# OAR Box 1115 Prepped byRyan Dugan



## Document

Number: 

# 84 ) ll-A-1 6
Docket Number: 

# A-84-2 2

Printed 4/18/200810:52:08AM Sheet 84 of 94 P. 14 P. 2 

# fir/-**- -%-h-ii

STATISTICAL ANALYSI S O F VISIBL E EMISSION S FIEL D TEST S

by P . V . Piserchi a T . D . Hartwel l J . H . Crowde r

Prepare d fo r
Th e U.S . Environnenta l Protectio nAgenc y Researc hTriangl e Park , Nort hCarolin a

Februar y18 , 19 8 2P. 3



## 1. 0 INTRODUCTION

Thi s repor t present s statistica l analyse s an d dat a summarie s fo r thre e visibl e emission s fiel d studie s con ducte d i n 198 0 an

d 198 1 b

yEaster nTechnica l Associate s o f Raleigh , NC . Th e fiel d studie s wer e carrie d ou t a t Researc h Triangl e Park , NC , Orlando , FL , an d Jacksonville , F L unde r th e auspice s o f th e U.S . Environmenta l Protectio nAgency' s Divisio n o f StationarySourc e Enforcement , an d ful l descrip

tiv e report s o n th e test s hav e bee n prepare d b yDe l Gree n Associates , Inc . o f Foste r City , CA[1-3]
. Eac hindividua l tes t wa s o f six-minut e duratio nan d wa s conducte d o n a plume generate d b ya smok e generator . Smok e typ e wa s distribute d approximatel yequall ybetwee nblac k an d whit e plumes
. Fo r eac htest , multipl e visibl e emission s observers , eac hcertifie d according t o EP AReferenc e Tes t Metho d 9 (4 0 CF RPar t 60 , Appendi xA ) , viewe d the smok e plume
. Atota l o f 4 2 differen t observer s participate d i n all
. Th e number s o f test s an d individua l observation s wer e a s follows :

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## 9 6 1 8 1 8 13 2 1,12 4

36 0 18 0 1,66 4 Tabl e 1
. Distributio no f Fiel d Test s and Observation s b y Locatio n Numbe r Numbe r o f Locatio no f Test s Obseirvation s Researc hTriangl e Park , N C (RTP ) Orlando , F L (FL

AI ) Jacksonville , F L (FL AII )

Th e purpos e o f thes e fiel d test s wa s t o asses s th e impac t o f variou s factors , especiall yplum e opacit ypatter n
and smok e type , o n the abilit yo f certifie d visibl e emis

sion s observer s t o estimat e th e time durin g whic ha plume' s opacit yi s equa l t o o r greate r tha n20%
. Tha t impac t i s assesse d i n thi s repor t throughstatistica l analyse s o f th e opacit yestimate s o f the certifie d visibl e emission s observ

er s and compariso nwit hinstrumen t opacit yreading s obtaine d b ya referenc e transmissometer
.

\ \ 

## -2

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# L [
\ 

## 2. 0 DEFINITION S

Th e following term s ar e use d i nthi s repor t t o describ e th e generate d smok e plume s and th e opacit yobservatio n techniques : OBSERVE R—An EP Acertifie d (Method 9 ) smok e reade r wh o estimate s a plume' s time duratio ni nexces s o f 20 % opacity
. Ther e wer e 1 2 observer s participatin g i n th e RT P fiel d tests , 2 0 participating i n th e FLAI fiel d tests , an d 1 0 participatin g i nth e FLAI I fiel d tests . TRANSMISSOMETE R—An instrumen t tha t photometricall y measure s th e opacit yo f a plume a s transmittanc e o f light
. I nthi s case , th e transmissomete r measure s the opacit y o f th e smok e plume s generate d b yth e smok e generator ; th e transmissomete r measuremen t i s considere d th e reference
. METHO D —Th e metho d o f observing an d estimatin g time duration
. Fo r th e FLAI an d FLAI I fiel d tests , the plume' s opacit ywa s estimate d an

d recorde d b

yth e observer s a t 15-second interval s an d thi s metho d i s calle d FREQUENCY . Fo r th e RT P fiel d study , durin g an

yon e test , one-hal f th e observer s use d the FREQUENC Ymetho d
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## SMOK E TYP E whil e th e othe r hal f o f th e observer s accumulate d the time duratio n i nexces s o f 20 % opacit yvi a a stopwatch ; thi s metho d i s calle d STOPWATCH .

—Denote s colo r o f smok e plum e (predomi

nantl yblac k o r white ) generate d fo r eac htest . PLUM E RIS E TIM E —Th e time i n second s fo r th e opacit yo f a plume t o ris e fro

mit s baselin e valu e t o it s peak valu e (for a nexample , se e Figur e 1 , RT P plumes)
. RIS E .AMOUN

T —Fo r th e Florida I I dat a (se e Figur e 1 ) ,

ove r th e six-minut e observatio nperiod , th e plume opacitie s ros e o r fel l (RIS E = + o r - ) b

ya specifie d amoun t (AMOUN T = 20% , 30% , 40 % opacity)
.

—Th e time (i

n seconds ) during whic h opacit yactuall yexceede d 20 % a s measure d b

ythe transmissometer
.

—RTIM E i s 1 5 multiplie d b yth e numbe r o f transmissomete r reading s take na t 15-secon

d interval s whic har e a t leas t 20 % opacity
.

—Th e time (in seconds ) during whic h opacit ywa s observe d t o excee d 20%
. RTIM E

OTIM E

\ 

## -4

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# t L I { 

# I I —Fo r th e STOPWATC H method , thi s i s th e cumulativ e stopwatc htime th e plum e wa s observe d t o b e a t leas t 20 % opacity
.

—Fo r th e FREQUENC Ymethod , OTIM E i s 1 5 multiplie d b

yth e numbe r o f 15-second reading s observe d t o b e a t leas t 20 % opacity
. DIFT M—OTIME-RTIM E = the differenc e betwee nth e observe d tim e an

d th e actua l time i n exces s o f 20 % opacity
. Apositiv e DIFT M i s a n overestimat e o f the time duratio n>

_ 20 % opacit yan

d a negativ e DIFTMi s an underestimat e o f th e time duratio n^ 20 % opacity
. RM 9 —Th e averag e transmissomete r opacit y (measured a t 15-second intervals ) calculate d fo r eac hsix-minut e test . OM 9 —Th e averag e observe d opacit y(observe d
a t 15-second intervals ) calculate d fo r eac hobserve r an

d six-minut e tes t whe n th e metho d i s FREQUENCY . RSD 9 —Th e standar d deviatio no f th e transmis

somete r opacitie s (measure d a t 15-second intervals ) calculate d fo r eac htest . RSD 9 i s a measur e o f plume opacit y variability
.

\ 

## \ -5

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## 0SD 9 —

Th e standar d deviatio n o f th e observe d opacitie s (observed a t 15-second inter

vals ) calculate d fo r eac hobserve r an d tes t whe n th e metho d i s FREQUENCY . Othe r variable s whic hwer e calculate d bu t no t use d i n thi s repor t are : OTIME2 5 —Th e calculate d time o f observe d opacit y i n exces s o f 25%
. Thi s calculatio nwa s possibl e fo r onl yth e FREQUENC Ymethod
. OTIME3 0 —Th e calculate d time o f observe d opacit y i n exces s o f 30%
. Thi s calculatio nwa s possibl e fo r onl yth e FREQUENC Ymethod
. Corresponding t o OTIME2 5 an d OTIME3 0 the following variable s wer e calculated :

DIFTM2 5 = OTIME2 5 - RTIM E DIFTM3 0 = OTIME3 0 - RTIME . Thes e fina l variable s (DIFTM2 5 an d DIFTM30 ) wer e calculate d i n orde r t o examin e th e effec t o ntime duratio n estimate s o f no t considering anobserve d opacit yi nexces s o f 20%

- unles s i t wa s observe d t o b e a t leas t 25 % (OTIME25 )
o r 30 % (OTIME30 )
. Thi s approac hdi d no t prov e usefu l becaus e i t exacerbate d difference s among th e observers ; however , fo r completeness , DIFTM2 5 an d DIFTM3 0 ar e presente d graphicall yi n Figure s 6- 7 an d i nsummar

ytabula r for

mi n Appendi xB .

-6

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(



# I 

# I 3. 0 TH E TEST S

3. 1 RT P Fiel dTest s Th e RT P fiel dtest s wer e designe dt o accommodat e multipl e factors ; namely , (a ) Method s o f observatio n(FREQUENC Yo r STOPWATCH) ; (b ) Plum e ris e time s (fas t o r intermediate) ; (c ) Numbe r o f opacit ypea k cycle s (1 , 2 , o r 3) ; an d (d ) Pea k width s (tim e ove r 20 % opacit ype r peak : 15 , 30 , 45 , 60 , 7 5 o r 9 0 seconds)
. Thes e differen t factor s produce dtest s tha t ar e characterize db yrapidl ychangin g plum e opacitie s wit h multipl e peak s an dver yhig hvariatio n(7.6%-38.1% ) i n opacit ywithi ntest s a s measure db yRDS9
. 3. 2 Florid a I Fiel dTest s Th e Florid a I fiel dtest s wer e conducte dt o asses s th e performanc e o f tim e duratio nestimate s whe nplum e opacit yi s relativel yconstant . Thes e nearl yconstan t plume s produce d test s characterize db yextremel ylo wvariatio n(0.5%-1.4% ) i nopacit ywithi ntest s a s measure db yRSD9
. 3. 3 Florid a I I Fiel dTest s f Th e Florid a I I fiel dtest s wer e conducte dt o asses s th e 

# L performanc e o f tim e duratio nestimate s whe nplum e opacit y

level s slowl yris e o r fall ; consequently , thes e test s wer e designe dt o sho wth e observer s smal l change s i nplum e opacit ylevel s ove r th e six-minut e observatio nperiod
.

