Comment 116: Commenter 17620 understands the need to incorporate some calculation of the variability in performance that is expected with modern pollution control devices in the determination of a MACT floor. The commenter believes that the arithmetic average of the performance achieved by the best performing 12% of existing units for which the EPA has data should be adjusted to reflect the repeatability of performance of complying units, so that an operator of a unit with a designed adequate compliance margin has a reasonable expectation that the unit will pass a compliance test. As we have commented in the ICI Boiler MACT data acquisition and rulemaking process, this is best accomplished by repeat controlled testing of complying units. The EPA has chosen not to do so, but has based its proposed assignment of variability on a calculation method that includes the difference in performance between all units in the top 12%. The use of inter-unit variability as a surrogate for unit repeatability can lead to an inappropriate calculation of the MACT floor. Congress has specified how to address the inter-unit variability in the performance of the best performing 12% of the units in a subcategory  -  average the results.
Response to Comment 116: The EPA has incorporated all data available to calculate the UPL. The EPA believes that when a source has several measurements they could be considered a sample of intra-unit (within unit) repeatability because even though data were not collected consecutively in time, data available were collected under the unit "regular conditions." The EPA has followed Congress's guidelines and incorporated variability into the calculations of the MACT floor using data provided by the industry. Using these data, the EPA calculated an UPL that includes intra (within unit) and inter (between unit) variability.
Comment 117: Commenter 17621 states that they found discrepancies between the EPA's description of the procedure used to derive MACT floor limits and the implementation of that procedure. The EPA stated that the MACT floor for new or reconstructed EGUs is based on the lowest emitting unit for which test run data were available. However, that procedure was not followed consistently, and no explanation is provided for some of the discrepancies. The procedures used to calculate the UPL is not consistent across all parameters and EGU categories. No explanation is provided for these discrepancies.
Response to Comment 117: Where 2010 ICR Part II emissions test data were available, the EPA chose to utilize them in the MACT floors as minimum emission averages or as data showing different emission averages for the same pollutant over time. This was only possible for Hg, HCl, and HF for coal-fired boilers in the proposed rule as those were the only units with these pollutants tested, where, the extra emission test data where provided on a comprehensive basis. Because of the number of units in the industry in the solid oil (petroleum coke) and IGCC subcategories, the EPA chose to assess their UPLs (floors) using available run-by-run test data, although coal- and oil-fired unit's floors were assessed using emission averages. Commenter did not specify the discrepancies alleged; we have reviewed our analyses and believe that to the extent there were any discrepancies in the analyses for the proposed rule they have been corrected.
4A03 - MACT Floor Methodology: Treatment of Non-Detect Values
Commenters: 17620, 17621, 17627, 17690, 17711, 17716, 17725, 17730, 17739, 17775, 17795, 17812, 17820, 17851, 17877, 17878, 17886, 17912, 17914, 18014, 18021, 18443, 18449, 18498, 6637, 8443, 19536/19537/19538, 18023
Comment 1: Commenter 17620 notes that the EPA argues that emissions of a number of individual organic HAP, such as benzene, were frequently below the detection limit ("BDL") at the very best performing units and therefore it is infeasible to establish or enforce an emission limitation. However, the EPA has established procedures for addressing BDL values in calculating MACT floors and for other purposes. Moreover, the relevant factual issue is whether the emissions from the group at large are below detection limits, not just those of the very best performers.
Commenter 17725 states that in cases where multiple units have reported emissions results that are at or below the detection limit, one cannot definitively establish a single "best performer" since the results represent values that are inherently indistinguishable from one another. Although one source that reported a BDL value may have reported a slightly lower detection limit than another source due to individual test calibration, sample volume, or equipment differences, it would be arbitrary to suggest that the unit's performance is better than the other's for that reason.
We determined the RDL for each pollutant using data from tests of all the best performers for all of the final regulatory subcategories (i.e., pooled test data). We applied the same pollutant-specific RDL and emissions limit adjustment procedure to all subcategories for which we established emissions limits. We believe that emissions limits adjusted in this manner better ensure measurement variability is adequately addressed relative to compliance determinations than did the procedure applied for the proposal that may have been based on limited data sets. By accounting for measurement uncertainty in this manner, we also believe that the emissions testing procedures and technologies available are adequate to provide the measurement certainty sufficient for sources to demonstrate compliance at the levels of the revised emissions limits.
Response to Comment 1: The EPA agrees with many of the comments related to treatment of data reported as detection limit values in the development of MACT floors and emissions limits. The probability procedures applied in calculating the floor or an emissions limit inherently and reasonably account for emissions data variability including measurement imprecision when the database represents multiple tests from multiple emissions units for which all of the data are measured above the method detection level. That is less true when the database includes emissions occurring below method detection capabilities regardless of how those data are reported. The EPA's guidance to respondents for reporting pollutant emissions used to support the data collection specified the criteria for determining test-specific method detection levels.
Those criteria insure that there is only about a 1 percent probability of an error in deciding that the pollutant measured at the method detection level is present when in fact it was absent. Such a probability is also called a false positive or the alpha, Type I, error. This means specifically that for a normally distributed set of measurement data, 99 out of 100 single measurements will fall within +-2.54 σ of the true concentration. The anticipated range for the average of repeated measurements comes progressively closer to the true concentration. More precisely, the anticipated range varies inversely with the square root of the number of measurements. Thus, if σ is the standard deviation of anticipated single measurements, the anticipated range for 99 out of 100 future triplicate measurements will fall within +- 2.54 σ/√3 of the true concentration. This relationship translates to an expected measurement imprecision for an emissions value occurring at or near the method detection level of about 40 to 50 percent.
By assuming a similar distribution of measurements across a range of values and increasing the mean value to a representative higher value (e.g., 3 times minimum detection level), we can estimate measurement imprecision at other levels. For an assumed 3xMDL, the estimated measurement imprecision for a three test run average value would be on the order 10 to 20 percent. This is about the same measurement imprecision as found for Methods 23 and 29 indicated in the ASME Precision of Manual Stack Emissions Measurements for the sample volumes prescribed in the final rule (e.g., 4 to 6 dscm) for multiple tests.
Analytical laboratories often report a value above the method detection limit that represents the laboratory's perceived confidence in the quality of the value. This arbitrarily adjusted value is expressed differently by various laboratories and is called limit of quantitation, practical quantitation limit, or reporting limit. In many cases, the LOQ, PQL, or RL is simply a multiplication of the method detection limit. Multipliers range from 3 to 10. Consistent with findings expressed in reports of emissions measurement imprecision and the practices of analytical laboratories, we believe that using a measurement value of 3 times a method's detection limit established in a manner that assures 99 percent confidence of a measurement above zero will produce a representative method reporting limit suitable for establishing regulatory floor values.
On the other hand, we agree with commenters that an emissions limit set determined from a small subset of data or data from a single source may be significantly different than the actual method detection levels achieved by the best performing units in practice. This fact, combined with the low levels of emissions measured from many of the best performing units, led the EPA to review and revise the procedure intended to account for the contribution of measurement imprecision to data variability in establishing effective emissions limits. In response to the comments and internal concerns about the quality of measurements at very low emissions limits especially for new sources, we revised the procedure for identifying a representative method detection level (RDL). We did not revise the manner in which we calculate the UPL for the MACT floors.
The revised procedure for determining an RDL starts with identifying all of the available reported pollutant specific method detection levels for the best performing units regardless of any subcategory (e.g., existing or new, fuel type, etc.). From that combined pool of data, we calculate the arithmetic mean value. By limiting the data set to those tests used to establish the floor or emissions limit (i.e., best performers), we believe that the result is representative of the best performing testing companies and laboratories using the most sensitive analytical procedures. We believe that the outcome should minimize the effect of a test(s) with an inordinately high method detection level (e.g., the sample volume was too small, the laboratory technique was insufficiently sensitive, or the procedure for determining the minimum value for reporting was other than the detection level). We then call the resulting mean of the method detection levels as the representative detection level (RDL) as characteristic of accepted source emissions measurement performance. The second step in the process is to calculate three times the RDL to compare with the calculated floor or emissions limit. This step is similar to what we have used before including for the Portland cement MACT determination. We use the multiplication factor of three to approximate reduce the imprecision of the analytical method until the imprecision in the field sampling reflects the relative method precision as estimated by the ASME study that also indicates that such relative imprecision, from 10 to 20 percent, remains constant over the range of the method.es. For comparing to the floor, if three times the RDL were less than the calculated floor or emissions limit (e.g., calculated from the UPL), we would conclude that measurement variability was adequately addressed. The calculated floor or emissions limit would need no adjustment. If, on the other hand, the value equal to three times the RDL were greater than the UPL, we would conclude that the calculated floor or emissions limit does not account entirely for measurement variability. If indicated, we substituted the value equal to three times the RDL for the calculated floor or emissions limit which results in a concentration where the method would produce measurement accuracy on the order of 10 to 20 percent similar to other EPA test methods and the results found in the ASME study.
We determined the RDL for each pollutant using data from tests of all the best performers for all of the final regulatory subcategories (i.e., pooled test data). We applied the same pollutant-specific RDL and emissions limit adjustment procedure to all subcategories for which we established emissions limits. We believe that emissions limits adjusted in this manner better ensure measurement variability is adequately addressed relative to compliance determinations than did the procedure applied for the proposal that may have been based on data sets smaller than seven tests and as few as one test. We also believe that the emissions testing procedures and technologies available now and in the future will be adequate to provide the measurement certainty sufficient for sources to demonstrate compliance at the levels of the adjusted emissions limits.
Comment 2: Commenter 17620 states that the EPA asserts that in its experience, test results near the detection limit of the test method employed are accurate to within 40 percent, but when the result is three times the detection limit, the expected accuracy of its test methods improves to 15 percent. Thus for example, if the detection limit was 1 ppm, the EPA would expect the result to be accurate within a range of 0.6 to 1.4 ppm; although if the result was 3 ppm, the Agency would assess the range to be 2.55 - 3.45 ppm. However, in designing the test program, the EPA instructed sources to utilize a very high "detection limit," one set at the 99th percentile, which should increase the confidence level of the result.[55] The EPA then assigned a value equal to three times the highest detection limit to any test result in the group that was BDL of the method employed in analyzing the results. Thus, it would assign 3 ppm (not 1.4 ppm) as the test result if the detection limit was 1 ppm. Thereafter, the EPA assigns a second variability factor to the results that include this multiplier. The scientific community has adopted several approaches for the use of BDL values, including an assumption of zero, an assumption that the value is half of the detection limit and an assumption that the value is the detection limit itself.
Comment 3: Commenters 8443 and 17621 suggest that the EPA should recognize that laboratory MDLs are often not an appropriate indicator of the capability of stack test methods. For some HAP, below detection limit test results were reported at much higher concentrations than typical MDLs (e.g., 10,000 times higher for HCl). These differences are due to matrix effects in samples exposed to flue gas that are not present in the clean laboratory samples used for MDL studies. Thus, commenters suggest that the question is not what substitution procedure should be used to represent BDL values in the UPL calculation, but rather, what is the lowest concentration of the HAP that a majority of competent labs measured accurately in the ICR.
Commenter 8443 adds that detection limit information was inconsistently reported by lCR test contractors and that how the EPA uses these very low measurements will have significant impacts on the MACT floors the EPA calculates as well as later compliance demonstrations. The commenter states that the EPA's presentation material fails to explain how the EPA will address measurements at or below a methods detection limit and quantitation limit.
Comment 4: Commenters 18498 and 17716 state that, although many sources provided emissions data identified as BDL or "detection level limited" ("DLL"), it is unclear whether these are all the BDL instances, given the possibility of reporting errors or inconsistencies in the approach used by the various laboratories to identify such values. The MDL represents the threshold for assuming a pollutant is present in the sample, but the uncertainty associated with the MDL is very high makes it impossible to meaningfully quantify the concentration.
Commenters add that emission measurements that are below the detection limit of a sampling method do not represent the quantifiable data necessary to perform a technically sound emissions floor analysis. The point at which a measurement can be deemed meaningfully quantifiable  -  known as a "limit of quantification" ("LOQ") -- is at a much higher concentration than the MDL, albeit still with some degree of measurement uncertainty. It is commonly accepted that LOQ represents the value that will produce a relative standard deviation ("RSD") of 10% in the measurements. A key issue for the UPL analysis is how to treat values that are greater than the MDL but below the LOQ be treated. This is especially important here where relatively small data sets are involved because not only might the results fail to represent the entire range of operating conditions or fuel supplies, but also these measurements are subject to variability and uncertainty.
Commenters recommend that the EPA conduct the UPL analysis using only values that are above MDL with values deemed to be below the actual MDL of the method replaced by an approximation of the MDL. This approach would reduce the danger that truncating the emissions at the MDL values will significantly affect the UPL calculation by underestimating the variance as well as avoid the fundamentally flawed problem of calculating an emission floor using a dataset that contains non-quantifiable data. See 76 FR 25044/2 ("There is a concern that a floor emissions limit based on a truncated data base may not account adequately for data measurement variability and that a floor emissions limit calculated using values at or near the MDL may not account adequately for data measurement variability, because the measurement error associated with those values provides a large degree of uncertainty"). Commenters agree with this concern and concur with the decision not to adjust the MDL values for the individual run that were used in the floor calculation.
Comment 5: Commenter 17730 notes that the EPA relied on the ICR testing data to establish the emission standards for Hg, each of the HAP metals, acid gases, and the associated surrogates. In the ICR, the EPA required sources to submit data from emissions testing regardless of whether that data was below the method detection limit or not. Subsequently, the EPA used the data submitted by sources that was recorded below the method detection limit in establishing the emission standards for the individual HAP, setting the below detection limit data at the detection limit value. This practice is inappropriate and the EPA should not use the ICR test results that are below the detection limit of the method. Emission test results that are recorded below the detection limit are invalid data. Additionally, the EPA's artificial adjustment of the data value to the level of the detection limit is inappropriate and should not be allowed. The EPA should discard the test results that are below the detection limit, and use test results that are above the detection limit of the method prescribed by the EPA for use in the ICR data collection request.
