acid leach 

digestion patterned after EPA method 200.2 used or some other alternative 

digestion? Were the metals samples preserved to pH < 2 at least 24 hours prior 

to digestion (total recoverable) or analysis (dissolved)? Would EPA provide a 

description of the digestion procedure used for metals samples analyzed by 

Method 200.7 and 200.8? 

2. How were the Hg samples digested? Was the bromine monochloride digestion 

done at room temperature, heated, by Method 1631E Appendix A, etc.? If 

heated BrCl digestions were used, what temperature and duration were used? 

Were the same digestion procedures used for samples collected at SP-1, SP-2 

and SP-3? 

3. Was a bubbler system or a flow-injection analytical system used for the Method 

1631E analyses? 
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4. Were individual grab samples for Hg flow-proportion composited? If so, was the 

compositing done physically prior to analysis or was the “compositing” done 

arithmetically after the individual analysis of each sample? 

5. What type of 0.45 micron filter was used to filter the dissolved Hg samples (e.g., 

capsule, flat membrane with pre-filter, flat membrane with no pre-filter, etc.)? 

Were the samples allowed to settle and the supernatant filtered or were the 

whole samples shaken and filtered directly without settling? What was the range 

of elapsed times after collection that the dissolved Hg samples were filtered? 

6. How are known interferences in FGD matrices controlled? For example, chloride 

is a known interferent in the COD method and the concentration must be 

carefully controlled to achieve accurate results. 

7. More information is needed in the analytical narratives for matrix spikes and 

matrix spike duplicates (MS/MSD) that fail. For example, if failed recoveries are 

close to the acceptance range (87% when the limit is 90 to 100%) then the data 

can be used with qualification. However, if the recoveries are significantly below 

the method acceptance criteria then the data should not be used. 

8. For the FGD influent (SP-1) samples, were whole, shaken samples used to 

determine classical analytes (except TDS and TSS) or were the FGD samples 

allowed to settle and the clearer supernatant used for any of the classical 

analysis 

Duke Energy urges EPA to make this information available so that the data can be 

reviewed in the context of full laboratory QA/QC information and a full understanding of 

the analytical methods used. 

IV. Quality Assurance/Quality Control Issues 

Problems with ICV, CCV, ICB, CCB, ISA, ISB, CRI or MRL Standard (indicated by a 

“^”)—This “catch all” mark appears to have been used by EPA to indicate a multitude 

of possible QC problems that would only be evident from an examination of the raw 

laboratory data. For ICP/MS, problems with the ICV (initial calibration verification) are 

supposed to be resolved before analysis proceeds. Also, the CCV analyses (continuing 

calibration verification, performed once every ten samples) are supposed to be 

corrected by recalibration and re-analysis. It is unclear why any of the samples would 

be qualified for either ICV or CCV outliers. 

Also, continuing calibration blanks (CCBs) are a very important QC check when the 

laboratory is reporting values down to the MDL as J qualified results, as is being done 

here. ERG stated that they applied “method specific criteria” in determining whether the 

CCBs (and other criteria qualified with a “^”, see above) were acceptable. However, for 

both the ICP and ICP-MS methods, the CCB acceptability is based on the reporting 

limit, not the MDL. For example, Method 200.7 requires only that the CCB be less than 
4 

the minimum (reporting) level. The ML is defined in Section 1.12 of the method: “The 

ML for each analyte can be calculated by multiplying the MDL by 3.18 and rounding to 

the nearest (2, 5, or 10 X 10n) where n is an integer.” If the method criteria are applied, 

then the data review would not qualify data until a continuing calibration blank exceeded 

the reporting limit. This means that values reported below the reporting limit can be 

highly inaccurate even without any data qualifier (other than “J”). 

More on Continuing Calibration Blanks (CCB)—This is a very important QC check 

when the laboratory is reporting values down to the MDL as J qualified results, as is 

being done here. ERG stated that they applied “method specific criteria” in determining 

whether the CCBs (and other criteria qualified with a “^”, see above) were acceptable. 

However, for both the ICP and ICP-MS methods, the CCB acceptability as based on the 

reporting limit, not the MDL. For example, Method 200.7 requires only that the CCB be 

less than the minimum (reporting) level. The ML is defined in Section 1.12 of the 

method: “The ML for each analyte can be calculated by multiplying the MDL by 3.18 and 

rounding to the nearest (2, 5, or 10 X 10n) where n is an integer.” If the method criteria 

are applied, then the data review would not qualify data until a CCB exceeded the 

reporting limit. This means that values reported below the reporting limit can be highly 

inaccurate even without any data qualifier (other than “J”). 

MS/MSD QC Excursions (“F”)—Any “F” qualified results should be considered 

estimated values and excluded from the EPA dataset. The “F” flag appears on the 

following Miami Fort FGD effluent data (Table C5-3): 

Set 1 Barium, Silver 

Set 2 Ammonia, Nitrate/Nitrite, COD, Cyanide, Silver 

Set 4 COD 

V. EPA Requested Information

As requested, please find below the mercury split sample results from the effluent of the 

FGD wastewater treatment system (SP2) from Miami Fort Generating Station for 

sample sets 1, 2, 3 and 4. Split samples were not collected from the influent to the 

wastewater treatment system (SP1) at Miami Fort Generating Station during the 

monthly sampling events. 

Miami Fort Split Sample Results - Total Recoverable Hg Data for SP-2

Sampling Date SP-2, 

Total Rec. Hg, μg/L 

09/28/2010 0.242 

11/02/2010 0.343 

12/07/2010 0.155 

01/14/2011 0.129 
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VI. Summary

In summary, Duke Energy reserves the right to comment on these data as EPA 

continues its work on the steam electric effluent guidelines rulemaking. In order to 

assess the data fully, EPA should provide comprehensive laboratory data for all 

samples. Duke Energy requests that EPA provide the actual laboratory reports from its 

contract laboratories for both the 4-day sampling episode and the monthly samples in 

order for Duke Energy to further evaluate the data and the QA/QC results.