MEMORANDUM 
SUBJECT:
The Impact of Emissions Averaging Time on the Stringency of an Emission Standard

FROM:
Stephen Boone, Roy Neulicht, and Jeff Cole,  RTI
TO:
Bill Maxwell, EPA, SPPD, Energy Strategies Group
DATE:
December 9, 2011

Purpose
These analyses were conducted on the Part II CEMS data to evaluate the impact of averaging time on variability and to "predict" the UPL value for different averaging times for the MACT floor facilities. This predictive tool has not been previously used and is intended to "ground truth" the variability estimated by the UPL calculation methodology.  These analyses are not the result of additional statistical analyses of the stack testing data collected under Part II or any data received under Part III, directly.
Note: These results have not been through an extensive QA.
 General Approach
1. Part II data from 87 units were evaluated for data completeness and hours flagged as invalid were removed prior to conducting any calculations.
2. For each unit, each hour of data was evaluated to determine the operating load (gross MW) and to determine if zero emissions were reported for the hour. Hours of zero reported emissions were excluded from the calculation of daily averages. 
3. Hours were classified as startup or shutdown periods if the gross megawatts recorded for the hour were less than 5 percent of the maximum hourly generating rate recorded in the data set.  These hours were not included in the calculation of daily averages. Daily averages were calculated in accordance with Equation 19-19 from Method 19.
4. Contiguous six-hour periods of valid CEMS data at operating conditions equivalent to typical stack testing conditions (i.e., steady-state flow rate and steady load at greater than 90 percent of the maximum recorded operating load) were used to calculate all the short-term emission rate averages occurring in the data set that were analogous to short-term stack test averages; these periods are referred to as "surrogate stack tests" in this memo.
5. All averaging periods calculated (30-day, 60-day, 90-day, 180-day, and 360-day) excluded startup and shutdown periods. 
6. For each averaging period analyzed, the variability ratio of [the 99[th] percentile long-term average] to [the 3[rd] percentile surrogate stack test value] was calculated for each operating unit with a sufficient number of hourly records to calculate at least one long-term period. These percentiles were used to eliminate outliers in the data sets.
7. The variability ratios for all units within a given averaging period data set were used to develop a general equation defining the relationship between the 99th percentile long-term average and the near-minimum achieved surrogate stack test. The general form of the equation is presented as Equation 1:
      [Equation 1]		y = Cx[-z]
                  
                  Where 	y  =  the estimated long term emissions average 
                  	x  =  the near-minimum short-term emissions average
                  	z  =  was a calculated exponent derived from all available CEMS hourly data.
                  	C =  was a calculated coefficient derived from all available CEMS hourly data.
8. For each averaging period analyzed, the general equation, developed in step 6, was used to transform short-term emissions data for each unit floor into an estimate of the 99[th] percentile long-term performance for the floor unit. The transformed estimates were calculated by inserting the minimum actual stack test data from each of the 47 units into the general equation from step 6. Appendix A of this memorandum only includes the two plots utilized to determine the equation for transforming MACT floor stack test averages to 30-day averages. The attached spreadsheets contain the plots of all other averaging periods.
9. The upper predictive limit for each long-term average Hg emissions rate was calculated for the floor units using the equation from step 6. Only the minimum test value (i.e., row 5 in the UPL spreadsheet) was used; all other stack test rows previously used to determine unit-specific variability were excluded.
Conclusion
Table 1 presents the results of the analysis of what the Hg MACT floor for existing coal units would look like if EPA decides to promulgate a compliance period longer than 30 days. As shown in Table 1, the amount of data available for each averaging period analysis varied. For example, only 23 units had sufficient data to calculate at least one 360-day average. Since the objective of this analysis was to compare achievable emissions rates based on the duration of the averaging period, the analysis used only the 23 units with sufficient data to calculate all averaging periods as a "control" to assess the impact of comparing the different data sets.

            Table 1  -  UPL's Calculated with All Available Data
                                Average Period
                                Available CEMS
                                Calculated UPL
                                    (days)
                                   Data Sets
                         With All Available CEMS Data
                                 (lb Hg/MMBtu)
                                      30
                                      87
                                   1.11E-06
                                      60
                                      83
                                   1.01E-06
                                      90
                                      77
                                   9.13E-07
                                      180
                                      66
                                   8.04E-07
                                      360
                                      23
                                   7.60E-07

To quantify the effect of the reduction in the count of available datasets with sufficient data as the averaging periods increase, the analysis also includes a series of UPL calculations using only the "control" data set. Table 2 presents a comparison of the calculated UPLs for each averaging period without the analytical artifacts caused by the limited availability of very long-term (i.e., semi-annual and annual) CEMS data.

       Table 2  -  UPL's Calculated with Control Data (23 Units Only)
                                Average Period
                                Available CEMS
                                Calculated UPL
                                    (days)
                                   Data Sets
                            With Control CEMS Data
                                 (lb Hg/MMBtu)
                                      30
                                      23
                                   1.32E-06
                                      60
                                      23
                                   1.13E-06
                                      90
                                      23
                                   1.03E-06
                                      180
                                      23
                                   9.17E-07
                                      360
                                      23
                                   7.60E-07

The data in Table 2 confirms that an appropriate ratio between a 30-day compliance period and a 360-day compliance period is approximately 60 percent. This is consistent with the ratio achieved by San Juan Unit 4 based on the maximum averages recorded by CEMS with no statistical variability added.


                                       
              Figure 1.-San Juan Unit 4 Actual CEMS Data Averages
                                       
                                       
                                       
                                       
                                  Appendix A
              Typical Data Sets Used to Derive Average Data Sets
                                       
                                       
                                       