Comment 6: Commenter 17739 notes that the EPA has erroneously included emissions data in the MACT floors that are below the MDL. In the Boiler MACT, the EPA concluded that "it is not appropriate, for development of MACT floor, to use any value less than the MDL." 76 FR 15624. The EPA reached this conclusion because "such values have not been demonstrated to have been met." Although the EPA has reached a correct conclusion with respect to use of values below the MDL for the Boiler MACT, due to inadequate or non-existent QA/QC analysis, 51 values in the Hg floor spreadsheet are below the applicable MDL. It is clear from the assessment of the EPA's QA/QC procedures that individual sampling results are incorrectly identified as ADL in the MACT database. The EPA's decision to use these BDL values as if they were the "true" values is contrary to widely accepted scientific practice and arbitrarily skews the emission averages to lower values. It may also mask sampling and analytical problems which should completely invalidate the subject data. The commenter did not have the time or the resources to evaluate this issue for the other HAP datasets, but the number of identified basic data errors the EPA has made thus far would suggest that additional errors in other data sets would be likely.
Response to Comments 2 - 6: In addition to the general response provided above under Comment 1, the EPA agrees with commenters on several points regarding the handling of very low or below MDL measured emissions values in establishing the floor. We agree with the assertion that developing a floor using data that include reported BDL values requires an additional accounting for measurement uncertainty. We agree that measurement uncertainty is related more to the measurement method than to individual subcategories of sources in the same general source category. We also agree that assessment of the largest pool of data available would provide a more realistic estimate of MDL than an analysis of a very few or even one data value from of subset of method detection levels.
We disagree with commenters who suggested using values less than the MDL or arbitrarily adjusted higher reporting values (e.g., LOQ) be applied to substitute for data otherwise reported as below detection level in the data set used to calculate the floor. We recognize that a test-specific MDL derived in accordance with the method(s) will be variable from test to test and to some extent from testing laboratory to laboratory. We believe that test method measurement imprecision, including the inherent test-to-test variability in MDL values, can be a significant contributor to the variability in a set of emissions data. We believe that emissions data sets that reflect the inherent variability of test specific method detection levels that are determined and defined using relatively consistent procedures, as discussed above, provide a reasonably reliable platform from which to assess process variability and intrinsic measurement uncertainty.
We also recognize that several tests reported detection levels much higher than the either the lowest reported detection levels or the lowest measured values. As some commenters suggested, we believe this is the result of laboratories reporting the arbitrarily higher LOQ values. We do not agree that the higher BDL values are a result of site specific matrix effects. All tested facilities were combusting typical coals or oils with no identified unique situations that we would expect to result in adverse matrix effects. We disagree that using data reported as BDL at that value is arbitrary. While the use of the BDL reported value in the UPL calculation may result in a slightly higher emissions standard, alternatives other than using the BDL value or using 0.5 of the BDL value (exclusion of value, setting the value at 0, or setting the value at an arbitrary multiple of the MDL) introduce an unacceptable bias. The use of the BDL value increases the likelihood that the final emissions standard would be based upon the UPL calculation rather than three times the average BDL value. We do not agree that an emissions standard calculated using the greater of the UPL or three times the average reported RDL cannot be measured with reasonable accuracy to demonstrate compliance. As stated above. Should the new source limit be based upon a source which reported all test runs as BDL, setting the standard at three times the RDL provides ample ability to demonstrate compliance with the standard using test procedures which are accurate and precise.
Comment 7: Commenter 17621 states that it is important that the EPA carefully review all emission data used in the MACT floor calculation to ensure that the data are free of errors and are reported according to ICR requirements. The resulting emission limit should be measurable with acceptable precision in actual field samples, using standard methods with a sampling duration that is practical for routine stack testing. To determine that emission value requires consideration of the precision of methods in the field, not simply taking a laboratory MDL and applying a multiplier. The most appropriate means to determine method precision is to conduct multi-train stack tests at full-scale power plants, at the approximate flue gas concentration considered for the MACT limit. Recognizing that such test data generally do not exist and will take a considerable effort to collect, the commenter recommends setting the limits for existing EGUs such that most BDL-flagged ICR results are below the MACT limit. Any BDL-flagged values above the limit should be reviewed to determine whether the elevated detection limits are the result of unusual source characteristics, poor laboratory performance, or sampling, analytical, or reporting error. As discussed earlier, in setting limits for new/reconstructed EGUs, the MACT limit should not be based on BDL-flagged values.
Reference: based on results of a statistical study provided in commenter's Appendix D section: "regarding EPA's unit limit calculation procedures and why these procedures may produce a new unit limit below the actual capability of the test method."
Response to Comment 7: See response to Comment 1, above.
Comment 8: Commenter 17716 notes that, in the final IB MACT Rule, the results for new units were tied to each specific new unit. Because the objective of the exercise is to ensure that emissions can be reasonably quantified during future tests, the levels should be set for any reference method test based on the pollutant of interest. The same level set for existing unit floor should be used to evaluate the new unit limit to assure compliance with each limit. This would avoid the possibility that new unit emissions limits would markedly differ from or otherwise be unrepresentative of the existing source limits due to the vagaries of testing as well as establish a consistent reasonable range of quantification to establish future compliance.
Commenter states that the issue of measurement uncertainty is fundamental to the analysis and is unrelated to any sub-categorization. To the extent the proposed approach present difficulties for some pollutants or surrogates, a possible alternative for Method 29 metals measurements would be to establish reasonable values based upon the reported detection limits in the ICR database and then set a limit for total metals using the sum of the ten individual metal limits.
Response to Comment 8: See responses to Comment 1 and Comments 2-6, above.
Comment 9: Commenter 17716 suggests that, for PM, a different procedure for handling non-detect values is warranted because very few sources reported non-detect values in the ICR database for filterable PM test methods or for the calculated total PM values, which consisted primarily of Method 5 or modified Method 29 measurements (or Method 202 for condensable PM). The field study that the EPA conducted to validate the recent revisions to Method 202 suggested a MDL of 2.5 mg for filterable PM and a MDL of 4.1 mg for condensable PM. (Field Evaluation of Condensable Particulate Matter Measurement, U.S. EPA Office of Air Quality Planning and Standards, Sector Policy and Program Division Monitoring Policy Group (prepared by Eastern Research Group, Inc. under EPA Contract No. EP-D-07-097), 2010.) In combination with a minimum sampling volume of 4 dscm, these values would suggest an MDL of about 1.7 mg/dscm or 0.0015 lb/MMBtu for total PM and approximately 0.6 mg/dscm or 0.0006 lb/MMBtu for filterable PM. Using these values would result in limits of 0.0045 lb/MMBtu (for 3xMDL) or 0.0075 lb/MMBtu (for 5xMDL) for total PM. For filterable PM, the limits would be roughly 0.002 lb/MMBtu (for 3xMDL) or 0.003 lb/MMBtu (for 5xMDL) for total PM (These PM limits should be considered conservative because the reported MDL values may not be representative of actual field measurements, especially for total PM. For both filterable and condensable PM, blank values can vary significantly due to contamination such as acetone residues. The practices of stack testers might vary even during presumably well-controlled studies. For condensable PM, lingering SO2 artifacts can (as discussed previously) have a significant impact on low-level measurements, even when a nitrogen purge is used after the tests.)
Response to Comment 9: The EPA agrees with the commenter on several issues raised in these comments. First, we note that the final rule does not include emissions testing for condensable PM and it is unnecessary for us to respond to comments on that issue. Second, few, if any, emissions testing contractors reported detection levels for particulate matter. For the Phase III ICR data, all but two sources reported the measured weight gains. Three sources reported values were lower than what we would consider the minimum mass that can be reasonable measured (i.e., BDL). Prior to using this data to calculate the UPL, we increased the reported weight gain to 1 mg. For the Phase II ICR data we did not have the detailed test data that we had for the Phase III ICR data. We did make similar adjustments although the adjustments were based upon assumed sampling volumes, moisture content and flue gas characteristics. As a result, we are confident that we have accommodated the lack of precision of the particulate test methods at the low emissions levels achieved by the best performing sources.
Comment 10: Commenter 17716 states that, for Hg the EPA's approach will tend to overstate the limit because some used Method 29 and because of misunderstanding regarding the limitations of Method 30B, which was the predominating Hg reference method used for the ICR. The commenter suggests the use of a limit for Hg of 0.04 μg/m3, which translates to roughly to 4 x 10-8 lb/MMBtu.
The MDL reported during the ICR for HCl seems to be somewhat higher than expected due to a number of sources combining the Method 26 trains with CTM-033 to jointly measure HCl, HF and HCN. Commenter recommends using a limit for HCl of 8 x 10-6 (3 x MDL) or 1.3 x 10-5 lb/MMBtu (5 x MDL).
Comment 11: Commenter 17716 states that determining the proper MDL and LOQ for Method 30B is paramount to assure data collected are of acceptable quality and known uncertainty. However, the commenter notes that these values will vary from lab to lab, analyzer to analyzer, and analyst to analyst. Therefore, simply stating a generic MDL/LOQ for the entire method, in their opinion, is folly at a minimum. Although the theoretically calculated MDL and LOQ has been shown to be as low as 2 ng, in practice the QA/QC at that level is not obtainable. That is, to validate a 2 ng mass on the calibration curve, a CCVS would have to be within +- 0.2 ng and that level of precision is below the MDL. Furthermore, the field recovery test (section 8.2.6 of Method 30B details the requirements for the field recovery test which is required to be successfully completed before any field samples are validated) portion of the method adds additional challenges and uncertainty that have not been discussed in this write up. Based on a tremendous amount of field experience in performing the analysis required of this method and the ongoing QA/QC requirements of the method, the author believes that in practice 10 ng is a reasonable range for the LOQ to collect data of acceptable quality and known uncertainty (i.e.,+-10%) and 5 ng is pushing the envelope on the lowest LOQ that should be used when evaluating low level effluent concentration data (i.e.,_ 0.1μg/m3). The response factor approach is used for merely estimating masses below the LOQ, but above the MDL and should not be used when establishing an emission limit as the data of are of unknown quality and uncertainty. It then follows for a typical ICR test (i.e.,2 hr test run collecting 120 liters of volume) that effluent concentrations ranging between 0.04 μg/m3 and 0.08 μg/m3 are the lowest that can be reasonably be determined with acceptable quality and uncertainty.
Response to Comments 10 - 11: Method 29 was an approved testing method for Hg measurement for the ICR and, so, testers were free to use it. The EPA agrees that it is important to assure that the data collected are of known and acceptable quality and that is precisely what the performance criteria of Method 30B are designed to accomplish although also providing significant operational flexibility. The lower limit of quantitation or LOQ is not a fixed value, but a value that can be improved by maximizing total sample volume and analytical sensitivity. With recent improvements to the Method 30B analytical equipment and reagents, this is now routinely accomplished. Commercially available Method 30B sorbent traps are being used with nominal sampling rates over 4 liters per minute (lpm) and we routinely see analytical calibration curves with Hg masses as low as 1-2 ng; this although meeting all the Method 30B performance criteria. As a result, Hg stack concentrations as low as 0.004 ug/m3 can be measured by using 2 hour sampling time with all the Method 30B performance criteria being met. Even in consideration of the commenter's recommendation of a 10 ng LOQ, Hg concentrations as low as 0.01 ug/m3 can be measured using a 4 hour emissions test.
We believe that this was demonstrated as part of the ICR testing program where an average stack Hg concentration of 0.01 ug/m3 was measured as part of triplicate 4 hour emissions test where all Method 30B performance criteria were met.
Comment 12: Commenter 17739 notes that the EPA required respondents to Part III of the 2009 ICR to use EPA Method 30B to determine Hg emissions. According to section 1.1 of the EPA's description of the method (see below), it is intended to measure Hg concentrations of 0.1 μg/dscm or greater. Assuming an F-factor of 9,780 (the standard F-factor for bituminous coal, from EPA Method 19), and a flue gas oxygen content of 5%, this 0.1 μg/dscm Hg concentration corresponds to an emission rate of 8 x 10-8 lb/MMBtu. However, 51 Hg emission rates below this level are listed in the spreadsheet that the EPA used in its revised Hg MACT floor determination of 5/18/2011 (See, "National Emissions Standards for Hazardous Air Pollutants (NESHAP) Maximum Achievable Control Technology (MACT) Floor Analysis for Coal-and Oil-fired Electric Utility Steam Generating Units  -  REVISED, " May 18, 2011]. The EPA should revise its Hg floor dataset to correct for these emission rates below the method detection limit, and then revise its Hg floor and variability analyses. As further evidence of detection limit problems, Method 30B, which the EPA required for Hg measurements, provides that sampling times must be determined based on the expected flue gas Hg content, and increased to accurately measure the low concentrations expected for well controlled units, as stated in the protocol for the method. 8.2.5 Determination of Sample Run Time. Sample run time will be a function of minimum sample mass (see Section 8.2.2), target sample volume and nominal equipment sample flow rate.
It is not clear from the QA documentation if this procedure was followed consistently because some of the reported sampling times appear to be impossibly short for the Hg emission level to have been reported accurately. Did the EPA ensure in all cases, and particularly for the data used in the MACT floor calculations, that adequate sampling times/volumes were determined and employed, and if so, how?
Response to Comment 12: The commenter correctly points out that, in section 1.1 of Method 30B, we quote a `typical' range of 0.1 ug/dscm to >50 ug/dscm. The EPA specified the range as `typical' as we recognized the method range would likely expand over time. In fact, as noted in the response above, recent improvements in analytical technology, sorbents, and traps have resulted in current capability to make measurements of known quality down to levels of approximately 0.004 ug/dscm with sampling times of 2 hours. In regard to the data used to set the MACT Hg floors, we have reviewed the data set used in determining the new source standard. In particular, this test program utilized a 4 hour sampling time, yielding mass catches of approximately 8 ng of Hg, and measured concentrations approximating 0.01 ug/dscm. Analyses were conducted using a lower calibration point of 5 ng Hg and all Method 30B performance criteria were met.
Considering the above information, we believe that it is reasonable to conclude that the data constituting the MACT floor for existing sources would be reliable based on 1 to 4 hour sampling runs.
Comment 13: Commenter 17775 states that the EPA's focus on the method detection limit reported by a given laboratory ignores many sources of measurement error that can affect a reported result. Accuracy considerations are not limited to the ability of a single laboratory to precisely measure the amount of a substance in a given sample it receives. Measurement errors also occur during the collection of a sample at the stack, the transfer of that collected sample to whatever means are used to transport the sample to an analytical laboratory, and the inter-laboratory inaccuracies of a different laboratories testing the same sample. The EPA's proposed rule does not address these areas of collection and analytical error. Furthermore, a laboratory MDL value is often not an accurate indicator of the true capability of a stack test method. MDL studies generally use clean samples for analysis. Samples from EGU stacks present far more challenging matrix effects because of flue gas chemistry. For these reasons, the EPA's detection limit analysis is fatally flawed.
Response to Comment 13: See responses to Comment 1 and Comments 2-6, above. The EPA believes that the adjustments and clarifications used to finalize the emission standards represent a scientifically-sound basis for this rule.
Comment 14: Emission value below detection limits (BDL) should not be used.
Multiple commenters (17621, 17851, 17886, 17912, 17914, 18014, 18021, 18443, 18449, 18498, 19536, 19537, 19538, 18023) state that an emission value below detection limits should not be used to calculate emissions for a "lowest-emitting unit," because these values understate measurement variability and do not have acceptable accuracy and precision.
