MACT Existing UPL for Mercury Using Pooled Variance, Corrected for Temporal Autocorrelation with Intraquarry Variability - 

Runs Kiln ID 1248 Kiln ID 1259 Kiln ID 1286

1 18.88 27.01

2 15.77 28.73

3 20.71 28.67

4 22.61 27.95

5 19.67 7.66

6 25.90 7.49

7 22.63 7.58

8 21.21 8.12

9 5.07 23.93

10 44.96 22.61

11 34.37 23.06

12 13.46 24.21

13 11.57 25.25

14 13.90 21.47

15 27.43 25.53

16 25.55 25.89

17 21.95 29.34

18 12.10 26.03

19 12.83 7.60

20 9.18 24.26

21 8.74 23.68

22 17.63 19.77

23 47.30 21.97

24 33.53 22.80

25 19.11 23.23

26 25.09 31.24

27 14.94 30.64

28 17.89 32.58

29 24.46 28.53

30 39.85

31 12.95

32

33

34

35

ni = number runs = 0 31 29

ni-1 30 28

= sum of (ni-1) 268
means 21.33 22.65

Mean 20.69

N = Number sources= 9

m= number future runs = 30

t-statistic = quantile t-distribution with df degrees of freedom at .99 confidence level =

Assuming Correlated variables

correlation =correl(data-last,data - first obs)

0.135746154 0.54308166

Pooled stdev= 9.62605957

Variance data = 92.6610229

adjustment for temporal correlation= 111.996455

intra quarry variance= 116.012236

adjustment for temporal correlation= 175.953767

total variance 287.950222 *** QUESTION FOR MIKE: DOES TEM

*** IN OTHER WORDS, WHAT YOU G

*** If NOT, THEN ONLY THE MEASU

*** DATA AND INTRAQUARRY VARI

*** if the data in columns Oto Q are 

*** defined as sdev^2

*** defined as before variance* (1+

*** defined as (RSD*Mean)^2
Variance = Variance pooled, intraquarry data adjusted for temporal correlation 287.950222

SQRT(Variance*(1/n+1/m)) 5.98127358

UPL-- source mean and variance pooled data, including intraquarry variability 34.6879487

57.2351153
ation with Intraquarry Variability - 07/28/10, 3:10PM

Kiln ID 1302 Kiln ID 1315 Kiln ID 1364 Kiln ID 1435 Kiln ID 1484 Kiln ID 1589 Kiln ID 1650

16.82 16.67 26.00 30.50 30.50 13.22

12.97 12.76 28.27 27.52 27.52 7.64

9.49 9.57 27.59 29.07 29.07 9.53

10.43 10.58 37.25 24.64 24.64 1.71

9.44 9.64 28.78 23.82 23.82 7.66

11.47 11.71 7.72 24.52 24.52 0.32

13.59 13.83 42.98 25.14 25.14 14.12

12.85 12.72 25.28 26.46 26.46 13.70

4.30 4.38 24.67 25.49 25.49 12.72

12.04 12.29 25.39 38.60 38.60 11.24

21.41 20.55 24.24 24.65 24.65 10.56

13.65 13.82 23.34 29.45 29.45 9.82

12.44 12.54 25.04 25.04 25.04 12.92

16.52 16.66 23.65 29.91 29.91 13.70

22.02 22.51 26.83 1.43 1.43 9.46

12.31 12.31 27.19 5.07 5.07 7.66

15.39 15.11 24.25 25.97 25.97 12.36

13.51 13.59 25.28 29.30 29.30 13.98

3.75 3.82 24.83 26.93 26.93 9.40

9.40 9.59 23.88 26.63 26.63 8.68

10.88 11.06 23.69 24.82 24.82 7.60

12.45 12.35 21.74 24.11 24.11 7.62

11.76 11.89 26.04 22.00 22.00 7.63

11.73 11.75 7.28 22.00 22.00 8.20

60.15 61.31 26.36 22.00 22.00 11.27

20.59 19.93 36.12 35.74 35.74 8.93

13.96 14.10 28.96 24.47 24.47 7.64

21.90 21.19 29.82 38.69 38.69 7.60

12.74 11.85 29.05 27.28 27.28

28.41 27.66 26.93 26.93

23.83 23.83

24.11 24.11

27.28 27.28

24.82 24.82

24.47 24.47

30 30 29 35 35 0 28

29 29 28 34 34 27

Emissions (lb/ton feed)
15.28 15.26 25.91 25.51 25.51 9.53

#source mean = mean of source means

#because UPL is based on source means

 freedom at .99 confidence level = 2.34034229 =tinv((1-.99)*2,df)