\ 

## -7

-' • > I . ssi

I 0 0 I RAPIDLYCHANGIN GPLUME S (RTP ) CONTINUOU S PLUME S (FL A I ) SLOWL YCHANGINGPLUME S (FL A II )



## (eachtes t containe d 1 t o 3 peaks )
-OBSERVATIO

NPERIO

D O F SI XMINUTES 

### MINUTE S 

## Figur e 1
. Typica l Plume Opacit yPattern s Use d i n Opacit yMetho d Evaluatio nStudie s

T l oP.1 1 

# F 

# r



# L I [ Thes e test s ar e characterize d b ymoderat e variatio n(4.6%

- 12.4% ) i n opacit ywithi ntest s (RSD9)
. 3. 4 Summaryo f Difference s Amon g th e Tes t Design s A s state d above , th e thre e fiel d test s (RTP , FLAI , FL AII ) wer e no t designe d t o b e simpl e replicate s o f eac h other
. Th e thre e fiel d tests , a s show ni nFigur e 1 , repre sen t fundamentall ydifferen t type s o f chang e i nplume opacit ylevels
. I ngeneral , plume opacit ypatterns , withi n fiel d test s wer e mor e alik e on e anothe r tha n wer e plum e opacit ypattern s take n acros s fiel d tests . Table s 2- 3 and Figur e 1 summariz e th e tes t parameter s discusse d i n section s 3.1-3.3
.

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## Tabl e 2
. Tes t Summaries — 1 /
Minimu mMea n Maximu

m RTIM E (in Seconds ) Rapidl yChanging Plume s (RTP ) 15. 0 120. 0 285. 0 Continuou s Plume s (FL AI ) 0. 0 223. 3 360. 0 Slowl yChangin g Plume s (FL AII ) 165. 0 305. 0 360. 0 RM 9 (in % Opacity ) Rapidl yChanging Plume s (RTP ) 4. 6 19. 8 51. 6 Continuou s Plume s (FL AI ) 9. 3 23. 4 40. 9 Slowl yChanging Plume s (FL AII ) 19. 8 29. 5 42. 1 RSD 9 (in % Opacity ) Rapidl yChanging Plume s (RTP ) 7. 7 21. 4 38. 1 Continuou s Plume s (FL AI ) 0. 5 0. 9 1. 4 Slowl yChanging Plume s (FL AII ) 4. 6 8. 4 12. 4 Numbe r o f Test s 9 6 1 8 1 8

—Fo r eac htest , on e RTIME , RM9 , an d RDS 9 mayb e compute d an d RTIM E • = Numbe r o f second s i nexces s o f 20 % opacit yi n si xminute s a s estimate d b ytransmissometer
. RM 9 = Mea n opacit ya s measure d b yth e transmissomete r fo r th e si xminute s (method 9 dat a reduction) ; on e opacit yeac hfiftee n second s (2 4 opacitie s i nsi x minutes)
. RSD 9 = Th e standard deviatio no f the opacitie s measure d b yth e transmissomete r fo r th e si xminutes ; on e opacit yeac hfiftee nsecond s (2 4 opacitie s i n si x minutes)
.

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## Tabl e 3
. Distributio n o f Test s b ySmok e Type , Pea k Ris e Time , Numbe r o f Peaks , an d Peak Widt hfo r Rapidl y Changin g (RTP ) Plume s Smok e Typ e

Blac k

Blac k

Whit e

Whit e Plum e Ris e

Tim e

Fas t

Intermediat e

Fas t

Intermediat e No . o f

Peak s

1 2 3 Tota l
1 2 3 Tota l
1 2 3 Tota l
1 2 3 Tota l 

## 1 5

1 1 1 3
0 0 0 0
0 2 0 2
0 0 0 0 Pea k Widt h 3 0

0 0 1 1
3 1 0 4
3 0 2 5
3 4 5 1 2 45
.
1 0 2 3
0 0 0 0
0 1 3 4
0 0 0 0 6 0

1 0 2 3
4 3 4 1 1
2 3 3 8
3 3 3 9 7 5

1 2 1 4
0 0 0 0
1 4 1 6
0 0 0 0 9 0

2 1 2 5
2 0 3 5
1 1 1 3
2 4 2 8 Tota l

6 4 9 1 9
9 4 7 2 0
7 1 1 1 0 2 8
8 1 1 1 0 2 9 

# [ [ 

# L

-n -P. M

r \



## 4. 0 FACTOR S INFLUENCIN GACCURAC YAND PRECISION

Severa l factor s wer e evaluate d t o determin e thei r effec t o n th e accurac yan d precisio no f estimating time duratio n i n exces s o f 20 % opacity
. Here , th e measure s o f
accurac yan

d precisio nare , respectively , mea nDIFTM(aver

ag e tim e bias ) and the standar d deviatio no f DIFTM . Th e factor s evaluate d wer e metho d o f observatio n(STOPWATCH an d FREQUENCY) , plume opacit ypatter n(rapidl ychanging opacit y levels , constan t opacit ylevels , an d slowl ychanging opacit y level s a s represented , respectively , b yth e thre e fiel d test s RTP , FLAI , an d FLAII) , smok e typ e (light (WHITE ) o r dar k (BLACK)) , pea k width , numbe r o f peak s an d pea k ris e time
.Tabl e 4 present s estimate s o f the accurac yan d preci

sio n o f estimating.time duratio n i nexces s o f 20 % opacit yb y plum e opacit ypattern , metho d an d smok e type . Fromthi s tabl e i t i s seen tha t plume opacit ypattern s (as represente d byth e thre e fiel d tests ) an d smok e typ e (BLACK o r WHITE ) hav e strong influence s upo nth e accurac yo f estimatin g emission s time duratio n i n exces s o f 20 % opacity
. I n addition , plume opacit ypattern s strongl yinfluenc e preci

sion
. Here , precisio n(S D (DIFTM) ) i s see nt o varyin

versel ywit hthe plume opacit yvariability ; th e greates t precisio n i s fo r th e RT P rapidl ychanging plume s and th e leas t precisio n fo r the continuou s FL AI plumes
.

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. ' * ~ H * -«••-- •



## 1 / 2 / Tabl e 4
. Fiel d Tes t Summarie s b ySmok e Type

—an

d Metho d o f Observation — Rapidl y Changing (RTP ) S W B W Plume Opacit yPatter n

Rapidl y Changing (RTP ) FRE Q B W Continuou s

(FL AI ) FRE Q B W Slowl y

Changin g (FL AII ) FRE Q B W

RTIM E MEAN-" 7 

## 12 4 11 9 12 4 11 8 25 0 19 7 31 2 29 8
DIFTMMEAN-'-- 7 

## 0. 6 5.0 ^ 3. 4 9. 7 -111. 0 19. 4 -14. 3 50. 3
S D (DIFTM ) 3,5 / 10. 2 14. 4 14. 1 18. 7 133. 7 134. 2 98. 8 58. 1

l 

## N 22 5 32 9 23 5 33 5 18 0 18 0 9 0 9 0

1/ 

## 2 / B = Black ; W= White
.

— S W= Stopwatch ; FRE Q = Frequency . 

# 1' 4 / Time i n seconds
.

—Observe d Tim e > 20 % Opacit y(OTIME ) minu s Transmissomete r Tim e >

_20 % Opacit y(RTIMET
. s /

- Standard deviatio no f DIFTM .P.1 6



## Figur e 2 shed s some ligh t o n th e behavio r o f th e Florid a I data
. Th e figur e suggest s tha t whe npresente d wit hsmok e plume s o f unchangin g opacity , observer s ar e hesitan t t o classif yopacit ya s greate r tha n20 % unti l i t i s considerabl ygreate r tha n20%
. Thi s doe s no t appea r t o b e th e cas e wit hrapidl ychanging (RTP ) o r slowl ychanging plum e opacit ypattern s (FL AII)
. Figure s 3- 5 presen t additiona l measure s o f accurac yan d precision
. I n particular , Figur e 3 show s ho wwel l observe d tim e duratio n ^20 % (OTIME ) correlate s wit hactua l tim e duratio n ^20 % (RTIME ) fo r RT P dat a fo r bot hth e frequenc y and stopwatc hmethods
. Figur e 4 , o n th e othe r hand , show s tha t relativ e t o rapidl ychanging plume opacit ypattern s (RTP) , estimate d tim e duratio n ^20 % opacit y(OTIME ) i s no t wel l behave d fo r constan t (FL AI ) o r slowl ychanging (FL AII ) plum e opacit ypatterns . Figure s 5- 7 presen t DIFTM , DIFTM2 5 an

d DIFTM3 0 plotte d agains t RTIME . I t i s see ntha t DIFTM2 5 and DIFTM3 0 produc e seriou s underestimate s o f th e tim e duratio n ^20 % opacity
. Finally , Figur e 8 present s a plo t o f classi c metho d 9 (OM9 ) tes t mean s (computed b yfiel d test ) agains t th e corresponding transmissomete r metho d 9 (RM9 ) opacit yaver age . I t i s see n tha t wit hrespec t t o classi c metho d 9 , th e observer s di d well
. Tha t is , unlik e th e time duratio n estimates , metho d 9 opacit yestimate s (OM9 ) fo r FLAI an d

-14

-r—r- f

i t-r u i I •Proportio n l . o *

0. 9

0. 8

0. 7

0. 6

0. 5

0. 4

0. 3

0. 2 •

0. 1 *

0. 0 • ! Symbo l 1 - RT P 2 » FLA

I 3 « * FL AI I

0 5 1 0 1 5 2 0 2 5 3 0 3 5 1 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 Transmissomete r Opacit y Figur e 2
. Proportio n o f Observation s Recorde d a s ^20 % Opacit ybyObserver s Plotte d Versu s Opacit y