Several commenters (17725, 17730, 17820) state that emissions data may have actually been below the detection limit but not identified as such in the ICR database because of reporting errors or inconsistencies in the approach used by the various laboratories to identify such values. Emission measurements that are below the detection limit of a sampling method do not represent quantifiable data, which is necessary to perform a technically sound emissions floor analysis. Commenter 17730 adds that the emissions data that was collected for the ICR for the proposed rule showed that approximately 50 percent of the data was below the detection limit of the method, yet in evaluating the data, it appears that the EPA has assigned the detection limit value to that data. The EPA should not arbitrarily assign an emission value to this data that is not accurate.
Commenter 17795 recommends that the EPA change the statistical approach for this rule and not use values BDL of the method when calculating the floor. At a minimum, all BDL values should be raised to 0.04 ppmv and the floor should be recalculated. This issue is highlighted by the proposed NSPS standard of 0.3 lb/GWh. Converting this standard to a ppm equivalent, a 7,700 Btu/kW heat rate would be required to meet 0.026 ppm of HCl, which is 35 percent lower than the method detection limit. It is unreasonable for the EPA to adopt standards below method detection limits.
Commenter 17878 recommends that measurements below MDLs should not be used for standard setting without adjustment. Many of the Hg emission rates in the EPA's MACT floor are at or below the MDL. The EPA required respondents to Part III of the 2009 ICR to use the EPA Method 30B to determine Hg emissions. According to section 1.1 of the EPA's description of the method (see below), it is intended to measure Hg concentrations of 0.1 μg/dscm or greater. Assuming an F-factor of 9780 (the standard F-factor for bituminous coal from the EPA Method 19), and a flue gas oxygen content of 5 percent, this 0.1 μg/dscm corresponds to an emission rate of 8 x 10-8 lb/MMBtu. However, Hg emission rates at or below this level are listed in the spreadsheet that the EPA used in the revised Hg MACT floor determination of 5/18/2011.
Commenter 17627 states that the use of data below MDLs to establish MACT limits for utility boilers is technically incorrect. When all three runs from a submitted emission test indicate data below the MDL, the EPA used the maximum of the three runs as the test average. For example, commenter's Bay Shore Unit 1 ICR data for 2,3,7,8-TCDD yields an average of the three runs of 1.097E-13 although the EPA's spreadsheet lists an average of 1.49E-13 for Bay Shore Unit 1. Additionally, all three of Bay Shore Unit 1 dioxin/furans runs were below the MDL, but the EPA used the maximum value, Run 3, to represent the 3-run average. This type of data accounting is inaccurate and results in erroneous and biased-low MACT emission limits.
Commenter 17775 states that the detection limits reported in the ICR responses are inconsistent and are not even based on a common understanding of the term "detection limit" or "method detection limit" ("MDL"). Most EGU owners seem to have reported the "detection limit" value they were provided by the laboratory analyzing the ICR samples. A cursory review of the ICR data shows that some "reported" values are actually below the detection limit values reported in other ICR tests.
Commenter 17851 states that the EPA should re-examine the data used to set the standards to make sure that all reported data is either reported as ML or RL. Any value below the RL is an estimated value and will be qualified (flagged) as such in the report from the laboratory. A number that has a qualifier is not a defensible number and should not be used for any purpose - either to set standards or to show compliance with that standard. A data point that is above the ML but below the RL is a result of extrapolation below the lowest calibration point. Extrapolation below the lowest acceptable calibration point simply does not result in a defensible number. Unless the current standards are developed from data that is defensible, the entire standards setting process is suspect. Commenter strongly recommends that the EPA examine or re-examine their data base to ensure that all data reported meets these quality requirements.
Several commenters (17725, 18014, 6637) state that the point at which a measurement can be deemed meaningfully quantifiable is at a much higher concentration than the MDL. This level is often referred to as a "limit of quantification" (LOQ). LOQ values represent a quantifiable measurement that still contains some degree of measurement uncertainty. Although there is no formal definition of LOQ even within analytical chemistry, it is commonly accepted that LOQ represents the value that will produce a relative standard deviation (RSD) in the measurements of 10 percent. Below MDL, the measurement data cannot be said to have any meaning. Above this threshold, the data might have only very limited meaning, but if there are a large number of low level measurements, then even though each individual measurement will have a very high level of uncertainty, the average of all the data will tend to approximate the population.
Commenter 17886 states that the appropriate metric to report or use in regulatory actions is the quantitation limit, which is usually three to ten times the detection limit. The quantitation limit is that level at which one can accurately determine the amount of a material that is present. Where ICR results fall in these low ranges, the EPA should determine the quantitation levels and use those levels as the basis for establishing MACT floors. The EPA should also ensure that MACT floors are not set lower than the quantitation limit for the applicable measurement method.
Commenter 17912 states that Part II test data submitted by Logan would not meet the Agency's proposed HCl emission limit: Logan's additional HCl data submitted is 6.6E-04 lb/MW, as compared to the proposed emission limit of 3.0E-04 lb/MW. Logan's would not be capable of meeting the surrogate SO2 emission rate of 0.045lb/MMBtu set by the EPA, given that Logan reported SO2 emissions of 0.091 lb/MMBtu. The EPA's proposed MACT floor for HCl for new units was calculated as three times the lowest MDL for the three sampling runs at Logan. The EPA can't use test results that are reported as "non-detect" from a single unit, especially when subsequent HCl tests for the same unit and reported to the Agency would constitute non-compliance if the proposed emission limit were adopted.
Response to Comment 14: See responses to Comment 1 and Comments 2-6, above.
Comment 15: Method 26A would not be able to measure HC1 or HF accurately.
Commenter 17621 states that unless better sensitivity can be obtained than indicated in Method 26A, this method would not be able to measure HCl or HF accurately in future EGUs at the proposed limit. Method 26A states that the typical analytical detection limit for HCl is 0.2 μg/ml and that the detection limits for other analytes (e.g., HF) should be similar. Assuming that 300 ml of liquid is recovered from the acidified impingers and the basic impingers, this would result in a MDL of 120 μg. Assuming that the sample volume is 2.5 cubic meters, the minimum required by the ICR, this mass corresponds to an emission rate for a coal-fired EGU of 4.4E-5lb/MMBtu. Comparing this analytical detection limit with the MACT proposal, the limit for existing coal-fired EGUs (0.002 lb/MMBtu) is well above the analytical detection limit. The limits for HCl and HF in existing oil units (3E-4 and 2E-4 lb/MMBtu, respectively) are above the analytical detection limit; however, the limit for all future EGUs (0.3 lb/GWh, equivalent to 3E-5 lb/MMBtu) is not.
Commenter 17621 also states that at 40 mg/dscm (about 0.04 lb/MMBtu), 99 of 100 future triplicate measurements will be within 11 percent of the true concentration. This concentration is 20 times higher than the MACT limit for existing coal-fired plants (0.002 lb/MMBtu) and about 1,300 times the MACT limit for new units. At 1 mg/dscm (9E-4 lb/MMBtu), 99 of 100 future triplicate measurements were predicted to be within +- 20 percent of the true value. At a stack gas concentration of 0.5 mg/dscm (4E-5 lb/MMBtu), the precision of the method (%RSD) fell to 30 percent. An acceptable level of precision for a test method is generally considered to be +- 15 percent. The ReMAP findings indicate that the lower limit of adequate precision for Method 26 is about 9E-4 lb/MMBtu. Over 90 percent of the HCl and HF ICR measurements made at coal-fired units were below 9E-4 lb/MMBtu, indicating that the great majority of the ICR measurements may not be accurate. The proposed MACT limit for existing coal EGUs (0.002 lb/MMBtu) falls in the range where acceptable accuracy is expected. However, the MACT floors for new coal and liquid oil-fired EGUs are much lower (3E-5 and 5E-5 lb/MMBtu, respectively) and the test methods are not expected to perform accurately at those concentrations.
Commenter 17795 states that the majority of data used for establishing the proposed EGU MACT HCl standard (acid gas surrogate) includes units with FGD control devices (i.e., wet scrubbers and spray dryer absorbers) that produce flue gas at or approaching saturation.
Response to Comment 15: The agency has reviewed the commenters' concerns and believes that its procedure for establishing the floor and the emissions limit ensures that the Methods identified in the rule, along with their requisite sampling times, are appropriate for determining compliance with the emissions limits.
Comment 16: Commenter 17807 is concerned that non-HCl chlorides from FGD units are a potential source of interference with the EPA Method 26A not typically found in dry stacks. Commenter recently tested trace metals in condensable fluid to determine the presence of non-HCl chlorides. The test results show concentrations of ammonia, calcium and magnesium in the condensable fluid indicating potential interferences causing high bias in the method 26A results. The contribution of chlorides from metal salts (e.g., CaCl2, MgCl2, MnCl2, and NH4CI) is not known, but presence of total ammonia, calcium, and magnesium suggests a substantial contribution of chlorides and HCl biases.
Response to Comment 16: The EPA acknowledges the potential for trace metals salts in the "condensable fluid," but the information provided in the comment does not support a definitive empirical interference or bias. Due to other comments, the final rule allows the use of Method 320 for HCl testing. Should an EGU owner or operator believe there are source-specific matrix interferences, he or she may request an alternative method of compliance with the standard per the requirements of section 63.7.
Comment 17: Neither Method 5 nor Method 27 establishes a Method Detection Limit for FPM.
Commenter 17621 states that the ICR required FPM tests on stacks with wet FGD units (wet stacks) to be conducted with Method 5, which uses a heated, out-of-stack filter. Some testers combined the Method 5 FPM measurement with a Method 29 metals analysis, reporting FPM from the probe and filter of the Method 29 sampling train. FPM tests on dry stacks were required to be conducted with OTM-27 (promulgated in December 2010 as revised Method 201A), which uses particulate sizing cyclones and an in-stack filter at stack temperature. The FPM method required for monitoring compliance with the TPM limit is Method 5 (for wet and dry stacks). A PM CEM can be used to monitor compliance with TPM, in place of Method 5 testing. Neither Method 5 nor Method 27 establishes a method detection limit for FPM; however, each method states a minimum mass that will allow acceptable precision in the gravimetric measurement.
a. Method 5 has two sample fractions, the filter and the rinsate of the sampling probe and line. Each fraction is weighed and the weights are summed to obtain the final result. The particulate filter is repeatedly dried and weighed until consecutive weighings are within 0.5 mg. The final weights are recorded to the nearest 0.1 mg. Commenter calculated the lower limit of method precision based on 0.5 mg times 2 (1 mg). Assuming the 4-hour sampling period required by the ICR, a sample volume of 120 dry standard cubic feet (dscf) and a default F-factor of 9780 dscf/MMBtu at 0% oxygen (O2), FPM residue can be measured accurately at 3E-4 lb/MMBtu. Very few ICR test runs reported FPM results lower than this: 1% of coal-fired EGU test runs and 3% of liquid oil-fired EGU test runs in the ICR Part III Access database would be considered inaccurate based on this metric.
b. OTM-27 (and Method 201A) has four fractions (the filter and three acetone rinses) that are repeatedly dried and weighed until consecutive weighings are within 0.5 mg or within 1% of total weight less tare weight. The final weights are recorded to the nearest 0.1 mg. Commenter calculated the lower limit of method precision based on 0.5 mg times 4 (2 mg). Based on this evaluation, Method 201A should be able to measure accurately at 6E-4 lb/MMBtu. About 16% of coal-fired EGU test runs in the Part III Access database, but only 3 percent of liquid oil-fired EGU test runs, fell below this emission value.
Response to Comment 17: Although the commenter is correct that neither EPA Method 5, Method 17, Method 29, Method OTM 27 or Method 201A identify method detection limits, there are several studies which have evaluated the detection limits for filterable particulate test methods. Generally, a minimum detectable mass of 1 to 1.5 mg was demonstrated. The majority of the imprecision was due to the weighing of the filter. Although there were few testers which recorded values less than these values, we made adjustments to samples which recorded values below these levels. We recognized the issue of detection levels prior to issuing the ICR which required four hour samples. As a result, we received very few particulate tests where the filter weight gain was less than 1.5 mg. With respect to testing to demonstrate compliance with either the existing source or new source standards, we do not expect any below detection level issues.
Comment 18: OTM-28 and Method 202 did not establish a Method Detection Limit.
Commenter 17621 states that most ICR test contractors used OTM-28; a few used the original Method 202. Neither method establishes a method detection limit. OTM-28 requires analysis of two sample fractions: inorganic (aqueous-phase) CPM and organic CPM. An ammonium hydroxide correction is applied to the inorganic fraction. The method allows for blank correction of residue in the field blanks of both fractions; however, the blank correction must be applied to the final CPM total (not the individual fractions) and the correction amount is limited to 2.0 mg. The median total CPM in blanks reviewed by Commenter exceeded 2.0 mg; thus, some of the ICR test results may have been biased high by this method restriction. No data sets had a gross inorganic catch less than 1 mg; however, 12 data sets reported an organic catch less than 1.0 mg. The data indicate that the MDLs were not an issue for the inorganic fraction, but reporting limits/MDLs may impact the organic fraction at some sites. Gravimetric detection limits ranged from 0.2 - 0.5 mg for the inorganic fraction and from 0.2 - 0.8 mg for the organic fraction. Assuming a 4-hour sampling period, an ICR sample volume of 120 cubic feet and a default F-factor of 9,780 dscf/MMBtu at 0% O2, total CPM emission rates corresponding to these detection limits range from 1.1E-4 lb/MMBtu to 3.5E-4 lb/MMBtu. The reporting limits for the inorganic fraction ranged from 0.5 - 1.0 mg; for the organic fraction they were all 1.0 mg. For the purpose of this evaluation, Commenter used a total CPM emission of 2E-4 lb/MMBtu (the middle of the range) to compare to the MACT limits. None of the total CPM emissions measured in coal- or oil-fired EGUs were lower than this value. The proposed TPM limit for new coal-fired EGUs is 0.05 lb/MWh (equivalent to 0.005 lb/MMBtu), about 20 times higher. This indicates that gravimetric imprecision is not a limiting factor for use of Method 202 at the proposed MACT limits.
Response to Comment 18: Although EPA Method 202 does not stipulate a method detection level in the method, the detection level as performed by EPA in a laboratory environment was reported in the preamble and response to comments for the method. The inorganic fraction has a detection level comparable to EPA Method 5 and the organic fraction's detection level is about an order of magnitude lower. Method detection level issues for test methods with multiple components are not impacted equally when different components are below detection level. The overall impact of the measurement is affected most by the fraction(s) which are greatest in mass (or highest detection level) and least by the fraction(s) with low mass (or lowest detection level). As a result, the non-detect values for the organic condensable particulate did not significantly degrade the overall precision for total condensable particulate matter or for many of the total particulate measurements. With the adjustments in the final rule (namely the use of filterable PM and not total PM as the alternate equivalent standard for non-Hg HAP metals), concerns over the use of OTM-28 and Method 202 in the context of the NESHAP standard are no longer applicable.
Comment 19: The methodology to monitor detection limits does not ensure limits derived are achievable.
Commenter 17690 states that the methodology related to monitor detection limits does not ensure that the limits derived are "achievable". As a result, the ICR data set published in the Utility MACT docket for oil-fired units does not provide adequate information to specify controls that can be expected to reasonably reduce stack concentrations to meet the proposed limits.
Commenter 18014 states that in cases where multiple units have reported emissions results that are at or below the detection limit, one cannot definitively establish a single "best performer" since the results represent values that are indistinguishable from one another. Although one source that reported a BDL value may have reported a slightly lower detection limit than another source due to individual test calibration, sample volume, or equipment differences, it would be arbitrary to suggest that the unit's performance is better than the other's for that reason. The Agency will need to establish a limit at a practical measurement threshold. The uncertainty of the reference methods makes it impossible to measure differences in emissions at these levels, whether for the purpose of setting the emissions standard or for potential compliance purposes.
Response to Comment 19: See generally the responses to Comment 1 and Comments 2-6, above.
Comment 20: Errors with sample collection and equipment handling, preparation, and analysis.