0.10213164 0.084305058 -0.18774805 0.23671245 0.23671245 0.19500164

Revised 3 quarry, intraquarry variability RSD= 0.52

** QUESTION FOR MIKE: DOES TEMPORAL CORRELATION AFFECT THE QUARRY OR ONLY THE KILNS?

** IN OTHER WORDS, WHAT YOU GET FROM THE QUARRY ONE DAY DEPENDS OF WHAT YOU GET THE PREVIOUS DAYS?

** If NOT, THEN ONLY THE MEASUREMENTS HAVE TEMPORAL CORRELATION, IF YES: THEN BOTH THE VARIANCE OF 

** DATA AND INTRAQUARRY VARIANCE NEED TO BE MULTIPLIED BY (1+CORR)

** if the data in columns Oto Q are the intraquarry data, we can calculate the temporal correlation there and use it for the adjustment of 

** defined as sdev^2

** defined as before variance* (1+corr)

** defined as (RSD*Mean)^2
#calculated as variance*(1+average(temporal correlation))

lb/MM tons feed

lb/MM tons clinker
Kiln ID 1594 Kiln ID # 1239 1248 1376

13.60 0.0795 0.0265

30.05 0.0233 0.0197

32.88 0.0296 0.0214

32.59 0.0245 0.0326

28.73 0.02 0.0225

34.14 0.0495 0.02

32.33 0.0462 0.0337

23.38 0.0315 0.0365

35.00 0.0264 0.0344

32.91 0.0294 0.0313

31.44 0.0263 0.0312

27.48 0.0242 0.028

28.55 0.0407 0.0317

25.19 0.0309 0.0207

25.63 0.0235 0.0274

10.01 0.0295 0.0263

28.03 0.0673 0.0211

30.27 0.0625 0.0177

25.85 0.0624 0.0318

33.36 0.0899 0.0246

29.10 0.0835 0.0289

26.91 0.122 0.0232

29.70 0.0998 0.0292

30.02 0.0991 0.0302

10.91 0.109 0.036

11.87 0.13 0.0291

14.04 0.104 0.0296

13.49 0.0589 0.0265

15.72 0.0729 0.0257

13.75 0.0856 0.0255

30

29

Daily Mercury Concentrations (ppm) in Limestone by Quarry
Avg 0.0594 0.027 0.043

Stdev 0.023

RSD 0.520592

correlation 0.8052 0.2282 0.5167

25.23

nv((1-.99)*2,df)

0.532073044

E PREVIOUS DAYS?

E VARIANCE OF 

here and use it for the adjustment of the intraquarry variance
MACT New UPL for Mercury Using Pooled Variance, Corrected for Temporal Autocorrelation with Intraquarry Variability - 07/

Runs Kiln ID 1248 Kiln ID 1259 Kiln ID 1286

1 0.32 18.88 27.01

2 15.53 15.77 28.73

3 17.43 20.71 28.67

4 16.57 22.61 27.95

5 18.30 19.67 7.66

6 17.06 25.90 7.49

7 16.57 22.63 7.58

8 21.00 21.21 8.12

9 16.57 5.07 23.93

10 16.57 44.96 22.61

11 16.57 34.37 23.06

12 16.57 13.46 24.21

13 16.57 11.57 25.25

14 20.45 13.90 21.47

15 16.57 27.43 25.53

16 16.99 25.55 25.89

17 16.60 21.95 29.34

18 16.57 12.10 26.03

19 16.57 12.83 7.60

20 16.57 9.18 24.26

21 16.57 8.74 23.68

22 16.57 17.63 19.77

23 16.65 47.30 21.97

24 19.14 33.53 22.80

25 21.37 19.11 23.23

26 16.57 25.09 31.24

27 16.57 14.94 30.64

28 16.57 17.89 32.58

29 16.30 24.46 28.53

30 16.58 39.85

31 12.95

32

33

34

35

ni = number runs = 30 31 29

ni-1 29 30 28
= sum of (ni-1) 27

means 16.63 21.33 22.65

Mean 9.53

n to be used with 1 source= ni 28

m= number future runs = 30

t-statistic = quantile t-distribution with df degrees of freedom at .99 confidence level =

Assuming Correlated variables

correlation =correl(data-last,data - first obs)

0.20273792 0.135746154 0.54308166

Stdev= 3.35459919

Variance data = 11.2533357

adjustment for temporal correlation= 13.4477546

intra quarry variance= 24.6268249

adjustment for temporal correlation= 37.3510826

total variance 50.7988372 *** defined as variance of data + int

*** if the data in columns Oto Q are 

*** defined as sdev^2

*** defined as before variance* (1+

*** defined as (RSD*Mean)^2
Variance = Variance pooled, intraquarry data adjusted for temporal correlation 50.799

SQRT(Variance*(1/n+1/m)) 1.873

UPL-- source mean and variance pooled data, including intraquarry variability 14.16