(Rounde d t o th e Neares t 5 % Opacity) : FREQUENC YDat a Onl y 8 0 6 5 9 033 0

30 0

27 0

24 0

21 0

18 0 *

15 0 •

as I 12 0

9 0

6 0

3 C OTIM E

OTIM E - RTIM E

Correlation s o f OTIM E wit hRTIM E Blac k Whit e S

.9 9 .9 2 F

.9 8 .9 6

..«-..-• « --.«>---.-«-----a>--a---«-----«-- r --a>-a>.--«-aa-.~a>..-._«._...a>___._ 4

_ . 10 5 12 C 13 5 15 0 16 5 18 0 19 5 21 0 22 5 24 0 25 5 27 0 28 5 RTIM E 1 5 4 5 6 J 7 5 9U Figur e 3
. OTIM E Plotte d Versu s RTIME s Raw RT P FREQUENC Y(F ) an d STOPWATC H (S ) Dat a

XI ®r 

## — • 

## r '. « t

OTIM E 36 0
33 0
30 0
27 0
24 0
21 0
18 0
15 0
l 12 0 i — l 9 0
6 0
3 0 OTIM E » RTIM E

Symbo l 1 = RT P

2 - FLA

I I 3 - FLA

I I

15 0 3 0 6 0 9 0 12 0 18 0 21 0 RTIM E 24 0 27 0 30 0 33 0 36 P Figur e 4
. OTIM E Tes t Mean s Plotte d Versu s Tes t RTIME : FREQUENC YDat a Onl yI —'. f--'-*

f... •"-

DIFTM

15 0 ! 2

10 0

5 0

-5 0

-10 0

•15 0

!0 0 -t-r Symbo l 1 - RT P 2 = FLA

I 3 • = FL A I I 1 1 1 1 1 1 1 1 , . 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1

1 3

1 1
1
3 1

3 3 2 2 2
DIFTM

--• - 9 3 12 0 18 0 RTIM E

a.*. . 19 5 1 5 3 0 6 0 7 5 10 5 13 5 15 0 16 5 21 0 22 5 24 0 25 5 27 0 28 5 30 0 31 5 33 0 .-4m. 34 5 36 0

Figur e 5 . DIFTM

Tes t Mean s Plotte dVersu s Tes t RTIME : FREQUENC YDat a Onl y5 0 t>IFTH2 5

-5 0 ! 2

! 2 » 2 •*

- I ! 1 . « i
• ! ! 1 1 1 1 1 1 1 1 1 1 1 1
•' " 1 1 

# ' I

DIFTM2 5 - 0

to I •10 0

•15 0

-20 0

-25 0 Symbo l 1 = RT P 2 - FLA

I 3 = FL A I I

-30 0
1 5 3 0 4 5 6 0 7 5 9 0 10 5 12 0 13 5 15 0 16 5 ^8 ^ 19 5 21 0 22 5 24 0 25 5 27 0 28 5 30 0 31 5 33 0 34f
. •-4

- ?6 P Figur e 6
. DIFTM2 5 Tes t Mean s Plotte d Versu s Tes t RTIME : FREQUENC YDat a Onl yDIFTM3 0

0

-5 0

-10 0

•15 0

-20 0

t o o I -25 0

•30 0

-35 0 2 

## *J-?

DIFTM3 0 - 0

-a> . 0 Symbo l 1 » RT P . 2 - FL A I 3 » FLA

I I

•-4

- 1 5 3 0 4bfO7 5 --• - 9 0 .-«. a 10 5 12 0 13 5 15 P .......4--..«.
. 16 5 18 0 19 5 RTIM E 21 0 22 5 24 0 25 5 27 0 28 5 30 0 31 5 33 0 34 5 •-4

- 3 6 r >

Figur e 7 . DIFTM3 0 Tes t Mean s Plotte dVersu s Tes t RTIME : FREQUENC YDat a Onl y0M9 9 0

8 0

7 0

6 0

r-> I 5 0

4 0

3 0

2 0

1 0

0 . 

### i 3 i ytr 

### i i a t I 

### l 3 ^--3 * * I3 ^^ ^

1 1 31 3 3 -a^-" ^t 1 1 2 J^\ * 3 -^-*- l 1 1 3 JUT

3 1 3 1 

### iiui^tia 1 1 1 U^\



### t2 1 1 1 1 1 1 1 ^-"' 211 1 2I2 X1 1 m nSymbo l I Iii\y^u. 2 1 U- T 22 1 V^- 1 l^- mi2 f l 1 1 £ \ 0M 9 » RM 9

1 = RT P 2•* * FL A I

. 3 = • FL AI I

5 0 - • -

5 5 05 1 01 5 2 02 5 Figur e8

. 0M9 Tes t Mean s Plotte dVersu s Tes t RM9 : FREQUENC

YDat aOnl y 3 0 RM 9 3 5 4 0 4 5 6 0P.2 4



## FL AI I trac k the transmissomete r metho d 9 (RM9 ) i na reason abl e manner . Here , again , i t i s see ntha t th e FLAI dat a show s underestimatio no f th e tru e opacity
. Factor s othe r thanplume opacit ypatter n an d smok e typ e als o influenc e th e time duratio n estimate ; however , thi s dat a bas e doe s no t sugges t tha t theyar e nearl ya s importan t
a s plum e opacit ypatter no r smok e type . I n orde r t o asses s th e impac t o f thes e factors , analy

se s o f varianc e wer e performe d fo r th e RT P dat a o n th e variabl e DIFTM . Specifically , analyse s wer e performe d testin g th e equalit yo f th e averag e DIFTM(th e measur e o f accuracy ) acros s th e differen t level s o f thes e factors
. Th e analyse s ar e summarize d b ymetho d an

d smok e typ e i n Table s 5- 6 a s th e estimate d mea n DIFTMb yfacto r level
. T o denot e statistica l significanc e th e following conventio ni s followed : N S = n o significan t difference s among th e DIFTM
means , * = the mean s diffe r a t the 5 % significanc e (95 % confidence ) level , * * = th e mean s diffe r a t th e 1 % signifi

canc e (99 % confidence ) level
. Tabl e 5 . Analysi s Summary : Method s

Method s b

ySmok e Typ e Blac k

Mea n DIFTM (N ) Whit e

Mea n DIFTM (N )
STOPWATC H FREQUENC Y Significanc e 0.6 1 (225 ) 3.3 8 (235 ) 5.0 1 (329 )

9.7 2 (335 )

-22

-

## r

Tabl e 6
. Analysi s Sununary : Othe r Factor s an d Metho d Accurac y(DIFTM )

i ts J U ) I 

## Othe r Factor s b y Metho d an

d Smok e Typ e Plume Ris e Time Fas t Intermediat e Significanc e Numbe r o f Peaks/Tes t 1 2 3 Significanc e Peak Width/Tes t 1 5 3 0 4 5 6 0 7 5 9 0 Significanc e 1 / STOPWATC H Blac k Mean DIFTM
-1.2 5 2.5 1 N S
1.6 7 -0.1 9 0.0 4 N S
4.6 7 3.0 3 1.7 2 2.3 7 -1.6 7 -3.6 4 N S (N )
(114 ) (111 )
( 85 ) ( 47 ) ( 93 )
( 18 ) ( 29 ) ( 18 ) ( 78 ) ( 24 ) ( 58 ) Whit e Mean DIFTM
1.3 8 8.7 5 * *


## 1.9 9 4.4 7 7.9 4 N S
-4.4 2 11.4 0 9.4 6 3.1 1 2.7 4 -0.8 8 * 

## (N )
(167 ) (162 )
( 86 ) (130 ) (113 )
( 12 ) ( 98 ) ( 24 ) (101 ) ( 35 ) ( 59 ) FREQUENC Y

Blac k Mea n DIFTM
0.6 6 5.9 5 N S
2.1 7 3.7 5 4.3 3 N S
1.6 7 1.0 0 0.8 3 5.8 2 1.2 5 3.2 5 N S (N )
(114 ) (121 )
( 90 ) ( 48 ) ( 97 )
( 18 ) ( 30 ) ( 18 ) ( 85 ) ( 24 ) ( 60 ) Whit e Mea n DIFT M
0.4 5 19.0 4 * *


## 2.3 3 8.4 1 17.1 2 * *


## 0.0 0 14.8 5 3.1 3 10.1 0 0.4 2 10.5 0 N S (N )
(168 ) (167 )
( 90 ) (132 ) (113 )
( 12 ) (102 ) ( 24 ) (101 ) ( 36 ) ( 60 )

—Peak widt h= time >

_ 20 % opacit ype r peak ; test s designe d s o tha t fo r a give n tes t the same peak widt hwa s use d fo r eac hpea k i nth e test .P.2 6



### Th e analysi s summarie s give n i n Table s 5 , 6 abov e sho w that : (a ) Fo r bot hblac k an d whit e smok e STOPWATC H i s

mor e accurat e (mea n DIFT Mclose r t o zero ) tha n FREQUENC Ya t th e 95 % confidenc e level ; (b ) Whit e plume s wit hfas t ris e time s ca n b e rea d F mor e accuratel ytha n slo wrisin g whit e plume s (99 % confidenc e level) ; (c ) Ther e i s som e suggestio n tha t metho d accurac y
ma yb e inversel yrelate d t o th e numbe r o f peak s pe r uni t time ; an d (d ) N o conclusio n ma yb e draw n concernin g pea k width
. L



