1

TECHNICAL MEMORANDUM

TO: Tina Ndoh , U

. S

. EPA/OAQPS/SPPD

- Minerals and Manufacturing Group

FROM: Eastern Research Group, Inc.

DATE: May 30 , 2014

SUBJECT: Maximum Achievable Control Technology (MACT) Floor Analysis for

Phosphate Rock Calciners at Phosphoric Acid Manufacturing Plants

1.0 INTRODUCTION
This memorandum presents the methodology and results of the maximum achievable control technology (MACT) floor d eterminations for mercury (Hg) and hydrogen fluoride ( H F) for phosphate rock calciners in the phosphoric acid manufacturing plants (40 CFR part 63, subpart AA) source category. The organization of this memo is as follows:

2.0 Summary of Existing Limits

3.0 Background of MACT Floor Methodology

4.0 MACT Floor Determination Methodology

5.0 References Appendix A: Excel File “MACT_Floor_Calculations_for_Calciners.xlsx.”

2.0 SUMMARY OF EXISTING LIMITS
The existing National Emissions Standard for Hazardous Air Pollutants (NESH AP) for phosphate rock calciners in the phosphoric acid manufacturing plants source category (40 CFR Part 63, subpart AA) established emission limits for particulate matter (as a surrogate for hazardous air pollutant (HAP) metals). Table 2

- 1 summarizes thi s emission limit.

Table 2

- 1

. Existing Emissions Limits for Particulate Matter from Phosphoric Acid

Manufacturing Plants under 40 CFR Part 63, Subpart AA

Equipment Description Particulate Matter (gr/dscf) Existing Sources New Sources Phosphate rock calciner 0.080 0.040 gr/dscf

– grains per dry standard cubic foot2

3.0 BACKGROUND OF MACT F LOOR METHODOLOGY
Section 112(d) of the CAA requires EPA to set emissions standards for HAP emitted by major stationary sources based on performance of the MACT. The MACT standar ds for existing sources must be at least as stringent as the average emissions limitation achieved by the best performing 12 percent of existing sources (for which the Administrator has emissions information) or the five best performing sources for source categories or subcategories with less than 30 sources (CAA section 112(d)(3)(A) and (B)). This minimum level of stringency is called the MACT floor. For new sources, MACT standards must be at least as stringent as the control level achieved in practice by the best controlled similar source (CAA section 112(d)(3))

. These requirements constitute the MACT floo r for new and existing sources. EPA may not consider costs or other impacts in determini ng the MACT floors. EPA must consider cost, non

- air q uality health and environmental impacts, and energy requirements in connection with any standards that are more stringent than the MACT floor (beyond

- the

- floor (BTF) controls).
MACT analyses generally involve an assessment of the emissions from the best performing units in a source category or subcategory . The assessment can be based on actual emissions data, knowledge of the air pollution control in place in combination with actual emissions data, or state and Federal regulatory requirements that may ena ble EPA to estimate the actual performance of the regulated units and other relevant emissions information. For each source category or subcategory , the assessment involves a review of actual emissions data with an appropriate accounting for emissions vari ability. Other methods of estimating emissions can be used provided that the methods can be shown to provide reasonable estimates of the actual emissions perfo rmance of a source or sources. In March 2007, the District of Columbia Circuit Court issued an op inion ( Sierra Club v. EPA

, 479 F.3d 875 (D.C. Cir. 2007) ( Brick MACT )) vacating and remanding CAA section 112(d) MACT standards for the Brick and Structural Clay Ceramics source categories. Some key holdings in that case were:

 MACT floors for existing sour ces must reflect the average emission limitation achieved by the best performing 12 percent of existing sources, not levels EPA considers to be achievable by all sources (479 F.3d at 880

– 81);

 EPA cannot set floors of “no control.” The Court reiterated its prior holdings, including National Lime Association v. EPA , 233 F.3d 625 (D.C. Cir. 2000), confirming that EPA must set floor standards for all HAP emitted by the major source, including those HAP that are not controlled by at