Commenters 17711 and 17812 state that all source emission measurements have random (precision) errors associated with the sample collection, sample and equipment handling, sample preparation, and sample analysis. When emission levels are much higher than the magnitude of these errors, there is a high degree of confidence in the measured value obtained from a test run. However, as the measured value decreases, the contribution of these errors to the measured value increases, thus decreasing the confidence level in the accuracy of the measured value to the point where the measured value cannot be distinguished from the random error ("noise" level). This is the case with the utility boiler dioxin/furan data. When this occurs, the measurement cannot be distinguished from zero with high confidence. Although the EPA Method 23 procedures minimize measurement errors at the stack emission levels and applications for which it was intended, measurement errors are not zero and become significant at the extremely low levels in boiler exhaust. In setting recent MACT standards (e.g., Industrial Boiler MACT), the EPA has acknowledged that the emission limit should not be set below the capability of the applicable test method. However, the EPA did not use the widely accepted definition of test method detection limit, which is based on the capabilities of multiple commercial laboratories to collect and analyze a stack sample and identify the presence of a chemical above the "noise" level. This erroneous methodology results in estimating D/F detection limits that are lower than those regularly achieved by commercial laboratories. Reported values below the method's quantitation limit should not be treated as real values.
Response to Comment 20: The final rule provides for a work practice standard to ensure that dioxin/furan emissions are minimized. The final rule does not require any testing of these emissions from affected EGUs, and thus the concerns raised in this comment are not applicable in the context of this rule.
Comment 21: Determination of coal rank and heating value should be based on long standing USGS classification.
Commenter 17725 recommends that the determination of coal rank and heating value be based on long standing USGS classifications of coal regions and sampling of coal properties within the U.S., and additional sampling and analysis only for imported coals.
Response to Comment 21: The final rule does not include fuel sampling and analysis requirements, and, thus, this comment is no longer applicable.
Comment 22: Sample size will determine the level of accuracy.
Commenter 17725 states that in MACT floor analysis, there are a fairly large number of low level measurements, such that performing the UPL analysis on the data can be a valid exercise, presuming that the measurements reflect the true variability. However, the same is not true for a small sample size. In assessing the performance of any unit based on the results of a single compliance test (or even a handful of tests), particularly if those results are below the LOQ, one must take special care not to fall prey to "Law of Small Numbers" fallacy. Not only might the results not represent the entire range of operating conditions or fuel supplies, but the measurements may be subject to significant uncertainty.
Response to Comment 22: There are situations in which the final rule relies on periodic testing to demonstrate compliance with the emission limits. In other cases, the rule provides for continuous monitoring. In all cases, the test methods established by the rule will be used to determine compliance. The UPL analysis, although used to aid the standard setting process, is not part of the compliance demonstration process.
Comment 23: Recommended adjustments for truncated data.
Commenter 17725 recommends that when evaluating the validity of any data set, the EPA must consider not only how the samples were acquired, but also how the analyses were performed. As the quantity of the analyte falls below the MDL, there is virtually no confidence in the measurement. However, if the quantity of the analyte is above the LOQ, reasonable results may be obtained. MDL may be described as the absolute lowest quantity that may be discerned from the baseline noise of an analytical device. This quantity allows determination of whether some versus none of the analyte is present. However, in most cases the inaccuracy and uncertainty of the quantity is too large to be considered a reasonable result. Therefore, additional quantities have been developed to add some degree of certainty to a measurement. These quantities may be referred to as either the LOQ or the practical quantification limit (PQL). These quantities are simply some multiplier, typically ranging from 5 to 10 times the MDL. PQL is typically defined as 5 times the MDL.
Commenter 17725 adds that a practical method for determining the MDL is to analyze 8 replicate samples of a concentration near the expected limit of detection. The standard deviation is then determined. The MDL may then be computed by multiplying the one-sided t distribution and the determined standard deviation. For eight samples (with seven degrees of freedom) the t value for a 99 percent confidence interval is approximately three. Thus, the standard deviation multiplied by three may be defined as the MDL. Once the MDL is determined, a LOQ may then be defined as anywhere between 5 to 10 times the MDL. Method 30B contains stringent requirements with regard to the calibration procedure, performance specifications, and ongoing checks of the analytical device. These procedures and specifications are present to ensure data of an acceptable quality and known uncertainty are obtained. However, the manner in which the analytical device is configured and calibrated affects the MDL and thus the LOQ.
Response to Comment 23: See generally the responses to Comment 1 and Comments 2-6, above.
Comment 24: Commenter 17877 states that the EPA's effort to set emission limits for all HAP emitted by coal-fired EGU boilers is greatly complicated by the fact that a number of HAP are emitted at levels at or below the MDL that was used to collect and analyze HAP emissions. Detection limit issues have significant impacts on MACT standard setting as well as later during compliance demonstrations. First, the Agency did not provide a clear and proper definition of detection limit in the EGU ICR. As a result, the detection limits reported in the ICR responses are inconsistent and are not even based on a common understanding of the term "detection limit." It is likely that most EGU owners seem to have reported the "detection limit" value they were provided by the laboratory analyzing the ICR samples. The ICR data shows that some "reported" values are actually below the detection limit values reported in other ICR tests. Second, the EPA's focus on the MDL reported by a given laboratory ignores many sources of measurement error that can affect a reported result. Accuracy considerations are not limited to the ability of a single laboratory to precisely measure the amount of a substance in a given sample it receives. Measurement errors also occur during the collection of a sample at the stack, the transfer of that collected sample to whatever means are used to transport the sample to an analytical laboratory, and the interlaboratory inaccuracies of different laboratories testing the same sample. The EPA's proposed rule does not address these areas of collection and analytical error. As a result, the EPA's detection limit analysis is fatally flawed.
Response to Comment 24: See generally the responses to Comment 1 and Comments 2-6, above.
Comment 25: Commenter 17878 recommends that the EPA clarify the role of analyte measurement. This method is designed to measure the mass concentration of total vapor phase Hg in flue gas, including elemental Hg (Hgo) and oxidized forms of Hg (Hg+2), in micrograms per dry standard cubic meter (μg/dscm).
Response to Comment 25: The commenter is correct in stating that Method 30B is designed to measure the mass concentration of total vapor phase Hg emissions from stationary sources, specifically the combination of elemental (Hgo) and oxidized (Hg2+) emissions, and this is specifically stated in Section 1.1 of the method.
Comment 26: Commenter 17914 recommends that the EPA reject the data below the PQL from the data set used to set the MACT floor limits. The PQL should be set at five times (or higher) the MDL and not the three times suggested in the MACT preamble. The emission limits should be set at a level which can be accurately and repeatedly measured by the reference method.
Response to Comment 26: See generally the responses to Comment 1 and Comments 2-6, above.
Comment 27: Commenter 6637 states that the ICR requirements for assigning data flags to indicate the detection status of an emissions value were not consistently followed. A significant percentage of emissions values (up to 20 percent for some parameters) were incorrectly flagged and thus did not indicate accurately whether a reported emissions value was detected.
Response to Comment 27: We have recognized that not all respondents followed the directions which were provided and many took shortcuts or other alternative data entry procedures. Although we may not have identified all of these situations, we did attempt to put out of character reports into perspective and use the data as appropriate for other data of similar reported values. We noticed that in addition to reports which either did not report detection level issues when values were low, testers did not report individual values for multi-component analyses, and reported detection level issues when values were significantly higher than other labs that reported measureable values.
Comment 28: Commenter 6637 states that for test methods that require multiple analyses for a single sample (for example, the filter and resin trap fractions of a speciated organics sample), the ICR required the emission values to be assigned a DLL flag when the sample fractions were a mixture of measurements above and below detection limits. Logically, if a chemical is above detection limits in any fraction of a sample, it can be assumed that the chemical is detected in that sample. However, the ICR required the same format to be used in the Excel template for both DLL- and BDL-flagged results. With this convention, results that are truly below detection will be indistinguishable from those in which one fraction is very high and one is below detection.
Response to Comment 28: We recognize that multi component analyses which have a mixture of measurements above and below detection limits require additional assessment to determine the precision of the overall measurement. Where the non-detect value is for a component that is typically a minor component of the overall emissions, this non-detect may have a minor impact on the overall precision of the test. On the other hand where the non-detect value is for a component that is typically most of the emissions, the impact of the non-detect value can be significant. As part of the identification of the best performing 12 percent and determination of the emissions limit we were cognizant that the lowest emitting sources could have greater issues with non-detect components. We believe that the procedures that we used in addressing BDL issues have adequately addressed not only the setting of a level indicative of the best performing 12 percent but also establish a level which can be reliably measured and therefore used to demonstrate compliance with the established level.
Comment 29: .Commenter 6637 states that very few ICR data packages provided sufficient detail on the detection limit used for non-detected emissions to determine if there were equivalent bases for different reports. The method used to derive the detection limit was rarely stated in the ERT or emissions spreadsheet. In some cases, an explanation was included in the stack test report, but more often the information was simply not provided.
Response to Comment 29: We agree that there was a general lack of documentation on the methods used by laboratories for assessing their analytical detection limits. For those pollutants for which we are establishing numerical emissions limits, we do not believe that we require this level of detail. We believe that BDL values reported by the laboratories of the best performing 12 percent of sources have generally employed methodologies for determining the BDL level that are consistent with our criteria.
Comment 30: Several commenters (6637, 19536, 19537, 19538) state that many of the "nondetect" values reported by laboratories were stated to be reporting limits, which represent the laboratory's best estimate of the lowest concentration that can be measured accurately in a particular sample matrix. A reporting limit is always higher than the method detection limit, but there is no set procedure for determining a reporting limit  --  it differs from one laboratory to the next. Ten randomly selected data packages were reviewed, representing different combinations of stack testers and laboratories that provided multiple sets of data for arsenic. Two issues are apparent in Table 3-1 (Table 3-1 Excerpted). First, none of these laboratories reported MDLs for arsenic to represent nondetects; in all but one case, a reporting limit was used. For one data set, the basis of the value was not provided. Second, even when a MDL was listed in the laboratory report in addition to the reporting limit, it was rarely possible to determine whether the MDL had been adjusted upward to reflect dilution of the sample. The implication of these observations for the ICR data is that it will be very difficult to put all of the nondetect values on a consistent basis.
Response to Comment 30: As stated earlier, we recognize that many respondents, including the laboratories they used, did not follow the procedures which we provided. We also believe that we have instituted procedures for the selection of the best performing 12 percent and for setting the emissions standard which minimize the impact of the non compliant-reporting of the detection levels.
Comment 31: Commenter 18021 is concerned that errors were found in some of the data that is being used as a basis for these standards including conversion errors related to establishing the MACT floor for Hg. Furthermore, we believe the EPA's approach to synthesizing a performing unit to generate what they consider to be usable data is not defensible. It is important that a regulation that has the degree of impact on the industry, inherent in these requirements, be based on a solid, documented, QA/QC review. Outliers should be eliminated or included with a specific justification. Additional explanation is needed for how data that is below an accepted MDL is being qualified.
Response to Comment 31: As noted elsewhere in this document, we believe that we have corrected all of the conversion errors brought to our attention, provided the necessary QA/QC, conducted the appropriate outlier analyses, and explained our approach to the use of MDL data. Further, we believe that we have established the MACT floors in accordance with the statute and Court decisions.
Comment 32: Commenter 17621 notes that the lowest emitting EGU is often one in which all runs are flagged BDL, indicating that emissions are below detection limit. However, those detection limits often are low not because the laboratory used unusually sensitive techniques, but because the reporting requirements specified in the ICR were not followed. A very common error, observed by the commenter in many ICR Part III ERT files, is failure to sum the fractions of a multi-fraction sample correctly. For example, if, rather than summing the detection limits of the front half and back half fractions of a Method 29 sample, as required for the ICR, the emission was reported using the MDL of only one fraction, this would result in a much lower "MDL" value. Blank-correcting metals results to below the MDL are another common error that results in an unrealistic, low emission value.
Response to Comment 32: While the commenter is correct that a large number of respondents did not follow the reporting requirements that we specified, we assessed the veracity of submitted data to correct or exclude data which would result in significant errors in the development of the emissions limits. We did not find any consistency in testers reporting values that were likely to result from the use of only one component of a multi component analysis. The commenter focuses on the submission of data which are reported at levels lower than the capabilities of a reasonably competent tester and laboratory. In the development of the numerical limit for the best performing 12% of the sources, data similar to what the commenter describes are a very small component of the overall data. For the development of the numerical limt for the best performing source, our procedures for identifying a representative detection level and for using this value in establishing the numerical limit (described elsewhere) more than adequately address any issue that may be due to our inability to identify data similar to what the commenter describes.
4A04 - MACT Floor Methodology: Potential three-times method detection level approach for limits
Commenters: 17620, 17621, 17716, 17725, 17730, 17851, 18014, 18034, 18421, 18498, 19536, 19537, 19538
Comment 1: Commenter 17716 notes that the EPA proposes to account for measurement imprecision by determining the highest MDL below emissions limit in any data set and multiplying that number by three. If the multiplication shows a number "less than the calculated floor emissions limit, [the EPA] would conclude that measurement variability is adequately addressed and [the EPA] would not adjust the calculated floor emissions limit. If, on the other hand, the value equal to three times the representative MDL were greater than the calculated floor emissions limit, [the EPA] would conclude that the calculated floor emissions limit does not account entirely for measurement variability. [the EPA] then would use the value equal to three times the MDL in place of the calculated floor emissions limit to ensure that the floor emissions limit accounts for measurement variability." 76 FR 25044... EPA's suggestion that the three times for any UPL below MDL "ensure[s] measurement variability is adequately addressed in the floor or the emissions limit," 76 FR. 25044/3, is a valid objective. Using a three-times factor seems intended to address the fact that "environmental measurements used by EPA in other rulemakings exhibit accuracies of plus or minus up to 15 percent." 76 FR 25023; see also id. at 25044 ("pollutant measurement imprecision decreases to a consistent relative 10 to 15 percent for values measured at a level about three times the MDL"). Although the EPA cites the ASME Reference Method Accuracy and Precision ("ReMAP") report [American Society of Mechanical Engineers, Reference Method Accuracy and Precision (ReMAP): Phase 1, Precision of Manual Stack Emission Measurements, CRTD Vol. 60, February 2001] for the latter claim, no such statement appears in the document.
The commenter believes quite the opposite, i.e., that the results of the ReMAP study demonstrate that such accuracies will not be achieved at the 3 x MDL level. As shown in the table below, applying the ReMAP equations to the EPA's hypothesis demonstrates that a higher value than 3 x MDL must be used. Multipliers of five to ten are often used in conjunction with the MDL to represent the point where meaningful quantification occurs. Accordingly, the commenter recommends that the EPA use a value of at least 5 x MDL.
MDLs and PQLs Derived from ReMAP Study Results using EPA Assumptions