### -24

-P.2 7 

# r r

i 5. 0 CONFIDENC E LIMIT S AND STATISTICAL POWE R

5. 1 Confidenc e Limit s A95 % confidenc e limi t fo r a standar d (e.g. , on e minut e i n exces s o f 20 % opacit yi non e hour ) i s tha t amoun t o f time tha t a n observe r mus t estimat e a plume' s opacit yt o b e i n exces s o f 20 % i n orde r t o b e 95 % confiden t tha t th e standar d ha s bee n exceeded
. A s a n example , i n sectio n 5. 2 w e sho w tha t i n orde r t o b e 95 % confiden t tha t a standar d o f on e minut e i n exces s o f 20 % opacit yi non e hou r ha s bee nexceed

ed , an observe r mus t repor t a n estimate d time o f 6. 8 minute s i n exces s o f 20 % opacit y(5. 8 minute s o f erro r allowanc e plu s 1 minut e fo r th e standard ) i non e hour
. Becaus e neithe r th e accurac yno r th e precisio n (Figur e 3 ) o f th e estimate d time duratio ni nexces s o f 20 % opacit ywa s strongl yrelate d t o th e transmissomete r tim e i n exces s o f 20 % opacity , w e hav e assume d a simpl e additiv e statistica l mode l fo r DIFTM . Specifically , w e assume fo r a particula r six-mintu e tes t (denoted a s i ) an d particula r observe r (denoted a s j ) that :
a ) 6-mi n DIFTM. . = B + T . + 0
. + E.. , wher e B = th e averag e bia s o f th e metho d o f estimating time

duration , T . = th e effect , du e t o th e i tes t conditio n (assumed randomfromtest-to-test) ,

-25

-P.2 8 

# r r 

# r aV V 

## 0
. = th e effec t du e t o th e j observe r (assumed t o b e randoml yselecte d froma conceptuall yinfinit e numbe r o f observers) , an d E . . = randomerror . b ) Th e averag e valu e (E ) o f DIFTM(averaged ove r al l tes t condition s an

d observers ) is : E(6-min
. DIFTM ) = B ; tha t is , th e averag e valu e o f th e differenc e betwee n th e observe d time an d transmissomete r time

• i n exces s o f 20 % opacit yi s simpl yth e averag e bia s o f th e metho d and mus t b e estimate d fromth e dat a (Tabl e 4)
. c ) Th e varianc e i nDIFTMfromth e averag e bia s (B ) is : V (6-mi n DIFTM ) = cr

^ + CQ+ a^ , wher e 2 a T

## = th e componen t o f varianc e du e t o differen t tes t conditions , 2 o Q 

## = th e componen t o f varianc e du e t o differen t observers , an

d 2 a„ = th e componen t o f varianc e du e t o randomerror , an d th e varianc e component s mus t b e estimate d fromth e dat a (Tabl e 7)
.

-26

-

### Tabl e 7 . DIFT MVarianc e Component s Du e t o Difference s Amon g Test s an d Observer s byPlum e Opacit yPattern , Smok e Type

—an d Metho d o f

2 / Observation —

Rapidl y Changin g (RTP ) S W 

## B W Plum e Opacit yPatter n

Rapidl y Changin g (RTP ) FRE Q 

## B W Continuou s

(FL AI ) FRE Q 

## B W Slowl yChangin g (FL AII ) FRE Q 

## B W

I F • *- • 3 / 

### Variation — Du e To :

t o

- j i 

### Test s (o T 

### ) 2

Observer s ( o )

2 Erro r ( o ) Estimate d 

## 5 / Correlation — Betwee n Tw o Six-Minut e DIFT MObser

vation s (p ) 51. 2 107. 6 16. 3 21. 5 39. 4 82. 0



## .6 3 .6 1 56. 1 205. 2 5503. 4 8731. 9

25. 8 33. 1 6003. 3 3970. 7 120. 4 118. 1 7224. 1 6398. 4



## .4 0 .6 7 .6 1 .6 6 3203. 3 3187.4 4329. 9 2937. 9 481. 3



## .7 2 35
. 9-1 /



## .8 7

1/ 

# y ii

5 / B = Black ; W= White
. S W= Stopwatch ; FRE Q = Frequency . Tim e i n second s squared
. Al l varianc e component s significan t a t th e 1 % (99 % confidence ) leve l fo r amon g observer s o n Florid a I I whit e smoke
. 2 2 2 2 2 p = (aTM + o 0 

### )/(° T

### + a + ° e 

### ) - correlatio n betwee n tw o si xminut e DIFT M observation s byth e sam e observe r unde r th e sam e tes t conditions
.P.3 0



## Assumin g tha t a one-hou r observatio nperio d i s th e su m o f 1 0 six-minut e test s wher e neithe r th e observe r no r th e tes t condition s change , then : d ) Th e averag e valu e (E ) o f th e differenc e betwee n th e observe d time and transmissomete r time i n exces s 20 % opacit yfo r a one-hou r (one-hour DIFTM ) observatio nperio d is : E(1-hou r DIFTM ) = 10B , wher e B = th e averag e bia s o f th e metho d fo r si xminutes ,

= E (6-min
. DIFTM)
. e ) Th e varianc e o f th e one-hou r DIFTMis :

V(l-hr
. DIFTMJ-i- 7 

## = 10(l+9p ) V(6-min
. DIFTM) , wher e

—1-hr
. DIFTM= th e su mo f 1 0 six-minut e DIFTM s fo r th e same observe r an

d tes t condition s 1 0
= 10 B + 1 0 T . + 1 0 0
. + T E . .. . i 3 h= 1 

## in * I t follow s that : V(l-hr
. DIFTM ) = 10 0 a*+ 10 0 a*+ 1 0 oj *

= 10( 1 + 9p ) V(6-min
. DIFTM)
.

-28

-P.3 1



# L 

# t L L p •** * th e correlatio n betwee n tw o six-minut e DIFTM s

= (a T

### + 0 o 

### )/(a T

### + a Q 

### -+ a E

### )
. Equation s (d ) an d (e ) abov e give , respectively , th e
amoun t o f tim e bia s an d th e varianc e abou t tha t bia s fo r a n observe r lookin g a t a plum e fo r on e hour
. Th e choic e o f a one-hou r observatio n perio d i s chose n a s a n example
. Unde r th e sam e assumptions , th e tim e bia s an d varianc e ma yb e derive d fo r a n arbitrar yobservatio n perio d o f Wminutes
. Th e derivatio n proceed s a s follows : f ) Th e averag e valu e o f th e differenc e betwee n th e observe d an d transmissomete r tim e i n exces s o f 20 % opacit yfo r a W-minut e observatio n perio d is : E(W-rain
. DIFTM ) = (|)B , wher e B = th e tim e bia s i n a six-minut e observa

tio n period , an d W= th e lengt ho f th e observatio n period
. g ) Th e varianc e i n th e W-minut e DIFT Mis :

V(W-min
. DIFTM ) = (| ) [l+(|-l)p]V(6-min

. DIFTM ) Continuin g wit hth e one-hou r observatio n perio d exam ple , an d assumin g tha t th e sumo f th e 1 0 six-minut e test s (i.e. , th e one-hou r DIFTM ) ca n b e approximate d b ya norma l distribution , the n th e uppe r 9 5 percentag e poin t o r uppe r confidenc e limi t (UCL ) o f th e one-hou r DIFT Mdistributio ni s give n a s follows :

-29

-P.3 2



# [ • t h 

# r

h ) Th e Uppe r 95 t h

## Percentag e Poin t (UCL ) o f a one T hou r DIFTMis :

r UC L ="10 B + 1.64 5 yl V(l-hr
. DIFTM ) wher e 1.64 5 i s th e uppe r 9 5 percentag e poin t o f J th e norma l (0,1 ) distribution
. Unde r th e assump tio n o f normality , percentag e point s ar e easil y calculate d b

yusing th e mea n and varianc e o f th e norma l distributio nan d th e percentag e point s o f th e norma l (0,1 ) distributio n (see , fo r example : Dixon , W . J. , an

d Massey , F . J . Jr. , Introductio n t o Statistica l Analysis , McGraw-Hil l Boo k Company , Inc. , Second Edition , 1957)
. Th e quantit ygive n i n (h ) ha s the propert ytha t 95 % o f th e one-hou r DIFTM s wil l b e belo wit
. Tha t is , 95 % o f th e error s i n th e estimate d time duratio ni n exces s o f 20 % opacit ywil l b e belo wth e quantit ygive nb y(h ) whe nth e observatio n perio d i s on e hour
. I n general , th e 9 5 percentag e poin t (UCL ) fo r a n observatio n perio d o f W-minute s i s give nby : i ) UC L - (^r)B + 1.64 5 . WV(W-min
. DIFTM )
.

+ • V i 

### Th e uppe r 9 5 percentag e poin t o f th e one-hou r DIFT M distributio n ca n b e use d t o establis ha 95 % confidenc e leve l fo r a standar d (S)
. Suppos e th e tru e tim e i n exces s o f 20 % opacit yi s les s tha n th e standar d S ; tha t is , RTIM E < S . Now , DIFT Mi s les s tha n th e derive d UC L 95 % o f th e time
. Therefore , on e i s 95 % confiden t tha t -30

-P.3 3



# r i 

## DIFTM< UCL , I bu t DIFTM= OTIM E - RTIME ; T therefore , OTIM E - RTIM E < UCL ,

bu t RTIM E < S b yassumption ; [ therefore , OTIM E - RTIM E > OTIM E - S , 

# [ 

# 1 s o OTIM E - S < UCL . Therefore , on e i s 95 % confiden t tha t th e standard ha s bee n exceede d if:
. j ) OTIME > S + UCL . I So , i f the actua l time i n exces s o f 20 % opacit yi s les s

tha n th e standard (S) , the nth e observe d time i nexces s o f 20 % opacit y(OTIME ) wil l b e les s tha n th e standar d plu s th e 

# I [



# I L

L L DIFT M9 5 percentag e poin t 95 % o f the time
.