- the

- stack control devices (47 9 F.3d at 883); and

EPA cannot ignore non

- technology factors that reduce HAP emissions, including when determining which sources are best performers for purposes of ascertaining the MACT floor. Specifically, the Court held that “EPA’s decision to base floo rs exclusively on technology even though non

- technology factors affect emissions violates the Act.” (479 F.3d at 883).
In addition, the fact that a specific level of performance is not being intentionally achieved by the source is not a legal basis for exc luding the source’s performance from consideration. Sierra Club v. EPA , 479 F.3d at 631

- 34; National Lime Association (NLA)

, 233 F.3d at 640.3

The Brick MACT decision also stated that EPA may account for variability in setting floors. However, the C ourt fou nd that EPA erred in assessing variability

, because it relied on data from the worst performers to estimate best performers’ variability, and held that “ EPA may
not use emission levels of the worst performers to estimate variability of the best performers without a demonstrated relationship between the two ” ( 479 F.3d at 882 ).
EPA incorporated these decisions into the MACT floor analysis for phosphoric acid manufacturing plants

. Incorporating Variability
In determining the MACT floor for existing sources, EPA may exercise its judgment, based on an evaluation of the relevant factors and available data, to determine the level of performance that has been achieved by the average of the best

- performing five so urces under variable conditions. The Court has recognized that EPA may consider variability in estimating the degree of emissions reduction achieved by best

- performing sources and in setting MACT floors (see Mossville Envt’l Action Now v. EPA, 370 F.3d 123 2, (D.C. Cir. 2004)), holding EPA may consider emission variability in estimating performance achieved by best

- performing sources and may set the floor at a level that best

- performing sources can expect to meet “every day and under all operating conditions .”
The MACT and other technology

- based standards are often derived from short

- term emissions test data, but such data may not be representative of the range of operating conditions that the best performing facilities face on a day

- to

- day basis. In statisti cal terms, each test produces a limited data sample, not a complete enumeration of the available data for performance of the unit over a long period of time. 1 EPA, therefore, may adjust the short

- term data to account for these varying conditions. The types of variability that EPA attempts to account for include operational distinctions between and within tests at the same unit.

“Between

- test variability” can occur even where conditions appear to be the same when two or more tests are conducted. Variations i n emissions may be caused by differences in operating conditions, settings for emissions testing equipment, field teams conducting the testing, sample handling or laboratories analyzing the results. Identifying an achieved emission level for best performin g sources often needs to account for these differences between tests, in order for “a uniform standard [to] be capable of being met under most adverse conditions which can reasonably be expected to recur[.]” (See NLA I, 627 F.2d at 431, n. 46.) (See also P ortland Cement Ass’n, 486 F.2d at 396 noting industry point that “a single test offered a weak basis” for inferring that plants could meet the standards.)
The same types of differences leading to between

- test variability can also cause variations in result s between various runs comprising a single test, or “within

- test variability.” A single emissions test at a unit usually includes at least three separate test runs. (See 40 CFR 63.7(e)(3) for MACT standards under CAA section 112.) Each data point should be viewed as a snapshot of actual performance. Along with an understanding of the factors that may affect performance, each of these snapshots gives information about the normal, and unavoidable, variation in emissions that would be expected to recur over ti me.4

V ariability can be accounted for using different statistical methods. For example, recent rules have used confidence intervals, prediction intervals, and percentiles to determine MACT floor emission limits

. A confidence interval represents the interva l within which the true population mean (not the sample mean) would fall at the specified confidence level. Assume that you calculated a 95 percent confidence interval for the mean of your sample data. If you were to obtain additional samples from the same population, in 95 percent of such cases the calculated interval will include the true population mean. A confidence interval is a descriptive interval.
A prediction interval for a single future observation is an interval (with upper and lower prediction l imits, i.e., UPL and LPL, respectively) that will, with a specified degree of confidence, contain the next (or some other pre

- specified) randomly selected observation from a population. In other words, the prediction interval estimates what future values w ill be, based on present or past background samples taken

. Percentiles are straightforward and are also descriptive. They represent the specified “slice” of the sample data. Unlike confidence and prediction intervals, they are distribution

- free (i.e., to c ompute a confidence/prediction interval, you need to ascertain that the data follow a specific distribution, such as the normal distribution but to compute a percentile you do not need to make that kind of a determination).