                                MDL (50% Error)
                                    3 x MDL
                                LOQ (15% Error)
                              Method 29 (Metals)
                      0.06 μg/dscm 5.34 x 10-8 lb/MMBtu
                      0.18 μg/dscm 1.60 x 10-7 lb/MMBtu
                       50 μg/dscm 4.45 x 10-5 lb/MMBtu
                                Method 26 (HCl)
                      0.003 mg/dscm 2.67 x 10-6 lb/MMBtu
                      0.0009 mg/dscm 8.01 x 10-6 lb/MMBtu
                        1 mg/dscm 8.90 x 10-4 lb/MMBtu
Comment 2: Commenter 17620 states that there is no technical basis for assuming that a value that is reliably reported as below the detection limit is three times higher than that value. This is especially true where the EPA has instructed sources to use a very high value for the detection limit. The EPA recognizes that use of three times the minimum detection limit may lead to inappropriately high MACT floor calculations and has requested comment on this issue as well as how to calculate variability, where a significant part of the data is below the detection limit. The EPA should use a figure no higher than the detection limit for its calculations.
Comment 3: Commenter 17621 states that the procedure described for limits based on an " MDL" requires clarification: The procedure for adjusting some MACT floors for new EGUs to be above a method detection limit (MDL) [FR 25044] does not clearly indicate that the " MDL" that is referred to is actually the lowest test run value in the 3-run test series of the lowest-emitting EGU. For example, in the coal HCl MACT floor worksheet (EPA-HQ-OAR-2009-0234-3036), cell C102 of the HCl_New_MW tab points to cell B7 -- a BDL value that is more than two times lower than the other two BDL values in the same test series. The selected value cannot be called a representative "MDL" for the method. Multiplying that "MDL" by three, as the EPA has done, results in a MACT limit that is exceeded by test series from the same EGU. The ICR database contains BDL-flagged HCl values 10,000 times higher than the one selected, indicating that it is highly unlikely that the "BDL" value selected is representative or achievable by all laboratories.

