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

Emissions (lb/ton feed)

Runs Kiln ID 1259 Kiln ID 1286 Kiln ID 1302 Kiln ID 1315 Kiln ID 1364

1 18.88 27.01 16.82 16.67 26.00

2 15.77 28.73 12.97 12.76 28.27

3 20.71 28.67 9.49 9.57 27.59

4 22.61 27.95 10.43 10.58 37.25

5 19.67 7.66 9.44 9.64 28.78

6 25.90 7.49 11.47 11.71 7.72

7 22.63 7.58 13.59 13.83 42.98

8 21.21 8.12 12.85 12.72 25.28

9 5.07 23.93 4.30 4.38 24.67

10 44.96 22.61 12.04 12.29 25.39

11 34.37 23.06 21.41 20.55 24.24

12 13.46 24.21 13.65 13.82 23.34

13 11.57 25.25 12.44 12.54 25.04

14 13.90 21.47 16.52 16.66 23.65

15 27.43 25.53 22.02 22.51 26.83

16 25.55 25.89 12.31 12.31 27.19

17 21.95 29.34 15.39 15.11 24.25

18 12.10 26.03 13.51 13.59 25.28

19 12.83 7.60 3.75 3.82 24.83

20 9.18 24.26 9.40 9.59 23.88

21 8.74 23.68 10.88 11.06 23.69

22 17.63 19.77 12.45 12.35 21.74

23 47.30 21.97 11.76 11.89 26.04

24 33.53 22.80 11.73 11.75 7.28

25 19.11 23.23 60.15 61.31 26.36

26 25.09 31.24 20.59 19.93 36.12

27 14.94 30.64 13.96 14.10 28.96

28 17.89 32.58 21.90 21.19 29.82

29 24.46 28.53 12.74 11.85 29.05

30 39.85 28.41 27.66

31 12.95

32

33

34

35

ni = number runs = 31.00 29.00 30.00 30.00 29.00

ni-1 30.00 28.00 29.00 29.00 28.00

= sum of (ni-1) 268.00
means 21.33 22.65 15.28 15.26 25.91

Mean 20.69 #source mean = mean of source means

N = Number sources= 9.00 #because UPL is based on source means

m= number future runs = 30.00

t-statistic

Assuming Correlated variables

correlation

0.14 0.54 0.10 0.08 -0.19

Pooled stdev= 9.62605957

Variance data = 92.6610229 *** defined as sdev^2

adjustment for temporal correlation= 111.996455 *** defined as before variance* (1+corr)

intra quarry variance= 116.012236 *** defined as (RSD*Mean)^2

adjustment for temporal correlation= 175.953767

total variance 287.950222 *** QUESTION FOR MIKE: DOES TEMPORAL CORRELATION AFFECT THE QUARRY OR 

*** IN OTHER WORDS, WHAT YOU GET FROM THE QUARRY ONE DAY DEPENDS OF W

*** If NOT, THEN ONLY THE MEASUREMENTS HAVE TEMPORAL CORRELATION, IF YES

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

Variance = Variance pooled, intraquarry data adjusted for temporal correlation 287.95 #calculated as variance*(1+average(temporal correlation))

*** if the data in columns Oto Q are the intraquarry data, we can calculate the temp

it for the adjustment of the intraquarry variance
SQRT(Variance*(1/n+1/m)) 5.98

UPL-- source mean and variance pooled data, including intraquarry variability 34.69 lb/MM tons feed

57.24 lb/MM tons clinker
rrelation with Intraquarry Variability

Kiln ID 1435 Kiln ID 1484 Kiln ID 1650 Kiln ID 1594

30.50 30.50 13.22 13.60

27.52 27.52 7.64 30.05

29.07 29.07 9.53 32.88

24.64 24.64 1.71 32.59

23.82 23.82 7.66 28.73

24.52 24.52 0.32 34.14

25.14 25.14 14.12 32.33

26.46 26.46 13.70 23.38

25.49 25.49 12.72 35.00

38.60 38.60 11.24 32.91

24.65 24.65 10.56 31.44

29.45 29.45 9.82 27.48

25.04 25.04 12.92 28.55

29.91 29.91 13.70 25.19

1.43 1.43 9.46 25.63

5.07 5.07 7.66 10.01

25.97 25.97 12.36 28.03

29.30 29.30 13.98 30.27

26.93 26.93 9.40 25.85

26.63 26.63 8.68 33.36

24.82 24.82 7.60 29.10

24.11 24.11 7.62 26.91

22.00 22.00 7.63 29.70

22.00 22.00 8.20 30.02

22.00 22.00 11.27 10.91

35.74 35.74 8.93 11.87

24.47 24.47 7.64 14.04

38.69 38.69 7.60 13.49

27.28 27.28 15.72

26.93 26.93 13.75

23.83 23.83

24.11 24.11

27.28 27.28

24.82 24.82

24.47 24.47

35.00 35.00 28.00 30.00

34.00 34.00 27.00 29.00
25.51 25.51 9.53 25.23

2.34 =tinv((1-.99)*2,df)

0.24 0.24 0.20 0.53

Revised 3 quarry, intraquarry variability RSD= 0.52

ORRELATION AFFECT THE QUARRY OR ONLY THE KILNS?

 THE QUARRY ONE DAY DEPENDS OF WHAT YOU GET THE PREVIOUS DAYS?

HAVE TEMPORAL CORRELATION, IF YES: THEN BOTH THE VARIANCE OF 

D TO BE MULTIPLIED BY (1+CORR)

age(temporal correlation))

quarry data, we can calculate the temporal correlation there and use 
MACT New UPL for Mercury Using Pooled Variance, Corrected for Temporal Autocorrelation with Intraquarry Variability - 07/2

Emissions (lb/ton feed)

Runs MACT NewKiln 1650

1 13.22

2 7.64

3 9.53

4 1.71

5 7.66

6 0.32

7 14.12

8 13.70

9 12.72

10 11.24

11 10.56

12 9.82

13 12.92

14 13.70

15 9.46

16 7.66

17 12.36

18 13.98

19 9.40

20 8.68

21 7.60

22 7.62

23 7.63

24 8.20

25 11.27

26 8.93

27 7.64

28 7.60

29

30

31

32

33

34

35

ni = number runs = 28.00

ni-1 27.00

= sum of (ni-1) 27.00

Mean 9.53 #source mean = mean of source means

n to be used with 1 source= ni 28.00
m= number future runs = 30.00

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

Assuming Correlated variables

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

Stdev= 3.35

Variance data = 11.2533357 *** defined as sdev^2

adjustment for temporal correlation= 13.4477546 *** defined as before variance* (1+corr)

intra quarry variance= 24.62682492 *** defined as (RSD*Mean)^2

adjustment for temporal correlation=37.35108256 *** if the data in columns Oto Q are the intraquarry data, 

total variance 50.79883717 *** defined as variance of data + intra quarry variance

Variance = Variance pooled, intraquarry data adjusted for temporal correlation 50.7988372

SQRT(Variance*(1/n+1/m)) 1.87284243

UPL-- source mean and variance pooled data, including intraquarry variability 14.1634054 lb/MM tons feed

23.3696189 lb/MM tons clinker

Recall the formula for the variance is N is the number of sampling units used in the sample: in t
ntraquarry Variability - 07/28/10, 3:10PM

mean of source means
2.47

0.24

Revised 3 quarry, intraquarry variability RSD= 0.52

Q are the intraquarry data, we can calculate the temporal correlation there and use it for the adjustment of the intraquarry variance

 + intra quarry variance

its used in the sample: in this case the number of data points

raquarry variance