5. 2 Classificatio n o f Plume s j I n orde r t o us e th e above , on e mus t kno w(o r estimate ) th e six-minut e bia s (B ) an d th e six-minut e varianc e (V(6

- I min
. DIFTM))and correlatio n(p) ; however , Table s 4 an d 7 sho wtha t thes e quantitie s varyb ysmok e typ e (BLAC K o r WHITE ) an

d b yplum e opacit ypatter n(rapidl ychanging , [ ' continuous , slowl ychanging)
. Therefore , fo r a particula r

smok e typ e on e mus t eithe r kno wth e plum e opacit ypatter n prio r t o observatio no r b e abl e t o classif yth e plume
r opacit ypatter n subsequen t t o observation
. W e hav e attempte d t o defin e a simpl e metho d o f classi

I fying a plume subsequen t t o observatio nb yus e o f th e

-31

-P.3 4



## standar d deviato n (0SD9)

—o f th e observe d opacities
. Specifically , th e plum e opacitie s wer e classifie d a s rapidl y changing , continuou s (no t changing) , o r slowl ychanging i f th e standar d deviatio n(0SD9 ) o f th e observe d opacitie s (2 4 opacitie s fo r eac hobserve r fo r eac hsix-minut e test ) satisfie d th e inequalitie s o f Tabl e 8
. Tabl e 8
. Plume Classificatio nRul e Classif yth e Plume Opacit yChang e As : If : Rapi d 0SD 9 > 15 % Continuou s (N

o Change ) 0SD 9 < b % Slo w5 % < 0SD 9 < 15 %
Th e choic e o f th e 0SD 9 brea k point s wa s suggeste d b ya visua l examinatio n o f th e dat a and , therefore , th e break

point s ar e somewha t arbitrary
.



# T7 ~ , 2 4 , 0SD 9 = ±r

£ (x
. - xP , Z J 

## i= l 1 

## x . - th e observe d opacit yfo r th e i interva l 1 

## (i=l,2,...,24) ;
x= th e averag e observe d opacit yove r th e si xminute s (twenty-four 15-second intervals)
.

-32

-

# i i [
[ 

# r c t L L 

# t Usin g th e abov e classificatio n rule , eac hobserver' s

tes t result s wer e classifie d int o on e o f th e thre e cate

gories
. Th e result s o f th e classificatio n ar e give n i n Tabl e 9
. Tabl e 1 0 present s th e classificatio n result s b y smok e type . Tabl e 9
. Classificatio n o f Plume s byOpacit yPatter n Classifie d Plum e Actua l Plum e Rapi d Continuou s Slo wTota l Rapidl yChangin g 37 7 2 19 1 57 0 Opacit y(RTP ) (66.1% ) (<1% ) (33.5% ) (100.0% ) Continuou s 0 33 4 2 6 36 0 Opacit y(FL

AI ) (0% ) (92.8% ) (7.2% ) (100.0% ) Slowl yChangin g 7 3 2 14 1 18 0 Opacit y(FL

AII ) (3.8% ) (17.8% ) (78.3% ) (100.0% )

A s i s see n fro mTabl e 9 , i t i s rar e tha t a plum e o f continuou s o r slowl ychangin g opacit yi s classifie d a s a plum e o f rapidl ychangin g opacit y(0 % an d 3.8% , respec tively )
. I f i t i s assume d tha t tim e duratio n estimate s wil l onl yb e use d fo r plume s classifie d a s havin g rapidl ychang

in g opacit y(OSD 9 > 15%) , the n th e classificatio n rul e will :
a ) disallo wusin g th e tim e duratio n metho d i n approximatel y1/ 3 o f th e case s wher e th e plum e opacit ypatter n i s actuall ychangin g rapidl y (193/570 ) an d b ) rarel yallo wit s us e whe n th e plum e opacit y patter n i s continuou s o r slowl ychangin g (^15%)
.

-33

-P.3 6



# r Tabl e 10
. Classificatio no f Plume s int o Plum e Opacit yPatterns — o n th e Basi s o f Observe d Opacit yStandar d Deviation s (OSD9 ) Classifie d Plume Opacit yPatter n

Blac k Smok e 1 /

Actua l Plume Opacit yRapi d Continuou s Slo w Rapidl yChanging Opacit y(RTP ) Continuou s Opacit y(FL

AI ) Slowl yChangin g Opacit y(FL

AII ) 14 5

(61.7% ) 0 (0.0% ) 5 (5.6% ) 1

(0.4% ) 17 6 (97.8% ) 1 5 (16.6% ) 8 9

(37.8% ) 4 (2.2% ) 7 0 (77.8% ) Tota l

23 5 (100.0% ) 18 0 (100.0% ) 9 0 (100.0% )
IJ

•• /

• 

## Rapidl yChanging

Opacit y(RTP ) Continuou s Opacit y(FL

AI ) Slowl yChangin g Opacit y(FL

AII ) Whit e

23 2 (69.2% ) 0 (0.0% ) 2 (2.2% ) Smok e

1 (0.3% ) 15 8 (87.8% ) 1 7 (18.9% ) 10 2

(30.5% ) 2 2 (12.2% ) 7 1 (78.9% ) 33 5

(100.0% ) 18 0 (100.0% )

. 9 0 (100.0% )

—Plum e Opacit yPatter n= Rapidl yChanging i f OSD 9 > 15 % Opacity ;
= Continuou s i f OSD 9 < 5 % Opacity ; an d
= Slowl yChanging i f 5 % < OSD 9 < 15 % Opacity
. ~ "

-34

-

## 5. 3 Calculatio n o f 95 % Confidenc e Limit s



# [ [ 

# L L I I n sectio n 5. 1 w e discussed , i ngeneral , th e computa

tio n o f 95 % confidenc e limits
. Sectio n5. 2 gav e a rul e t o assis t i n determining a plume' s opacit ypatter n (rapidl y changing , continuous , slowl ychanging ) subsequen t t o obser

vation
. Thi s sectio n give s th e 95 % confidenc e limit s fo r a one-hou r DIFTMcalculate d using formul a h ) o f sectio n5.1*
. Th e limit s (in minutes/hou r o f observation ) ar e summarize d i n Tabl e 1 1 wit hTable s 1 2 an d 13 , a t th e en

d o f thi s section , giving 95 % confidenc e limit s (an d th e detail s require d fo r thei r computation ) fo r bot hth e situatio nwher e th e plum e opacit ypatter n i s know nan d th e situatio nwher e th e plum e opacit ypatter n mus t b e classifie d subsequen t t o observation
. Tabl e 11
. Confidenc e Limit s o nOne-Hou r DIFTMb yMethod , Plume Opacit yPattern , Smok e Type , an d Patter n Classificatio n

Method-- 7 

## S W
F
F
F Plume

Opacit y Patter n Rapi d Rapi d Continuou s Slo w Smok e

Typ e Blac k Whit e Blac k Whit e Blac k Whit e Blac k Whit e Patter n

2 / Known- 7 

## 2. 4 min/hr
. 4.0

- 3. 2 5. 9 11. 0 33. 9 21. 0 23. 3 Patter n

Classified-- 7 

## 4 / 

## 7 / 5. 2 min/hr
. 5. 8 10. 9 33. 2 21. 4 19. 6

—S W= ' Stopwatch ; F = Frequency .

- / 

## Se e Tabl e 12
. ' 3 / 4 / Se e Tabl e 13
. Plume opacit ypatter n canno t b e classifie d whe nth e stODwatc hmetho d i s used
.
-35

-P.3 8



## An exampl e i s no wgive ni n constructin g a 95 % confi

denc e limi t a s give n i n Tabl e 1 1 and it s us e fo r establishin g limits , o na one-hou r standard
. Specifically , w e assum e a whit e plum e classifie d a s rapidl ychanging (0SD 9 > 15 % opacity) , a nobservatio nperio d o f on e hou r and
a standar d o f 20 % opacit yno t t o b e exceede d fo r mor e tha n on e minut e i n on e hour
. .Amon g th e 23 4 observation s o n whit e smok e whic h satisfie d th e 15 % opacit ystandar d deviatio nclassificatio n rule , i t wa s observe d that : 6-min
. DIFTMMea n=8. 5 second s (Tabl e 13) , an d 2 6-min
. Varianc e = 36 1 second s (Tabl e 13)
. Fo r th e whit e rapidl ychanging plumes , a correlatio n o f p=0.6 7 betwee n six-minut e DIFTMobservation s (sam e observer , sam e tes t conditions ) wa s estimate d (Tabl e 4)
. Usin g formul a (d ) o f sectio n 5. 1 fo r th e one-hou r bia s an d (e ) o f sectio n 5. 1 fo r th e one-hou r variance , on e calculate s th e following : One-hou r bia s = 10 B = 10(8.5 ) = 85. 0 seconds
. One-hou r varianc e = 10(l+9p)V(6-min
. DIFTM )

= 10(l+9(.67))(361 )

2 = 25378. 3 se c . Therefore , th e 9 5 percentag e poin t fo r a one-hou r DIFTM , from(h) , is :
UC L = 85+1.64 5 ^(25378.3 )

= 347. 0 seconds
.

-36

-P.3 9



# L L L L I n minutes , thi s gives : UC L =.347.0/6 0 = 5. 8 minutes/hou r o f observation
. Usin g (j ) o f sectio n5.1 , on e i s 95%
. confiden t tha t th e one-minut e standard ha s bee n exceede d if : OTIM E > S + UCL , substituting fo r S an d UC L w e have , OTIM E > 1. 0 + 5. 8 = 6. 8 minute s i n1 hour
. Fromthe abov e arguments , i t i s clea r tha t differen t confidenc e limit s ar e appropriat e fo r differen t observatio n times , an

d thes e mayb e calculate d using formula s (i ) an d (j ) o f sectio n 5.1
.