Reference: based on results of a statistical study provided in commenter's Appendix D section: "The procedure described for limits based on an " MDL" requires clarification." Commenter adds that basing the MACT limit on three times the lowest test run of the lowest test series of the lowest emitting EGU resulted in a limit that could not be detected at that EGU on a consistent basis. That is the case for HCl for new coal units, where all measurements in all test series were non-detect and several of the detection limits exceeded the proposed limit.
Reference: based on results of a statistical study provided in commenter's Appendix D section: "regarding EPA's unit limit calculation procedures and why these procedures may produce a new unit limit below the actual capability of the test method."

Comment 4: Commenter 17621 states the method of determining HCl and HF limits for new EGUs by selecting lowest test run values in the lowest test series of the lowest emitting coal-fired EGU and multiplying that by a factor of three without consideration for outlier identification or reporting errors, instead of statistically analyzing the ICR data, resulted in limits for new EGUs that are not achievable with the methods used in the ICR.

Commenter 17621 states that the new unit HCl and HF limits for coal-fired and oil-fired EGUs are based on low outliers, which can be noted when comparing the emission values to the average emissions for other test series of all flagged BDL from Part II and Part III data. Commenter adds that is would be more appropriate to set the limit at a concentration that most qualified labs could measure accurately in the stack gas samples.