Percentiles are based on the dis tribution of the available emission observations (e.g., test runs), and do not embody a predictive aspect that a prediction interval does. T he UPL represents the value the mean of future test run observations can be expected to fall below, based on the

res ults of the independent sample of size (n) from the same population. Therefore, should a future test condition be selected randomly from any of these sources ( e.g. , average of three runs),

one can be confident (99 percent confident in the case of a 99 perc ent UPL) that the reported level will fall below a MACT floor emission limit calculated using a UPL

. The UPL is the appropriate statistical tool to use to account for variability in the concentration data from phosphoric acid manufacturing plants. For the se emission points, where there is a limited sampling of the source category and EPA does not have test data from all of the emission points for a pollutant in the in the subcategory, the predictive aspect of the UPL calculation is especially important.

4.0 M ACT FLOOR DETERMINAT ION METHODOLOGY FOR PHOSPHATE ROCK CALCINERS The following sections describe the methodology used to calculate MACT floors for HF and total Hg for phosphate rock calciners in phosphoric acid manufacturing plants.
Only one facility curre ntly operates phosphate rock calciners; PCS Aurora. In response to an April 2010 CAA section 114 request, PCS Aurora provided Hg (by US EPA Method 30B) emissions testing results for one of the six calciners to the EPA. The facility provided HF emissions te sting results (by US EPA Method 320) for the same calciner in response to a January 2014 CAA section 114 request. In addition, the facility provided Hg emissions testing results (by US EPA Method 30B) for another, previously untested calciner also in respo nse to the January5

2014 CAA section 114. For additional information, refer to the separate memorandum entitled “Information Collection and Additional Data Received for the Phosphoric Acid and Phosphate Fertilizer Production Source Categories 2 ,” available i n the docket for this action.
As previously stated, the EPA received HF emissions testing results by US EPA Method 320 for one phosphate rock calciner in response to the January 2014 CAA section 114 request. Of the six test runs reported to EPA, four were reported as below the method detection limit. The detected concentrations were, on average, only 20 percent above the method detection limit. The expected measurement imprecision for an emissions value occurring at or near the method detection limit is abo ut 40 to 50 percent. Because the HF emission levels are near or below the method detection limit, the measured concentration values are questionable for HF. As a result, the true levels of HF emitted from phosphate rock calciners are uncertain.

CAA section 112(h)(1) states that the Administrator may prescribe a work practice standard or other requirements, consistent with the provisions of CAA sections 112(d) or (f), in those cases where, in the judgment of the Administrator, it is not feasible to enforce a n emission standard. CAA section 112(h)(2)(B) further defines the term “not feasible” in this context to apply when “the application of measurement technology to a particular class of sources is not practicable due to technological and economic limitations .”
Because approximately 67 percent of the HF data collected using US EPA Method 320 were below the method detection limit, and the fact that the detected concentrations were, on average, only 20 percent above the method detection limit, it was concluded t hat HF emissions from phosphate rock calciners cannot practicably be measured. As a result, work practice standards were identified in place of numeric emission limits for HF from phosphate rock calciners.
According to information provided by PCS Aurora 3

, phosphate rock calciners are operated to remove organic content from the phosphate rock in efforts to produce products with low organic content. Based on review of available literature, removal of fluorine takes place at temperatures between approximately 2,500 and 2,750 degrees Fahrenheit (in addition to adding defluorinating agents), whereas removal of organic matter and dissociation of carbonates is typically carried out between 1,200 and 1,830 degrees Fahrenheit. 4 Process flow diagrams submitted by PCS Aurora in response to the April 2010 and January 2014 CAA section 114 requests indicate that the phosphate rock calciners currently in operation maintain a calcination temperature of less than 1,600 degrees Fahrenheit. Based on this information, maintaini ng the temperature of the phosphate rock calciner fluidized bed at less than 1,600 degrees Fahrenheit will minimize emission s of HF.
In addition, based on process flow diagrams submitted by PCS in response to the April 2010 and January 2014 section 114 req uests, particulate emissions from the calciners currently in operation are controlled using a combination of an absorber (i.e., a venturi type wet scrubbing system) and an electrostatic precipitator. A PCS facility representative confirmed that the venturi scrubbers operate whenever the calciners are in operation. 5 As discussed in a separate memorandum, 6 other facilities in the phosphoric acid source category use venturi scrubbers to control HF emissions from various processes located at the source category . Because hydrogen fluoride is highly soluble in water, if hydrogen fluoride is present in the calcination exhaust6