-37

-

## Tabl e 12
. Means , Standard Deviation s an d 95 % Confidenc e Limits

—o f DIFTMfo r On e Hour' s Observatio nEstimate d fro mSi xMinut e Test s b yPlume Opacit yPattern , Smok e 2 / 3 / Type

—an

d Observatio n Method — Rapidl y Changing (RTP ) S W B W Rapidl y

Changing (RTP ) FRE Q B W Continuou s

(FL AI ) FRE Q B W Slowl y Changin g (FL AII ) FRE Q B W

« u i 0 0 

## Mean On e Hour- ^ DIFT M (in seconds/hr. ) 5 / Standard Deviation

—o f On e Hou r DIFTM(i

n seconds/hr. ) 6. 1 50. 1

83. 5 116. 1 33. 8 97. 2-1110. 0194. 0-143. 0503. 0

. 6 / 

## On e Hour 95 % Confidence

Limi t fo r DIFTM(i

n seconds/hr. ) 143. 5 241. 1 On e Hou r 95 % Confidenc e Limi t fo r DIFTM(i

n min./hr. ) 2. 4 4. 0 

## 95. 7 157. 0

191. 3 355. 4

3. 25. 9 1077. 0 1118. 0 854. 5 545. 9

661. 8 2033. 1 1262. 6 1401. 1

11. 0 33. 9 21. 0 23. 3 

# J7 "

5 / Th e estimate d 9 5 percentag e poin t fo r DIFTM ; i.e. , Probabilit y(DIFT M£ Confidenc e Limit ) = .9 5 an

d an observe d time (OTIME ) mayb e sai d t o excee d a on e hou r standar d a t the 95 % leve l o f confidenc e i f OTIME > STANDARD + 95 % DIFTMConfidenc e Limit
. B = Blac k Smoke ; W= Whit e Smoke
. SW= Stopwatch ; FRE Q = Frequency . Estimate d On e Hour Mea nDIFTM= 1 0 xSi xMinut e Mea nDIFTM(Tabl e 4)
. Standard Deviatio n o f On e Hou r DIFTM= th e standar d deviatio no f a su mo f 1 0 correlate d si xminute s DIFTM s

6 / 

# • V1 0 (SixMinut e Standar d Deviation ) ( 1 + 9p) , an d p i s th e correlatio nbetwee nsi xminut e DIFTM s give ni nTabl e 4
. Critica l Valu e = On e hou r DIFTMMean+ 1.64 5 On e Hou r DIFTMStandar d Deviation
.I

U ) v o I 

## Tabl e 13
. Means , Standard Deviation s an d 95 % Confidenc e Limit s fo r th e Classifie d Plume s b ySmok e Typ e an

d Classificatio n Plume Classificatio n 1 /

Si xMinute s (tim

e i nseconds/6-min. ) RTIM E Mea n DIFTMMea n DIFTMStandard Deviatio n N Estimate d On e Hou r (tim e i n sec./hr. ) 

# 17 " DIFTMMean- 7 

## DIFTMStandard Deviation — 4 / On e Hou r 95 % Confidenc e Limit — I n seconds/hr
. I n minutes/hr
. 5 / Rapi c Chan c B! >


## 15 7 5. 4 23. 3 15 0

54. 0 157. 8
313. 5 5. 2 Ily jing W



## 12 8 8. 5 19. 0 23 4

85. 0 159. 2
346. 9 5. 8 Continuou s

B

25 4 -112. 2 134. 0 19 2

-1122. 0 1079. 7
654. 1 10. 9 W

19 8 19. 5 131. 0 17 6

195. 0 1091. 1
1989. 8 33. 2 Slowl yj

Changin g B
18 3 1. 6 51. 0 16 3

16. 0 441. 2
741. 7 12. 4 W

19 0 30. 1 56. 6 19 5

301. 0 531. 6
1175. 4 19. 6

4 / Plume Opacit yPatter n= Rapidl yChanging i f OSD 9 > 15 % Opacity ;
= Continuou s i f OSD 9 < 5 % Opacity ; an d
= Slowl yChanging i f 5 %
_ < OSD 9 <

_15 % Opacity
. B = Blac k Smoke ; W= Whit e Smoke
. On e Hour DIFTMMea n= 1 0 xSi xMinut e DIFTMMean . On e Hour DIFTMStandard Deviatio n 

# • 4 1 0 (SixMinut e Standard Deviation ) ( 1 + 9p) f 

## 5 / an d p i s the correlatio n betwee nsi xminut e DIFTM s give ni nTabl e 4
. • 4

- V* \ 

## Th e estimate d 9 5 percentag e poin t fo r a DIFTMclassifie d b yOSD 9 an

d equal s On e Hou r DIFTMMea n + 1.64 5 On e Hour DIFTMStandard Deviation , i.e. , Probabilit y(DIFT M<

_ Con

fidenc e Limit ) = .9 5 an d an observe d time (OTIME ) mayb e sai d t o excee d a on e hou r standard a t the 95 % leve l o f confidenc e i f OTIME > STANDARD + 95 % Confidenc e Limit
.P.4 2 

# r

L [ t L L 5. 4 Statistica l Powe r

Upo n computing the 95 % confidenc e limit s fo r th e classifie d plumes , statistica l powe r wa s calculated
. Specifically , wha t wa s calculate d wa s th e amoun t o f time i n exces s o f 20 % opacit ywhic hcoul d b e detecte d a t specifi c level s o f probabilit yi f th e limit s o f Tabl e 1 1 ar e use d t o establis hadherenc e t o a time duratio nstandard
. Thes e powe r calculation s ar e give n i n Tabl e 14
. A s anexampl e i n th e us e o f Tabl e 14 , suppos e w e hav e a blac k plume classi

fie d a s rapidl ychanging (OSD 9 > 15% ) and th e standar d i s S second s pe r hour
. Tabl e 1 4 say s tha t i f th e sourc e i s reall ygenerating S + 127. 0 second s pe r hou r i n exces s o f 20 % opacity , the nth e probabilit yi s 0.2 0 tha t anobserve r wil l recor d a time duratio ni n exces s o f th e 95 % confidenc e leve l ( S + 313. 5 seconds , Tabl e 11)
. I t i s see n fromTabl e 1 4 tha t th e lo wprecisio ni n estimatin g time duratio n=*_20 % opacit yfo r continuou s an d slowl ychanging plume opacit ypattern s require s verylarg e 95 % confidenc e limit s and , consequently , provide s poo r powe r i n detectin g actua l time i n exces s o f 20 % opacity
.

-40

-

# f P.4 3



## Tabl e 14
. 

# r r

I L L [ 

# I Th e .Amount s o f Tim e (inSeconds/Hour ) i nExces s o f 20 % Opacit yWhic hCa nB e Detecte d a t Specifi c Level s o f Probabilit y(Statistica l Power ) Usin g th e Confidenc e Limit s o f Tabl e 1 1

Probabilit y Leve l .0 5 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 0 • 

## Plume Opacit yPattern — Rapidl yChanging 

# _£' 

# W 0 57. 6 127.0- / 

## 177. 5 220. 1 259. 5 298. 9 341. 5 392. 0 461. 4 0

58. 1 128. 2 179. 1 222. 1 261. 9 301. 7 344. 7 395. 7 465. 7 Continuou s

B 0 394. 1 869. 1 1214. 6 1506. 1 1776. 1 2045. 9 2337. 5 2683. 0 3158. 0 W 0

398. 2 878. 3 1227. 5 1522. 0 1794. 8 2067. 6 2362. 2 2711. 3 3191. 4 Slowl y

B 0 161. 0 355. 1 496. 3 615. 4 725. 7 836. 0 955. 1 1096. 3 1290. 4 Changin g

W 0 '194. 0 427. 9 598. 0 741. 5 874. 4 1007. 3 1150. 8 1321. 0 1554. 8

—Plume Opacit yPatter n = Rapidl yChanging i f OSD 9 > 15 % Opacity ;
= Continuou s i f OSD 9 < 5 % Opacity ; an d
=• Slowl yChanging i s 5 % <

_OSD 9 <

_15 % Opacity
.

— ' B = Blac k Smoke ; W=• * Whit e Smoke
. A s a n exampl e in.th e us e o f thi s table , suppos e th e time exemptio n standard i s S seconds.i n on e hour , th e smok e i s blac k and rapidl ychanging (OSD 9 > 15 % Opacity)
. Then , i f th e sourc e i s actuall ygenerating S + 127. 0 second s pe r hou r i nexces s o f 20 % opacit yth e confidenc e limi t o f S + 313. 5 (Tabl e 11 ) wil l b e exceede d wit hprobabilit y.20
. 2/ 

## 3 /

-41

-P.4 4



### 6. 0 CONCLUSION S

I n thi s repor t i t ha s bee n show n that : (a ) Plum e opacit ypatter n a s measure d b yopacit y variabilit y(RSD9 ) an d smok e typ e (blac k o r white )
ar e importan t factor s i n estimatin g tim e duratio n i n exces s o f 20 % opacit y(Table s 4 an d 5)
. (b ) Les s importan t factor s ar e metho d o f observation , numbe r o f plum e peaks , an d pea k widt h(Tabl e 6)
. (c ) Plum e opacit ypattern s ca n b e reasonabl ytype d by th e observe d opacit yvariabilit y(OSD9) , bu t thi s techniqu e ca n onl yb e use d fo r th e FREQUENC Y metho d o f observatio n (Table s 9-10)
. (d ) Compute d 95 % confidenc e limit s fo r continuou s an d slowl ychangin g plum e opacit ypattern s ar e larg e du e t o th e poo r precisio n o f estimatin g tim e duratio n i n exces s o f 20 % opacit yfo r thes e typ e plume s (Tabl e 11-13)
. (e ) Th e larg e 95 % confidenc e limit s fo r continuou s an d slowl ychangin g plum e opacit ypattern s lea d t o lo w statistica l powe r (Tabl e 14)
. (f ) Fo r continuou s plumes , th e statistica l powe r i s s o lo wtha t i t seem s unlikel ytha t shor t excursion s abov e 20 % opacit ycoul d b e detecte d (Tabl e 14)
.