Commenter 17730 states that the error band of 10 to 15 percent associated with using a value three times the method detention limit is too large; therefore, a larger multiplier is needed.

Commenter 17730 states the EPA needs to conduct broad based studies to determine the PQLs for the compliance methods it chooses for showing compliance with HAP limits, and then set MACT limits based on those PQLs.

Commenter 17730 states that a MDL supplied by a given laboratory does not account for all sources of variability in sample collection, nor inter-laboratory variability in analyzing a given sample.

Commenter 17851 suggests the EPA use work practice standards any time they do not have reliable data on which to develop standards.

Commenter 17851 agrees with conclusions made in the 1995 paper, Development of Compliance Levels from Analytical Detection and Quantification Levels, written by the Agency's Engineering and Analysis Division, stating that the lowest number that can be used for developing standards and showing compliance with those standards is the ML or RL. Commenter includes a copy of the paper in Appendix A to the docket entry EPA-HQ-OAR-2009-0234-17851.

Several commenters (17725, 18014, 18498) state that the EPA described a RQL (Representative Quantification Limit or three times the RDL) approach in the preamble similar to the one it used for the IB MACT floor analysis. The Agency said this approach could be used; however, the Agency did not actually apply the approach and did not adjust to address low level measurement variability in the proposed rule.

Commenters 17725, 18014, and 18498 support the Agency's RQL approach with the following exceptions:

      a. Because the issue of measurement uncertainty is fundamental to the analysis and is unrelated to any subcategorization, it is appropriate to establish "method-specific" detection limits based on all available data for that method regardless of subcategory.

      b. Although the agency cites the ASME ReMAP report to support the claim that using three times the MDL to estimate the RQL is sufficient to achieve the agency's target reference method uncertainty of 10 to 15%, commenters did not come to the same conclusion and actually used the information to determine the multiplier of three is insufficient. Using equations from the ASME ReMAP which characterized method uncertainty as a function of emission concentration, the commenter calculated the concentration at which the RSD will be 50% and assigned the value as the MDL, and calculated the concentration at a 15% RSD and assigned it as the LOQ threshold which is compared to three times the MDL. Commenters reference Table 6 in docket EPA-HQ-OAR-2009-0234-18014 for results of these calculations. Commenters recommend using a multiplier of five.

      c. The way that the agency implemented this adjustment in the final IB MACT Rule is problematic because it determined the RQL for assessing a new unit limit based solely on the MDL results reported for that top performing unit. The agency should use the same RDL that it determines for the existing unit floor when evaluating the new unit limit since the same methods are used to assure compliance with each limit. It is important to identify a representative quantification level for any reference method test for the pollutant of interest to ensure the limits can be reasonably quantified during future tests. If the EPA were to use only the MDL associated with the best performing unit test, the resulting RDL would not be representative.
Commenters 17725 and 18498 agree that some statistical screening should be applied to the data, but the suggestion that the RQL be limited to the floor emissions limit is a questionable practice since it assumes dependence between the RQL and the average. Although commenters would typically recommend a more standard statistical screening, they believe that the screening the agency described will be adequate in this case.
Commenters 17725 and 18498 recommend that the agency use the RQL determined in conjunction with the existing unit floor for the other smaller solid fuel sub-categories.
Several commenters (17725, 18014, 18498) agree with the agency's proffer of three times the RDL value as a replacement for any UPL below that threshold to address measurement variability and states that any limit that does not take measurement variability into account would be arbitrary.
Commenters (17725, 18014, 18498) states that a review of the data indicates that the agency may not be able to establish RQL values for pollutants or surrogates following the approach it described and suggests the following alternate procedures for specific pollutants/surrogates:
      a. Commenters (17725, 18014, 18498) suggest for Method 29 metals measurements, the EPA should be able to establish reasonable RQL values based upon the reported detection limits in the ICR database following the approach. A RQL for total metals would then be represented by the sum of the ten individual metal RQLs.
      b. Commenters (17725, 18014, 18498) note that the predominate Hg reference method used for the ICR was Method 30B and recommends using a RQL value for Hg of at least 0.04 ug/m[3] based on reasoning provided in "Discussion of Method Detection Limit and Limit of Quantification for Method 30B." The article is attached to the docket entry EPA-HQ-OAR-2009-0234-18014. Commenter adds that the EPA's approach will tend to overstate the RDL for Hg because some testers used Method 29.
      c. Commenters (17725, 18014, 18498) state that the MDL reported during the ICR for HCl seems higher than expected due to some sources combining Method 26 trains with CTM-033 and recommends using an RQL of at least a multiplier of three or five times the MDL.
      d. Commenters (17725, 18014, 18498) state that for PM a different procedure for handling non-detect values is warranted because few sources reported non-detect values in the ICR database for filterable PM test methods or for the calculated total PM values. Commenters suggest using MDLs of 2.5mg for filterable PM and 4.1 mg for condensable PM, as suggested in a field study (Field Evaluation of Condensable Particulate Matter Measurement, U.S. EPA Office of Air Quality Planning and Standards, Sector Policy and Program Division Monnitoring Policy Group (prepared by Eastern Research Group, Inc under EPA Contract No. EP-D. 07-097), 2010)) conducted by the Agency to validate revisions to Method 202, and a minimum sampling volume of 4 dscm. Commenters state that the RQL values for PM should be considered conservative because the MDL values from the field study may not be representative of actual field measurements due to variability in blank values and differences in practices used by stack testers and the test contractor. Commenters add that for condensable PM and SO2 artifacts can have a significant impact on low level measurements.
Several commenters (17725, 18014, 18034, 18498) assert that the EPA should not set a limit below the LOQ of a compliance method since obtaining repeatable measurements below the LOQ is technically infeasible and a source with adequate performance could not be expected to demonstrate compliance with the standard on a consistent basis.
Commenters 17725 and 18498 state that if an emissions measurement is not feasible, the Agency could promulgate a work practice in lieu of an emissions standard in accordance with Section 112(h) of the CAA.
Commenter 18034 states that the EPA did not provide any technical or statistical analysis to support that using a value equal to three times the MDL sufficiently accounts for measurement uncertainty for the purposes of establishing compliance.
Commenter 18034 states that because the MACT floor limits are based on a series of three test runs on a single source, multiplying the MDL by a factor of three does not account for the range of variability of the detection limits across sources.
Commenter 18034 states a unit used to set the new unit HCl MACT floor for coal-fired EGUs is equipped with dry fFGD. Commenter adds that an emission limit based on MDL determined on a unit equipped with dry acid gas controls is likely biased against units equipped with wet scrubber control technology.
Commenter 18034 states that basing the proposed HCl emission limit and some of the other new unit emission limits on the MDL of the methods used for the ICR is technically unsound and may be impossible for sites to demonstrate compliance with using the prescribed test methods. Commenter asserts that basing emission limits on non-detectable test results is problematic because the in-stack detection limits for Method 26A are dependent on a number of variables and the MDL for these methods will vary depending on what control equipment is installed. Commenter adds that the Agency does not appear to have accounted for the fact that because the Method 26A impinger solutions are analyzed directly without concentration or extraction, the effective detection limit of the test on a specific source is increased as more moisture vapor is condensed in the sampling train impingers and the volume of impinger solution for analysis increases.
Commenter 18034 suggests the EPA abandon attempts to apply adjustment factors to determine emissions limits based on data close to the MDL or multiplier of the MDL when results are less than the MDL and should only include in the MACT floor analysis those emission results with data that are above the LOQ.
Commenter 18034 states that in the EPA's NESHAP for Boilers in response to similar suggestions about using MDL to determine emissions limits, the Agency rejected the idea of using LOQ or the practical quantitation limit (PQL) as criteria for screen emissions data for MACT floor analysis because such criteria are variable from laboratory to laboratory, and the Agency stated it cannot apply data arbitrarily adjusted in establishing the floor. Commenter adds that the MDL is variable from source to source, condition to condition, and can vary depending on laboratory procedures; therefore, commenter contends that the EPA's approach to adjusting and applying MDL values for establishing MACT floor limits for the utility NESHAP rule is arbitrary.
Commenter 18034 states that the agency's argument that LOQ and PQL are not defined statistically is contradictory to the EPA's definition of LOQ as being the level at which there is a known degree of confidence.
Commenter 18421 urges the agency to require greater reduction in emissions of Hg from coal-fired power plants, stating that technology solutions to reduce mercury are widely available and cost-effective. The commenter adds that many coal-fired units are already achieving or have emissions significantly lower than the Hg standards promulgated in the proposed rule and that standards promulgated under CAA section 112 of the CAA should represent the average emission limitation achieved by the best performing 12% of existing sources.
Commenters (19536, 19537, 19538) assert that the agency should not set limits at triple the MDL.
Commenters (19536, 19537,19538) state that the ReMAP study (included as an appendix to Docket No. The EPA-HQ-OAR-2009-0234-2937) cited by the agency to support the measurement imprecision suggested by the agency does not in fact support the EPA's statements that pollutant measurement imprecision decreases to a consistent relative 10-15% for values measured at a level about three times the MDL. Commenter adds that the ASME ReMAP used Method 26, and the EPA used 26A for HCl analysis in the ICR data collection. Commenters note that the data set does not fall in line with the assumption used in the ReMAP that the average pollutant concentration does not vary with time, noting that the current data sets have both random and systematic errors and temporal variations. Commenters state that, in the ReMAP data for 99 out of 100 triplicate measurements of HCl over a wide range of concentration, it is shown that over a very wide range of true concentrations the variability is such that the prediction range varied by 8-20%, which does not correspond to the agency's statement regarding imprecision of 40-50% at or near the MDL.
Commenters (19536, 19537, 19538) state that section 112 does not permit the agency to substitute triple the detection limit for standards based on the actual performance of the best performing similar source and requires new source standards to be no higher than the emissions of the best performing similar source. It does not suggest that actual emissions reported below the detection limit are triple the selected detection limit. Commenter adds that if the emissions data from sources at or near a detection limit are imprecise by 40-50%, then at most, the actual emissions would be 50% higher than the reported detection limit for that source.
Commenters (19536, 19537, 19538) state the CAA requires standards to be at least as stringent as the average emissions achieved in practice by the best performing 12% of existing sources, but the agency has substituted a figure that does not reflect the actual emissions of any source within the category.
Commenter 17621 asks the EPA to consider whether a MACT limit based on an EGU where all test runs were below detection qualifies as a "lowest emitting unit," because these emissions are not quantifiable.
Response to Comments 1 - 4: The EPA agrees with many of comments related to treatment of data reported as detection limit values in the development of MACT floors and emissions limits. The probability procedures applied in calculating the floor or an emission limit inherently and reasonably account for emissions data variability including measurement imprecision when the database represents multiple tests from multiple emissions units for which all of the data are measured significantly above the method detection level. That is less true when the database includes emissions occurring below method detection capabilities regardless of how those data are reported. The EPA's guidance to respondents for reporting pollutant emissions used to support the data collection specified the criteria for determining test-specific method detection levels.
Those criteria insure that there is only about a 1% probability of an error in deciding that the pollutant measured at the method detection level is present when in fact it was absent. Such a probability is also called a false positive or the alpha, Type I, error. This means specifically that for a normally distributed set of measurement data, 99 out of 100 single measurements will fall within +-2.54 σ of the true concentration. The anticipated range for the average of repeated measurements comes progressively closer to the true concentration. More precisely, the anticipated range varies inversely with the square root of the number of measurements. Thus, if σ is the standard deviation of anticipated single measurements, the anticipated range for 99 out of 100 future triplicate measurements will fall within +- 2.54 σ/√3 of the true concentration. This relationship translates to an expected measurement imprecision for an emissions value occurring at or near the method detection level of about 40 to 50%.
By assuming a similar distribution of measurements across a range of values and increasing the mean value to a representative higher value (e.g., three times minimum detection level), we can estimate measurement imprecision at other levels. For an assumed 3x representative method detection level (RDL), the estimated measurement imprecision for a three test run average value would be on the order 10 to 20 percent. This is about the same measurement imprecision as found for Methods 23 and 29 indicated in the ASME Precision of Manual Stack Emissions Measurements for the sample volumes prescribed in the final rule (e.g., 4 to 6 dscm) for multiple tests.
Analytical laboratories often report a value above the method detection limit that represents the laboratory's perceived confidence in the quality of the value. This arbitrarily adjusted value is expressed differently by various laboratories and is called limit of quantitation, practical quantitation limit, or reporting limit. In many cases, the LOQ, PQL, or RL is simply a multiplication of the method detection limit. Multipliers range from three to ten. Consistent with findings expressed in reports of emissions measurement imprecision and the practices of analytical laboratories, we believe that using a measurement value of three times a method's detection limit established in a manner that assures 99 percent confidence of a measurement above zero will produce a representative method reporting limit suitable for establishing regulatory floor values.
On the other hand, we agree with commenters that an emissions limit set determined from a small subset of data or data from a single source may be significantly different than the actual method detection levels achieved by the best performing units in practice. This fact, combined with the low levels of emissions measured from many of the best performing units, led the EPA to review and revise the procedure intended to account for the contribution of measurement imprecision to data variability in establishing effective emissions limits. In response to the comments and internal concerns about the quality of measurements at very low emissions limits especially for new sources, we revised the procedure for identifying a RDL.
The revised procedure for determining an RDL starts with identifying all of the available reported pollutant specific method detection levels for the best performing units regardless of any subcategory (e.g., existing or new, fuel type, etc.). From that combined pool of data, we calculate the arithmetic mean value. By limiting the data set to those tests used to establish the floor or emissions limit (i.e., best performers), we believe that the result is representative of the best performing testing companies and laboratories using the most sensitive analytical procedures. We believe that the outcome should minimize the effect of a test(s) with an inordinately high method detection level (e.g., the sample volume was too small, the laboratory technique was insufficiently sensitive, or the procedure for determining the minimum value for reporting was other than the detection level). We then call the resulting mean of the method detection levels as the representative detection level (RDL) as characteristic of accepted source emissions measurement performance.