stream in any amount, it is expected that the absorbers currently in operation are achieving some level of emission reduction. Based on this information, routing emissions from phosphate rock calciners to an absorber was identified as a work practice standard for HF from phosphate rock calciners.
For Hg, we calculated MACT floors for phosphate rock calciners after evaluating the variability in the concentration data reported by PCS Aurora. Hg emissions data were available for two phosphate rock calciners, see Table 4

- 1 for the average Hg concentration for each. Calciner Hg emissions are the result of Hg contained in the fuel and raw materials

. Because the six phosphate rock calciners are designed to be identical and use the same raw materials and fuels, Hg emissions from the six calciners are expected to be identical. Therefore, all Hg data from the calciners were combined into one dataset to de termine both new and existing MACT floors.

Table 4

- 1. Average Concentration of Mercury from Phosphate Rock Calciners (as

Measured by US EPA Method 30B)

Rank Facility and Process

Line Average Hg Concentration

(mg/dscm @ 3% O 2 ) 1 PCS Aurora (202) 9.87E

- 02 2 PCS Aurora (203) 9.92E

- 02 mg/dscm @ 3% O 2 – milligrams per dry standard cubic meter corrected to 3 percent oxygen Hg

- mercury

I ncorporating Data Variability

As discussed in Section 2.0, the UPL was used for the MACT floor variability analysis. The first step included a determination of whether the data from the sources were normally or log

- normally distributed. If the data were normally distributed (e.g., similar to a typical bell curve), further variability analyses were conducted on the data set. If the data were no t normally distributed (for example

, if the data were asymmetric or skewed to the right or left), the type of distribution (e.g., log

- normal) was determined and a data transformation (e.g., taking the natural log of the data) was performed to normalize the data prior to conducting the variability analysis

. T wo statistical measures, skewness and kurtosis, were examined to determine if the data were normally or log

- normally distributed.
The skewness statistic (S) characterizes the degree of asymmetry of a gi ven data distribution

. Normally distributed data have a skewness of zero. A n S value that is greater (less) than zero indicates that the data are asymmetrically distributed with a right (left) tail extending toward positive (negative) values

. Further, the standard error of the skewness statistic (SES) is given by Equation 1:

(Eq. 1)

W here :
N = the sample size7

According to the small sample s kewness hypothesis test, if S is greater than twice the SES, the data distribution can be considered non

- nor mal.
The kurtosis statistic (K) characterizes the degree of peakedness or flatness of a given data distribution in comparison to a normal distribution

. Normally distributed data have a kurtosis of zero. A K value that is greater (less) than zero indicates a relatively peaked (flat) distribution

. Further, the standard error of the kurtosis statistic (SEK) is given by Equation 2:

(Eq. 2)

Where:

N = the sample size According to the small sample kurtosis hypothesis test, if K is greater than twice the SEK, the data distribution is typically considered to be non

- normal.