-42

-P.4 5



## (g ) Fo r th e thre e plum e opacit ypatterns , classi c metho d 9 (0M9 ) tes t mean s correlate d wel l wit hth e corresponding transmissomete r metho d 9 (RM9 ) valu e (Figur e 8)
.



# L L -43

-P.4 6



## REFERENCE S
[1 ] Intermitten t Opacit yMethod/Fiel d Experiment , Contrac t no . 68-01-5110 , Tas k Orde r No . 19
. Prepare d b yDe l Gree n Associates , Inc. , Foste r City , CAfo r USEPA , Divisio n o f StationarySourc e Enforcement , Researc h Triangl e Park , NC , 1981
. [2 ] Evaluatio n o f Opacit yFrequenc yMetho d o n Continuou s Plumes , Contrac t no . 68-01-5110 , Tas k Orde r No . 26
. Prepare d b

yDe l Gree n Associates , Inc. , Foste r City , CA fo r USEPA , Divisio no f StationarySourc e Enforcement , Researc hTriangl e Park , NC , 1981
. [3 ] Evaluatio n o f Opacit yFrequenc yMetho d o nSlowl y Changin g Plumes , Contrac t no . 68-01-5110 , Tas k Orde r No . 34
. Prepare d b yDe l Gree n Associates , Inc. , Foste r City , C

Afo r USEPA , Divisio no f StationarySourc e Enforcement , Researc hTriangl e Park , NC , 1981
.



# L

-44

-P.4 7 

# I

APPENDI XA DATAAPPENDI X



# L 1 A- lP.48 ^



# r NUMBE R

PARTI C PEA K PEAK-WI D OTIM E RTIM E
OM 9

RM 9 RIS E AMOUNT DEFINITION S

Tes t Numbe r Observe r Numbe r Numbe r o f Peak s Pea k Widt h Estimate d Tim e j>20 % Opacit yi n Second s Transmissomete r Time ^20 % Opacit yi n Second s Averag e Observe d Opacit y(canno t b e compute d fo r STOPWATC H method ) Averag e Transmissomete r Opacit y Fo r th e Florid a I I data , the chang e i n opacit yove r th e si xminut e observatio n period
. RIS E = + o r - depending o nth e opacit yincreasing o r decreasing an d AMOUNT = 20% , 30% , 40%
.

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TABL E A-l

. RT P STOPWATC H SELECTE D VARIABLE S B YCOLO R &SPEE D

OBS 11. 3 13 4 13 5 10 6 10 7 IC S 1C 9 11 0 11 1 11 2 11 3 

### 11 4 NUMBE R

1 9 1 9 1 9 1 9 1 9 1 9 2 0 2 0 2 0 2 0 2 0 2 0 PARTI C

2 2 2 3 2 4 2 5 2 6 2 7 2 2 2 3 2 4 2 5 2 6 2 7 COLOR =

PEA K

1 3 3 3 3 3 T . 3 3 3 3 3 BLAC KSPEE D

PEAK_UI D 1 5 1 5 1 5 1 5 1 5 1 5 3 0 3 0 3 0 3 0 3 0 3 C O.TIrl E

3 5 5 3 5 C 5 5 5 1 5 3 8 6 9 3 9 3 9 2 9 0 9 1 RETIM E

4 5 4 5 4 5 4 5 4 5 4 5 9 0 9 0 9 0 9 0 9 0 9 0 RM 9

10.041 7 10.041 7 10.041 7 10.041 7 10.041 7 10.041 7 14.125 0 14.125 0 14.125 0 14.125 0 14.125 0 14.125 0



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### TABL E A-l . RT P STOPWATC HSELECTE DVARIABLE S B YCOLO R& SPEE D



### OB S 21 7 21 8 21 9 22 0 22 1 22 2 22 3 22 4 22 5 NUMBE R

3 9 3 9 3 9 3 9 4 0 4 0 4 0 4 0 4 0 PARTI C

2 3 2 4 2 5 2 7 2 2 2 3 2 4 2 5 2 7 L,DLUK=B L



### PEA K AC K5PtLU = 

### PEAK_UI D 3 0 3 0 3 0 3 0 6 0 6 0 6 0 6 0 6 0 0_TIME

4 4 

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### 1 0

OE S 37 9 38 C 38 1 38 2 3 8 3 38 4 38 5 38 6 38 7 38 8 38 9 39 0 39 1 39 2 NUMBE

R 7 ? 7 9 14 2 14 2 14 2 14 2 14 2 14 2 16 5 16 5 16 5 16 5 16 5 16 5 PARTI C

2 6 2 7 2 2 2 3 2 4 2 5 2 6 2 7 1 4 2 2 2 3 2 5 2 6 2 7 COLOR=UHIT E PEA KP E 2 2 2 2 2 2 2 2 2 2 2ro 

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15 8 15 5 15 9 15 9 16 2 15 6 15 5 16 5 16 3 16 5 16 2 15 2 16 4 R_TIM

E 15 0 15 0 15 0 15 0 15 0 15 0 15 C 15 0 16 5 16 5 16 5 16 5 16 5 16 5 RM

9 26.833 3 26.833 3 32.416 7 32.416 7 32.416 7 32.416 7 32.416 7 32.416 7 29.625 0 29.625 0 29.625 0 29.625 0 29.625 0 29.625 0

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### TABL E A-l . RT P STOPWATC HSELECTE DVARIABLE S B YCOLOR& SPEE D 

### 1 4

OB S 54 6 54 7 54 8 54 9 55 0 55 1 55 2 5 5 3 55 4 NUMBE R



## ° 9 9 9 10 0 10 0 IO C 10 0 17 5 17 5 17 5 COLOR=UHIT E SPEED=INT E

PARTI C PEA

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2 2 2 2 2 3 3 3 9 0

9 0 3 0 3 0 3 0 3 0 6 0 6 0 6 0 20 4

17 0 6 1 6 1 7 8 5 3 21 7 19 6 19 3 R_TIM E



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a1 1 1 4 5

4 5 4 5 4 5 4 5 45

- 9 0 ' 9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0 9 0 7 5 7 5 7 5 7 5 7 5 7 5 7 5 7 5 7 5 7 5 7 5 7 5 4 5 4 5 4 5 4 5 4 5 4 5 7 5 7 5 7 5 7 5 7 5 7 5 6 0 6 0 6 0 6 0 6 0 6 ? 1 5 1 5 1 5 ortatu- r M Oi

0_TIM E 4 5 4 5 4 5 4 5 4 5 4 5 27 0 27 0 27 0 27 0 27 0 27 0 24 0 22 5 22 5 22 5 24 0 22 5 22 5 22 5 22 5 22 5 22 5 22 5 15 0 15 0 15 0 15 0 15 0 15 0 13 5 13 5 16 5 13 5 13 5 13 5 7 5 6 0 7 5 7 5 7 5 7 5 19 5 21 0 19 5 19 5 19 5 19 5 1 5 1 5 1 5

A-1 7 R_TIM E

4 5 4 5 4 5 4 5 4 5 4 5 27 0 27 0 27 0 27 0 27 0 27 0 24 0 24 0 24 0 24 0 24 0 24 0 22 5 22 5 22 5 22 5 22 5 22 5 15 0 15 0 15 0 15 0 15 0 15 0 13 5 13 5 13 5 13 5 13 5 13 5 7 5 7 5 7 5 7 5 7 5 7 5 19 5 19 5 19 5 19 5 19 5 19 5 1 5 1 5

• 1 5 0M 9

12.500 0 13.958 3 11.458 3 10.C00 0 10.833 3 11.875 0 51.250 0 63.750 0 49.375 0 41.457 0 54.164 1 45.000 0 41.457 0 55.000 0 33.332 0 34.789 1 50.000 0 35.625 0 43.750 0 55.414 1 3 0.832 0 35.000 0 48.539 1 36.664 1 25.414 1 39.125 0 17.707 0 23.332 0 27.7C7 0 21.875 0 26.875 0 34.582 0 23.332 0 24.375 0 29.375 0 24.582 0 14.166 5 15.416 5 11.875 0 13.958 3 11.875 0 13.125 0 38.539 1 50.000 Q 28.539 1 31.250 0 40.000 0 31.250 0 5.208 3 5.000 0 4.791 5 TTT-' . .