The second step in the process is to calculate three times the RDL to compare with the calculated floor or emissions limit. This step is similar to what we have used before including for the Portland cement MACT determination. We use the multiplication factor of three to approximate reduce the imprecision of the analytical method until the imprecision in the field sampling reflects the relative method precision as estimated by the ASME study that also indicates that such relative imprecision, from 10 to 20 percent, remains constant over the range of the method.es. For comparing to the floor, if three times the RDL were less than the calculated floor or emissions limit (e.g., calculated from the UPL), we would conclude that measurement variability was adequately addressed. The calculated floor or emissions limit would need no adjustment. If, on the other hand, the value equal to three times the RDL were greater than the UPL, we would conclude that the calculated floor or emissions limit does not account entirely for measurement variability. If indicated, we substituted the value equal to three times the RDL for the calculated floor or emissions limit which results in a concentration where the method would produce measurement accuracy on the order of 10 to 20 percent similar to other EPA test methods and the results found in the ASME study.
We determined the RDL for each pollutant using data from tests of all the best performers for all of the final regulatory subcategories (i.e., pooled test data). We applied the same pollutant-specific RDL and emissions limit adjustment procedure to all subcategories for which we established emissions limits. We believe that emissions limits adjusted in this manner better ensure measurement variability is adequately addressed relative to compliance determinations than did the procedure applied for the proposal that may have been based on limited data sets. By accounting for measurement uncertainty in this manner, we also believe that the emissions testing procedures and technologies available are adequate to provide the measurement certainty sufficient for sources to demonstrate compliance at the levels of the revised emissions limits.4A05 - MACT Floor Methodology: variability
Commenters: 16849, 17621, 17681, 17725, 17774, 17776, 17798, 17807, 17820, 17904, 17930, 18443, 18498, 18500, 19114, 19122, 18023
1. Limitations of ICR data.
Comment 1: Commenter 16849 states that the ICR data reflects results obtained under optimal steady-state operating conditions and does not reflect real-world situations. Actual boiler operating load change and can even swing, equipment and parts deteriorate or fail without warning, maintenance cannot be geared toward 3 hours periods, weather conditions vary, and coal/fuel quality changes. The EPA has used a small number of tests that set the standards for all other existing sources, which often operate in less than perfect conditions.
Comment 2: Commenters 17621 and 17725 state that a significant limitation of the collected ICR data is that they do not reflect the full extent of emissions variability over time. The field measurements conducted for the ICR were generally limited to three short-term snapshots of stack emissions, conducted over a period of several days, with the unit burning a single fuel type and operating at full load. The ICR data do not adequately reflect process variability associated with fuel composition, control device operation, and other process variables. In those cases where the longer historical time perspective is lacking in the baseline data pool, the baseline variability used for the UPL calculations will be incompletely represented, and will not reflect the additional variability that the baseline EGUs would experience over time. Reference: Based on results of a statistical study provided in commenter's Appendix D.
Comment 3: Commenters 17681 and 19122 state that the EPA established the limit based on the ICR data during steady-state, full-load conditions, which does not account for emissions variability resulting from startup, shutdown, soot blowing and malfunction. The EPA needs to either propose a separate work practice standard or exempt any operational mode not included in the establishment of the MACT floor for demonstration of compliance with the PM limit.
Comment 4: Commenter 17904 states that the EPA's emissions data for the proposed MACT standards is taken from the 2009 ICR, which required certain individual EGUs to conduct stack sampling over a three-day period. The EPA used this data to establish the range of performance and variability for all EGUs. However, those three day tests can only provide a snapshot of a given unit's HAP emissions. Such tests are not indicative or representative of emissions over longer periods of time. In light of the snapshot nature of the ICR data, the data set does not represent the actual operating range of the EGUs covered by the rule (including the best performing sources).
2. Operational variability not accounted for.
Comment 5: Multiple commenters (17774,17776, 17798, 17820, 17904, 18443, 19114, 18023) state that the EPA has not fully accounted for operational variability (startup, shutdown, and load changing operations, ambient conditions, age of equipment, fuel variability causing changes in control equipment operations, etc.) of EGU's.
Comment 6: Commenters 17774 and 17904 state that the UPL statistics can never capture the variability of the operating range of the affected facilities. Without additional consideration of operational variability, the EPA's UPL analysis is insufficient to ensure that the MACT floors are achieved under all foreseeable operational conditions by the best performing sources.
Comment 7: Commenter 17776 states that HCl and Hg results are likely to be constantly at or just below the proposed MACT limits for EGUs. It could take only one erroneous or higher than normal result to exceed a 30-day average limit.
Comment 8: Commenters 17798 and 17820 state that the resulting filterable PM limit does not account for operating variability. Commenters recommend that the EPA should consider such variability in response to the DC Circuit Court Action (Federal Register, Vol 76, No. 85, page 25041) when setting the limit for total PM. It does not seem reasonable that a source now has to comply with a CEM limit based on a one time test with no accounting for operating variability. It seems that sources will need to operate at their highest possible emission level in meeting the PM total limit during testing in order to establish the most flexible PM filter limitation. This is contrary to demonstrating real emission performance and the environmental benefits achieved by a source.
Comment 9: Several commenters (17774, 17820, 17904) state that the emissions of HAP are highly variable for even the best performing single EGUs. Commenters cite the DC Circuit in National Lime Association vs. The EPA [627 F.2d 416, 431 n.46 (D.C. Cir. 1980)] held that where a statute requires a standard to be "achievable," it must be achievable "under most adverse circumstances which can reasonably be expected to recur." Commenters again cite the Sierra Club vs. The EPA [167 F.3d 658, 665 (D.C. Cir. 1999)]"it is reasonable to suppose that if an emission standard is as stringent as `the emissions control that is achieved in practice" by a particular unit, then that particular unit will not violate the standard". In order to assure that an emission limit is set at a level the best performing sources can and do actually achieve, the EPA must assess the variability in emissions of that unit.
Comment 10: Commenter 18023 states that the EPA has not provided information as to how to implement operating limits at varying loads.
3. Emissions variability not accounted for.
Comment 11: Commenter 17904 states that the EPA must account for emissions variability over the range of unit performance in order to determine the level of performance actually achieved by the best performing units.
Comment 12: Commenter 17930 states that the actual HAP emissions from sources will vary over time and variability was not properly taken into account.
Comment 13: Commenter 18023 states that the EPA's proposed emission limits do not capture the long-term emission performance under all foreseeable operating conditions.
Comment 14: Commenter 17820 states that for EGUs sharing a common stack, emissions from one unit were automatically assigned to the other unit if test data were available from only one unit, which discounts any emissions variability between the unit.
4. MACT data set consists solely of full load steady-state testing.
Comment 15: Several commenters (18498, 18500, 19114) state that the EPA's proposed MACT limits rely on testing done at steady-state conditions. The EPA's proposed limits did not account for effects of variable operating load, variability in fuel constituents, emissions profiles and other variables. Emissions controls generally work best when operated on a relatively static basis. The EPA did not test or consider startup and shutdown conditions in setting proposed limits. The EPA can help alleviate some of the effect of variability on unit emissions, that was not accounted for in ICR testing, by allowing annual averaging although still achieving the same emission reductions. The snapshot nature of the performance tests means the results will provide little insight on true range of variability.
Response to Comments 1 - 15: The EPA understands that the ICR data were collected under full load and steady state conditions. Variability  -  including that attributed to load/operational variability, fuel variability, and other sources of variability  -  has been accounted for in the setting of the proposed and final emission limits. The method used to account for this variability was described in the preamble for the proposed rule. The method is consistent with methods used in other NESHAP rules that the EPA has promulgated. Additionally, the emission standard compliance is specified as being based on periodic stack tests, which will presumably be conducted under operating conditions similar to those during the ICR testing, or on a 30-day rolling average which provides an additional allowance of variability and will account for regular process and fuel variability over the averaging period.
The final rule includes operating limits only for the non-mercury metals and filterable PM emissions limits and only with the PM CPMS. One would expect that PM CPMS signals linked to PM concentrations would decrease under load conditions less than full load provided that control devices and processes are operated in a manner consistent with good air pollution practices as required for Part 63 sources. That is, we would expect that sources continue to operate control devices at levels consistent with those established during the most recent performance test even when operating at less than full load. If an operator is concerned about a change in fuel characteristics affecting a PM CPMS signal disproportionally to actual emissions, the rule certainly provides the opportunity for the source to conduct additional testing to re-verify or reset the PM CPMS operating limit. We believe that the final rule provides a much simplified approach to parametric monitoring that will provide flexibility that may not have been available in the proposal.
5. Opposition to 30-day average limit.
Comment 16: Commenter 17776 states that there will likely be complications with sorbent trap monitoring for Hg on a 30-day average. Because the Hg concentrations in stacks are likely to be at or just below the MACT limit, sorbent traps will need to remain in the stacks collecting Hg for possibly 10-14 days. This would result in two to three samples or data points being used in the 30-day average calculations. If one sample is rejected due to quality assurance and was unusable for the 30-day average, the remaining one or two sample points will bias the 30-day average.
Response to Comment 16: We recognize and agree with the commenter that sampling emissions at all times the process is operating is critical in obtaining representative measurements of emissions rates. We also agree that data quality certainty associated with any calculated value decreases with the collection of fewer data or missing operating periods such as would occur with extended periods of monitoring system downtime. The final version of Appendix A provides for the use of back-up monitoring when using sorbent trap Hg monitoring to provide data in the event of sorbent trap sampling or QA/QC failure relative to the primary monitoring system. In light of this potential for increased data quality uncertainty and given the provision in the rule that the source owner must report a deviation from the monitoring requirements for monitoring system failure during required data collection or otherwise excepted periods, we believe it prudent for the source owner to apply this option:
      "2.2 Primary and Backup Monitoring Systems. In the electronic monitoring plan described in section <IP_ADDRESS>.1 of this appendix, you must designate a primary Hg CEMS or sorbent trap monitoring system. The primary system must be used to report hourly Hg concentration values when the system is able to provide quality-assured data, i.e., when the system is "in control." However, to increase data availability in the event of a primary monitoring system outage, you may install, operate, maintain, and calibrate backup monitoring systems, as follows:
      2.2.1 Redundant Backup Systems. A redundant backup monitoring system may be either a separate Hg CEMS with its own probe, sample interface, and analyzer, or a separate sorbent trap monitoring system. A redundant backup system is one that is permanently installed at the unit or stack location, and is kept on "hot standby" in case the primary monitoring system is unable to provide quality-assured data. A redundant backup system must be represented as a unique monitoring system in the electronic monitoring plan. Each redundant backup monitoring system must be certified according to the applicable provisions in section 4 of this appendix and must meet the applicable on-going QA requirements in section 5 of this appendix."
Performance Specification 12B (PS 12B) allows another couple of provisions that can help assure collection of samples sufficient to determine compliance with the 30-day applicable limits. PS 12B provides for the use of some measured data even when the analyzer fails to meet some of the quality control requirements. There are means built into PS 12B that allow for adjusting data for leak check failures, failed paired trap agreement, disproportional sampling, and trap breakthrough. Further, the sorbent trap sampling and analysis measurements are sensitive enough not to require 7-day or longer sampling. These periods are merely suggestions to follow within the context of the rule. One can operate sorbent traps following PS 12B on much shorter sampling periods, even as short as a few hours, so as to collect more samples and reduce the effect of one or two failed samples during the 30-day averaging period.
6. Recommendations.
Comment 17: Commenter 17776 recommends MACT standards based on a 12-month rolling average emission rate rather than a 30-day averaging period. A 12-month rolling average will provide much needed operational flexibility and accommodate real-world operating conditions for EGUs.
Comment 18: Commenter 18023 recommends that the EPA revise the methodology for estimating variability prior to issuing a final rule. As stated in UARG's comments, which are endorsed by the commenter, a proper variability adjustment would result in a Hg MACT limit of at least 1.42 lb/TBtu and a filterable PM MACT limit in the range of 0.022 lb/MMBtu to 0.033 lb/MMBtu.
Response to Comments 17 - 18: We believe that a 30-day boiler operating day period provides flexibility sufficient for sources to operate processes and control devices to assure ongoing compliance and that the 30-day period provides for the level of environmental protection intended for this rule. The 30-day rolling average requires that the operator review and act on measurement data on at least a daily basis consistent with the enforcement and compliance provisions of the Act (e.g., CAA §113(d)). A rolling 12-month average would reduce that frequency to once per month. Variability  -  including that attributed to load/operational variability, fuel variability, and other sources of variability  -  has been accounted for in the setting of the proposed and final emission limits. The method used to account for this variability was described in the preamble for the proposed rule. The method is consistent with methods used in other NESHAP rules that EPA has promulgated.
4A06 - MACT Floor Methodology: Fuel analysis variability
Commenters: 16849, 17254, 17621, 17696, 17711, 17716, 17725, 17739, 17807, 17808, 17813, 17914, 17925, 17930, 17975, 18024, 18498, 18963, 19114, 8443, 19536/19537/19538, 18023
Comment 1: Commenter 16849 recommends the adjustment of the calculated floor by a statistical method that allows for the variability in total fuel-borne HAP input, sampling and analysis methods, and variability resulting from site-to site differences for all units as compared to the best performing units and disregarding any truncated number seen as statistically insignificant. The commenter recommends the EPA's use of the research included in the white paper published by EPRI titled, "Data Quality Evaluation of Hazardous Air Pollutants Measurements for the U.S. Environmental Protection Agency's Electric Utility Steam Generating Units Information Collection Request." Commenter suggests as an example the EPA could consider is the 12-month rolling average as is currently prescribed by the Illinois Hg rule.
Comment 2: Multiple commenters (8443, 17621, 17696, 17716, 17739, 17725, 17813, 18498, 18023) state that the EPA's methodology does not adequately address fuel variability. The proposed emissions standards should adequately account for fuel-related variability for fuel-based pollutants because it is likely the most significant contributor to overall variability particularly for units firing a multitude of fuel types. There does not appear to be any attempt to address fuel variability here, though the IB MACT Rule did acknowledge the need for such consideration. Failing to account for the impact of fuel variability could lead to anomalous situations where a unit might be categorized as a "top performer" simply due to the happenstance of the fuel burned during the day of testing. Trace fuel impurities (e.g., metals, chlorine) that reflect natural characteristics of the fuel (coal or oil) can vary from deposit to deposit or even within seams. Sources may obtain fuels from a single or several sources. The potential caprice of trace HAP concentrations for oil or petroleum coke sources is even greater due to changing crude supplies at the refinery, which change the trace elements in its product.
Commenters state that establishing a limit that is based solely on the fuel burned during a single test could also result in a limit that has very little to do with the underlying performance of the source(s). For example, a unit with sub-par emission controls that burned a fuel on the test day that was low in trace metals might nonetheless be included in the floor analysis, despite otherwise falling outside the range of units that should be included in setting floor standards. See A Legislative History of the Clean Air Act Vol. II, p. 2897 (Rep. Collins) (floor should establish a "minimum degree of control in relation to the control technologies that have already been attained by the best existing sources"). The wide availability of fuel sources for EGUs distinguishes this situation from the Cement Kiln or National Lime cases where it was not economically feasible to change their limestone source, precluding such changes from consideration as part of the "worst reasonably foreseeable circumstances" that should be reflected in the floor analysis. Fuel variability and changes are reasonable expected occurrences for coal- and oil-fired units; such "reasonably foreseeable circumstances" must be accounted for when creating standards. Commenter 17725 adds that by not making allowances for such "reasonably foreseeable circumstances," the limits would be arbitrary and the EPA would be creating standards that are beyond-the-floor, which would require additional justification.
Comment 3: Commenter 17725 adds that it would be inappropriate to suggest that a unit with no emission controls should be considered a top performer because it happened to burn fuel with a lower pollutant concentration during the test. It is possible that this same unit might burn a fuel with a lower pollutant concentration the very next day. This approach would suggest that all EGUs purchase their fuel from the same single source, which obviously undermines the benefits of maintaining robust and diverse coal and oil supplies.
Comment 4: Commenters 17621 and 18024 state that the tests (undertaken for the ICR) do not characterize stack emissions over an extended period, when burning different coals as facilities often burn coals from multiple sources. Based on ICR data, no liquid oil-fired boiler could ever comply with the proposed standards based on fuel analysis for fuel HAP content because the ICR shows reductions in HAP between the fuel and stack emission data. Either MACT emission limits should be increased to allow for a viable fuel monitoring option, or the EPA should provide a divisor (percent factor) to equate fuel and stack HAP concentrations as equally stringent compliance alternatives.
Comment 5: Commenter 8443 adds that the presentation material provided by the EPA does not provide a detailed answer how the EPA plans to modify the stack emissions reported during the ICR to account for all these sources of variability. It simply notes that the EPA used a UPL of 99% in other MACT rulemakings without explaining how it would apply a UPL to the specific facts of the EGU MACT rule. The commenter states they cannot provide meaningful comments on the EPA's variability adjustments without more detailed information from the EPA. What remains essential is that the EPA properly and fully accounts for variability in setting MACT limits when proposing any rule.
Comment 6: Commenter 17739 notes that, in the Boiler MACT, the EPA addressed fuel variability as part of its acknowledged obligation to "account for sources' variability in assessing sources' performance when developing technology-based standards." 76 FR 15627. It did so there through a "fuel variability factor." Here, the EPA has made no attempt to address fuel variability at all, nor explained why it is rational not to do so. HAP emission rates from coal units, floor units or otherwise, are greatly impacted by the elemental composition of the fuel burned at a particular unit. Although fuel variability is significant between coal ranks, there is also variability within coal ranks, with the maximum content reported for arsenic and manganese in bituminous coal reported to be over 70 times greater than their average contents for that coal rank. (Based on data in the US Geological Survey COALQUAL database, V. 2.0, http://energy.er.usgs.gov/products/databases/CoalQual/index.htm .Ibid) Since floor units burning a given rank of coal can be expected to experience the significant impacts of fuel variability within a given coal rank, the EPA is obligated to account for this source of variability. (For example, the average bituminous coal contains about 30 ppm arsenic, whereas the average subbituminous coal contains about 5 ppm, based on data in the US Geological Survey COALQUAL database, V. 2.0, http://energy.er.usgs.gov/products/databases/CoalQual/index.htm . Similarly, the average bituminous coal has 9 times the average chlorine content, as the average subbituminous coal. On the other hand, subbituminous coals tend to have much higher concentrations of manganese.)
Comment 7: Several commenters (17716, 17725, 18498, 18023, 18014) believe that the fuel-related variability should be treated here using an approach similar to one the Agency used in the final IB MACT Rule. Westar recommends that the fuel variability factors ("FVF") for the individual units should be calculated based on a fuel pollutant concentration measured during the emissions test and some reasonable maximum fuel concentration derived from the entire pool of the units in the emissions floor. Specifically, the following procedure should be adopted for developing and implementing adjustment for fuel-related variability:
      1) Conduct the analysis using the average fuel concentration data (lb/MMBtu) for each source within the best performing 12 percent of sources that reported fuel analysis data in conjunction with the ICR tests;
      2) Exclude average fuel concentration data outliers using a three screening approach to exclude inordinately high (or low) fuel analysis results from influencing the FVF value;
      3) Select the 95th percentile value as the representative "maximum" fuel concentration;
      4) For each source not excluded by the three screening, calculate the ratio of the "maximum" fuel concentration to the average fuel analysis value from the ICR test;
      5) Calculate the FVF as the average of the ratios for all units;
      6) Use the FVF to assess whether new and existing unit UPLs fully reflect the fuel variability.
Despite the UPL value accounting for some fuel-related variability, the above suggested approach addresses what the average impact from all floor units burning the representative maximum fuel. This can be done by comparing the result of multiplying the average emissions for the floor by the FVF to the UPL value. A FVF adjusted average greater than the UPL shows the UPL does not adequately consider fuel variability. In such cases, the UPL would be replaced with the FVF adjusted value. A UPL value greater than FVF would adequately address the variability, and no adjustment is necessary. As shown on attached Table 7 [17739-A1_Table7Page78.doc], fuel related variability may be reasonably addressed in UPL values for filterable PM and Hg, but additional fuel adjustments are warranted for total metals and HCl.
Comment 8: Commenters 17725 and 18498 add to this exercise above by saying that RMB performed an independent floor analysis following the UPL procedure changes recommended in the comments using ICR test run data obtained via the Microsoft Access database that the EPA posted to its Air Toxics Standards for Utilities webpage. The results suggest that fuel related variability may be reasonably addressed in UPL values for filterable PM and Hg (if properly done with the top 131 units represented in the ICR test pool) but additional fuel adjustments are warranted for total metals and HCl. It is important to state that the recommended approach for handling fuel variability is not inconsistent with section 112(d) or court decisions (e.g., Brick MACT, Cement Kiln MACT, or National Lime decisions).