S kewness and kurtosis hypothesis tests were applied to both the reported test values and the lognormal values of the reported test values for Hg. T he S and K statistics of the report ed data set were both less than twice the SES and SEK, respectively, and as a result, the data set were classified as normally distributed

. After determining the distribution of each data set , a student’s t­test statistic was determined to calculate the U PL value. The t

- test was used in the promulgated hospital and medical waste incineration (HMWI) rulemaking and proposed Portland Cement rulemaking, and it is more appropriate for smaller sample sizes . The t

- statistic can be found in standard statistical

re ference tables or by using the Excel function “TINV,” each requiring the degrees of freedom and the desired confidence interval. The degrees of freedom was calculated as one less than the number of test runs and the confidence interval used was 99 percent.
Following the determination of the student’s t

- test statistic, the 99 percent UPL values for Hg were calculated using the test run data . Equation 3 was used to calculate the UPL for a MACT floor emission limit for which compliance is based on the average of a three

- run test:

(Eq. 3 )

Where:

n = the number of test runs (i.e., sample size)

m = the number of test runs in the compliance average (m

- value), 3.

s = standard deviation of the emission test data

= mean, i.e., average of the emission test da ta

t (0.99, n

– 1) = t

- statistic for 99% significance and a sample size of n8

The 99 percent UPL represents the value which one can expect the mean of future three

run performance tests to fall below with 99 percent confidence, based upon the results of the independent sample of observations from the same sources. There were no non

- detect values for the Hg test data from the phosphate rock calciners. However, imprec ision due to potential non

detect values was investigated after determining the 99 percent UPL values.

Use of Non

- Detect Values
At very low emission levels where emission tests resulted in ND values, the inherent imprecision in the pollutant measurement m ethod has a large influence on the reliability of the data underlying the regulatory floor emission limit. Because of sample and emission matrix effects, laboratory techniques, sample size and other factors, method detection levels normally vary from test to test for any specific test method and pollutant measurement. The confidence level that a value measured at the detection level is greater than zero is about 99 percent . The expected measurement imprecision for an emission value occurring at or near the method detection level is about 40 to 50 percent. Pollutant measurement imprecision decreases to a consistent level of 10 to 20 percent for values measured at a level about three times the method detection level.
The procedure for determining a representa tive detection limit (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.). Fro m that combined pool of dat a, the arithmetic mean value is calculated . By limiting the dataset to those tests used to establish the floor or emissions limit ( i.e. , best performers), the result is representative of the best

- performing testing companies and laboratories using the most sensitive analytical procedures. T he 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 deter mining the minimum value for reporting was other than the detection level). T he resulting mean of the method detection levels is designated as the RDL as characteristic of accepted source emissions measurement performance.
The second step in the process i s to calculate three times the RDL to compare with the calculated floor or emissions limit. T he multiplication factor of three is used to reduce the imprecision of the analytical method until the imprecision in the field sampling reflects the relative meth od precision as estimated by the Reference Method Accuracy and Precision (ReMAP) study. 7 That study indicates that such relative imprecision remains a constant 10 to 20 percent, over the range of the method. For assessing the calculated floor results rela tive to measurement method capabilities, if three times the RDL were less than the calculated floor or emissions limit ( e.g. , calculated from the UPL), it would be determined that measurement variability was adequately addressed. The calculated floor or em issions limit would need no adjustment. If, on the other hand, the value equal to three times the RDL were greater than the UPL, it would be conclude d that the calculated floor or emissions limit does not account entirely for measurement variability. Where such was the case, the value equal to three times the RDL would be substituted 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, which is sim ilar to other EPA test methods and the results found in the ASME ReMAP study.9

We used a procedure similar to the one discussed above to calculate the three times RDL value for Hg measured by US EPA Method 30B. Facilities submitted US EPA Method 30B

concen tration data (including non

- detect values) in response to the April 13, 2010 section 114 request and PCS Aurora submitted additional US EPA Method 30B concentration data in response to the January 24, 2014 section 114 request. The Hg concentration data inc luded testing from phosphate rock calciners and dryers, WPPA, SPA, and phosphate fertilizers process lines. First, we identified the method detection levels reporting by the best performing units. We then treated the average of the method detection levels as the RDL value for Hg. We calculated three times the RDL value and corrected the resulting concentration to a three percent oxygen basis for use in the phosphate rock calciner MACT floor variability calculation.
Results of the variability analyses of Hg emissions dat a from calciners are presented in Table 4

- 2

. As is discussed in a separate BTF Analysis memorandum, 8 more stringent BTF limits are being proposed for Hg at phosphate rock calciners. Therefore, the proposed limits for Hg from phosphate rock calciners are not equal to the calculated MACT limit s but rather the BTF limits. The BTF limit s w ere determined by estimating the emissions which would be achievable using a Hg control device (e.g., fixed

- bed carbon adsorption or activated carbon injection) at phosphate rock calciners. Based on the available data, it was determined that 90 percent Hg reduction is achievable. Therefore, the proposed BTF limits for Hg, as seen in Table 4

- 2 , are 10 percent of the calculated MACT limits.