23.37

Recall the formula for the variance is N is the number of sampling units u

2 1 1

s

N m

    

 
on with Intraquarry Variability - 07/28/10, 3:10PM

Kiln ID 1302 Kiln ID 1315 Kiln ID 1364 Kiln ID 1435 Kiln ID 1484

MACT 

NewKiln 

1650 Kiln ID 1650

16.82 16.67 26.00 30.50 30.50 13.22 13.22

12.97 12.76 28.27 27.52 27.52 7.64 7.64

9.49 9.57 27.59 29.07 29.07 9.53 9.53

10.43 10.58 37.25 24.64 24.64 1.71 1.71

9.44 9.64 28.78 23.82 23.82 7.66 7.66

11.47 11.71 7.72 24.52 24.52 0.32 0.32

13.59 13.83 42.98 25.14 25.14 14.12 14.12

12.85 12.72 25.28 26.46 26.46 13.70 13.70

4.30 4.38 24.67 25.49 25.49 12.72 12.72

12.04 12.29 25.39 38.60 38.60 11.24 11.24

21.41 20.55 24.24 24.65 24.65 10.56 10.56

13.65 13.82 23.34 29.45 29.45 9.82 9.82

12.44 12.54 25.04 25.04 25.04 12.92 12.92

16.52 16.66 23.65 29.91 29.91 13.70 13.70

22.02 22.51 26.83 1.43 1.43 9.46 9.46

12.31 12.31 27.19 5.07 5.07 7.66 7.66

15.39 15.11 24.25 25.97 25.97 12.36 12.36

13.51 13.59 25.28 29.30 29.30 13.98 13.98

3.75 3.82 24.83 26.93 26.93 9.40 9.40

9.40 9.59 23.88 26.63 26.63 8.68 8.68

10.88 11.06 23.69 24.82 24.82 7.60 7.60

12.45 12.35 21.74 24.11 24.11 7.62 7.62

11.76 11.89 26.04 22.00 22.00 7.63 7.63

11.73 11.75 7.28 22.00 22.00 8.20 8.20

60.15 61.31 26.36 22.00 22.00 11.27 11.27

20.59 19.93 36.12 35.74 35.74 8.93 8.93

13.96 14.10 28.96 24.47 24.47 7.64 7.64

21.90 21.19 29.82 38.69 38.69 7.60 7.60

12.74 11.85 29.05 27.28 27.28

28.41 27.66 26.93 26.93

23.83 23.83

24.11 24.11

27.28 27.28

24.82 24.82

24.47 24.47

30 30 29 35 35 28 28

29 29 28 34 34 27 27

Emissions (lb/ton feed)
15.28 15.26 25.91 25.51 25.51 9.53 9.53

#source mean = mean of source means

 freedom at .99 confidence level = 2.4726599 =tinv((1-.99)*2,df)

0.10213164 0.084305058 -0.18774805 0.23671245 0.23671245 0.19500164 0.19500164

Revised 3 quarry, intraquarry variability RSD= 0.52

** defined as variance of data + intra quarry variance

** if the data in columns Oto Q are the intraquarry data, we can calculate the temporal correlation there and use it for the adjustment of 

** defined as sdev^2

** defined as before variance* (1+corr)

** defined as (RSD*Mean)^2
lb/MM tons feed

lb/MM tons clinker

 is the number of sampling units used in the sample: in this case the number of data points
Kiln ID 1594 Kiln ID # 1239 1248 1376

13.60 0.0795 0.0265

30.05 0.0233 0.0197

32.88 0.0296 0.0214

32.59 0.0245 0.0326

28.73 0.02 0.0225

34.14 0.0495 0.02

32.33 0.0462 0.0337

23.38 0.0315 0.0365

35.00 0.0264 0.0344

32.91 0.0294 0.0313

31.44 0.0263 0.0312

27.48 0.0242 0.028

28.55 0.0407 0.0317

25.19 0.0309 0.0207

25.63 0.0235 0.0274

10.01 0.0295 0.0263

28.03 0.0673 0.0211

30.27 0.0625 0.0177

25.85 0.0624 0.0318

33.36 0.0899 0.0246

29.10 0.0835 0.0289

26.91 0.122 0.0232

29.70 0.0998 0.0292

30.02 0.0991 0.0302

10.91 0.109 0.036

11.87 0.13 0.0291

14.04 0.104 0.0296

13.49 0.0589 0.0265

15.72 0.0729 0.0257

13.75 0.0856 0.0255

30

29

Daily Mercury Concentrations (ppm) in Limestone by Quarry
Avg 0.0594 0.027 0.043

Stdev 0.023

RSD 0.520592

correlation 0.8052 0.2282 0.5167

25.23

nv((1-.99)*2,df)

0.532073044

here and use it for the adjustment of the intraquarry variance