Table 4

- 2

. MACT Floor , Variabili ty Analysis Results , and BTF Limits for Mercury (by US EPA Method 30B)

– Phosphate Rock Calciner

Parameter Value Sample Size 12 Non

- Detects 0 Average (mg/dscm @ 3% O 2 ) 9.88E

- 02 Median (mg/dscm @ 3% O 2 ) 1.020E

- 01 Standard Deviation (mg/dscm @ 3% O 2 ) 2.33E

- 02 Minimum (mg/dscm @ 3% O 2 ) 5.83E

- 02 Maximum (mg/dscm @ 3% O 2 ) 1.42E

- 01 Skewness

- 1.01E

- 02 SE Skewness 7.07E

- 01 Skewness Test Normal Kurtosis 1.26E

- 01 SE Kurtosis 1.41 Kurtosis Test Normal 99.0% t

- statistic for UPL 2.72 99.0% UPL (mg/dscm @ 3% O 2 ) 1.40E

- 01 Detection Limit Analysis Average (mg/dscm @ 3% O 2 ) 9.88E

- 02 RDL (mg/dscm @ 3% O 2 ) 1.90E

- 03 3x RDL (mg/dscm @ 3% O 2 ) 5.71E

- 03 Calculated MACT Floor Emission Limit for Hg [1] (mg/dscm @ 3% O 2 ) 1.40E

- 01 Proposed Beyond

- the

- Floor Limit for Hg (mg/dscm @ 3% O 2 ) 1.40E

- 0210

[1]

- MACT floor limits were rounded up to two significant figures (e.g., 100.1 would be rounded to 110). SE

– s tandard error (applied to skewness or kurtosis) mg/dscm @ 3% O 2 – milligrams per dry standard cubic meter corrected to 3 percent oxygen UPL

- u pper prediction limit RDL

– r epresentative detection limit

5.0 REFERENCES

1. Natrella, Experimental Statistics, National Bureau of Standards Handbook 91, Chapter 1 revised ed., 1966.

2. Eastern Research Group, Inc. “Information Collection and Additional Data Received fo r the Phosphoric Acid and Phosphate Fertilizer Production Source Categories.” Docket ID: EPA

- HQ

- OAR

- 2012

- 0522

. May 2014.

3. Eastern Research Group, Inc. “Summary of August 14, 2012 US EPA Meeting with PCS Phosphate.” Docket ID: EPA

- HQ

- OAR

- 2012

- 0522. August 1 4, 2012.

4. Abouzeid, A. M. “Physical and thermal treatment of phosphate ores

– An overview,” International Journal of Mineral Processing, 85 (2008) 59

- 84.

5. Eastern Research Group, Inc. “ Summary of May 19, 2014 Telephone Communication between PCS Phosphate and ERG .” Docket ID: EPA

- HQ

- OAR

- 2012

- 0522. May 19, 2014

6. Eastern Research Group, Inc. “Beyond

- the

- Floor Analysis for Phosphate Rock Calciners at Phosphoric Acid Manufacturing Plants.” Docket ID: EPA

- HQ

- OAR

- 2012

- 0522. May 2014.

7. “Reference Method Accuracy and P recision (ReMAP): Phase 1, Precision of Manual Stack Emission Measurements” American Society of Mechanical Engineers, Research Committee on Industrial and Municipal Waste. February 2001.

8. Eastern Research Group, Inc. “ Beyond

- the

- Floor Analysis for Phosphat e Rock Calciners
at Phosphoric Acid Manufacturing Plants

. ” Docket ID: EPA

- HQ

- OAR

- 2012

- 0522 . May 2014

.