1 5

RM 9 11.291 5 11.291 5 11.291 5 11.291 5 11.291 5 11.291 5 51.664 1 51.664 1 51.664 1 51.664 1 51.664 1 51.664 1 44.750 0 44.750 0 44.750 0 44.750 0 44.750 C 44.750 0 44.375 0 44.375 0 44.375 0 44.375 0 44.375 0 44.375 0 29.082 0 29.082 0 29.082 C 29.082 0 29.082 0 29.082 0 29.375 0 29.375 0 29.375 0 29.375 0 29.375 0 29.375 0 16.664 1 16.664 1 16.664 1 16.664 1 16.664 1 16.664 1 37.082 0 37.082 C 37.082 0 37"
. 0 8 2 0 37.082 0 37.082 0 7.250 0 7.2 5 3 0 7.250 0P.6 4

TABL E A-2 . RT P FREQUENC YSELECTE DVARIABLE S B YCOLO R& SPEE D 

## 1 6

S S 5 2 5 3 5 4 5 5 5 6 5 7 5 8 5 9 6 0 6 1 6 2 6 3 6 4 6 5 6 6 6 7 6 8 6 9 7 0 7 1 7 2 7 3 7 4 7 5 7 6 7 7 7 8 7 9 8 0 8 1 8 2 8 3 8 4 8 5 8 6 8 7 3 6 8 9 9 0 9 1 9 2 . 9 ? 9 4 9 5 9 6 9 7 9 8 9 9 2 **• : i ~:2 NUMEE R

9 9 a 1 3 1 0 1 0 1 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 J 1 2 1 2 1 2 1 2 1 2 1 2 1 3 1 3 1 3 1 3 1 3 1 3 1 4 1 4 1 4 1 4 1 4 1 4 1 5 1 5 1 5 1 5 1 5 1 5 1 7 1 7 1 7 1 7 1 7 1 7 1 8 1 8 1 8 18* 1 8 1 8 PARTI C

2 5 2 6 2 7 2 2 2 3 2 4 2 5 2 6 2 7 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 PEA K

1 1 1 3 3 3 3 3 3

t 2 2 . 2 2 2 2 3 3 3 3 3 3

2 o
a V 2 2 2 2 2 2 2 o 2 2 .O R= bLA(- K PEAK_WI D 1 5 1 5 1 5 4 5 4 5 4 5 4 5 4 5 4 5 6 0 6 3 6 0 6 0 6 C 6 0 9 0 9 0 9 0 9 C 9 0 9 0 1 5 1 5 1 5 1 5 1 5 1 5 6 0 6 0

. 6 0 6 0 6 0 6 0 9 0 9 0 9 0 9 0 9 0 9 C 9 0 9 0 9 0 9 0 9 0 9 0 7 5 7 5 7 5 7 5 7 5 7 5 SPLEaDSr * A !

0_TIM E 1 5 1 5 1 5 13 5 13 5 13 5 13 5 13 5 12 0 6 0 6 0 6 0 6 0 6 0 6 0 9 0 9 0 9 0 9 0 9 0 9 0 3 0 3 0 T f- 1 < v• » 3 0 4 5 3 0 18 0 18 0 18 0 18 0 18 0 18 0 9 0 9 0 9 0 9 0 9 0 9 0 18 0 18 0 19 5 18 0 18 0 18 0 15 0 15 0 15 0 1 5 0 15 0 19 5 R_TIM E

1 5 1 5 1 5 13 5 13 5 13 5 13 5 13 5 13 5 6 0 6 0 6 0 6 0 6 0 6 0 9 0 9 0 9 0 9 0 9 0 9 0 3 0 3 0 3 0 3 0 3 0

. 3 0 18 0 18 0 18 0 18 0 18 0 18 0 9 0 9 0 9 0 9 0 9 0 9 0 18 0 18 0 18 0 18 0 18 0 18 0 15 0 15 0 15 0 15 0 15 0 15 0 CM 9

6.253 0 3.958 3 7.291 5 21.250 0 27.082 0 15.833 3 18.539 1 24.375 0 17.914 1 14.375 0 10.625 0 8.958 3 8.958 3 11.041 5 8.541 5 19.789 1 18.164 1 11.666 5 14.583 3 19.375 0 10.833 3 9.375 0 9.375 0 8.541 5 7.500 0 14.166 5 7.291 5 34.164 1 32.500 0 20.625 0 21.664 1 26.875 0 22.082 0 20.625 0 19.375 0 13.333 3 i2.916 5 18.332 0 11.458 3 33.957 0 36.039 1 32.500 0 25.625 0 39.582 0 32.289 1 29.164 1 31.664 1 30.000 0 23.750 0 31.625 0 33.125 0 . RM 9

7.250 0 7.250 0 7.250 0 24.207 0 24.207 0 24.207 0 24.207 0 24.207 C 24.207 0 10.083 3 10.083 3 10.083 3 10.083 3 10.083 3 10.083 3 16.375 C 16.375 0 16.375 0 16.375 C 16.375 C 16.375 0 6.416 5 6.416 5 6.416 5 6.416 5 6.416 5 6.416 5 32.957 0 32.957 0 32.957 0 32.957 C 32.957 0 32.957 C 16.000 0 16.000 0 16.000 0 16.000 0 16.000 0 16.00C 3 36.832 0 36.832 0 36.832 0 36.832 C 36.832 0 36.832 0 29.750 0 29.750 0 29.750 0 29.750 0 29.750 0 2 9.750 ?

A-1 8P.6 5

TABL E A-2 . RT P FREQUENC YSELECTE D VARIABLE S B YCOLO R &SPEE D 1 7

5 8 S 

### 10 3 10 4 10 5 ;0 6 10 7 10 8 10 9 .1 0 11 1 .1 2 .1 3 .1 4 NUMBE R



### 1 9 1 9 1 9 1 9 1 9 1 9 2 0 

### 2 0 2 0 2 0 2 0 2 0 PARTI C



### 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 • PEA K



### 3 3 3 3 3 3 3 3 3 3 3 3 -UK** * BLAC K 

### PEAK_WI D 1 5 1 5 1 5 1 5 1 5 1 5 3 0 3 0 3 0 3 0 3 0 3 0 0_TIM E

4 5 4 5 6 0 4 5 4 5 4 5 12 0 . 9 0 9 0 9 0 9 0 9 0 R_TIM E

4 5 4 5 4 5 4 5 4 5 4 5 9 0 9 0 9 0 9 0 9 0 • 9 0 OM 9

10.833 3 11.458 3 13.125 0 8.541 5 10.208 3 13.541 5 20.207 0 14.166 5 13.750 0 10.208 3 13.125 0 16.039 1 RM 9

10.041 5 10.041 5 10.041 5 10.041 5 10.041 5 10.041 5 14.125 0 14.125 0 14.125 0 14.125 0 14.125 0 14.125 0



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### '2 4 :-25 :2 6 '2 7 '2 8 .2 9 ?3C •3 1 3 2 3 3 3 4 3 5 NUMBE R



### 3 7 3 8 3 8 3 8 3 8 3 8 3 8 3 9 3 9 3 9 3 9 3 9 3 9 4 0 4 0 4 0 4 0 4 0 4 0 PARTI C



### 2 6 1 1 1 2 1 3 1 4 1 5 2 6 1 1 1 2 1 3 1 4 1 5 2 6 1 1 1 2 1 3 1 4 1 5 2 6 PEA K



### 1 2 2 2 2 2 2 .Urv^tJLAtr v 

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60 . 12 C 12 0 12 0 12 0 12 0 12 0 3 0 3 0 3 0 3 0 3 0 3 0 7 5 7 5 7 5 7 5 7 5 7 5 0M 9

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### 7 0 7 0 7 0 14 2 14 2 14 2 14 2 14 2 14 2 16 5 16 5 16 5 16 5 16 5 16 5 PARTI C



### 1 5 1 6 2 4 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 5 1 6 2 4 PEA K



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1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 1 1 1 2 1 3 1 4 1 5 1 6 2 2 2 3 2 4 2 5 2 6 2 7 2 2 2 3 2 4 2 5 2 6 2 7 2 2 2 3 2 4 2 5 2 6 2 7 2 2 2 3 2 4 PEA KPEAK_WI D

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0_TIM E 16 5 13 5 15 0 15 0 13 5 13 5 4 5 3 0 3 0 3 0 ' 4 5 3 9 10 5 9 0 7 5 7 5 10 5 7 5 4 5 4 5 3 0 3 0 6 0 3 0 12 0 12 0 12 0 12 0 12 0 10 5 13 5 13 5 15 0 15 0 16 5 18 0 7 5 7 5 7 5 7 5 x 9 0 9 0 22 5 21 0 25 5 24 C 27 0 27 0 15 0 1 5 3 16 5 R.TIM E

12 0 12 C 12 0 12 0 12 0 12 0 3 0 3 0 3 0 3 0 3 0 3 0 7 5 7 5 7 5 7 5 7 5 7 5 3 0 3 0 3 0 3 0 3 0 3 0 10 5 10 5 10 5 10 5 10 5 10 5 12 0 12 0 12 0 12 0 12 0 12 0 7 5 7 5 7 5 7 5 7 5 7 5 19 5 19 5 19 5 19 5 19 5 19 5 9 0 9 0 9 0 0M 9

21.250 0 20.207 3 13.125 0 16.250 0 14.583 3 13.750 0 6.458 3 5.000 0 6.041 5 5.625 0 6.341 5 5.833 3 14.583 3 17.289 1 10.000 0 10.625 0 13.333 3 9.166 5 9.791 5 8.125 0 6.875 0 7.083 3 9.375 0 7.291 5 20.832 0 21.664 1 14.166 5 14.166 5 16.457 0 11.041 5 18.539 1 20.207 0 17.289 1 22.289 1 27.289 1 21.664 1 16.250 0 9.791 5 11.875 0 13.750 0 18.957 0 18.125 0 37.082 0 26.457 0 25.832 0 25.207 0 41.875 0 30.625 0 20.625 0 18.332 3 1 6 . 2 5 C 0 RM 9

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## 3 2

OB S 15 4 15 5 15 6 15 7 15 8 15 9 16 0 16 1 16 2 16 3 16 4 16 5 16 6 16 7 16 8 16 9 17 ? 17 1 17 2 17 3 17 4 17 5 17 6 17 7 17 8 17 9 180 ' NUMBE R

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1 4 1 5 1 6 1 7 1 8 1 9 2 0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 • COLOR=BLAC K

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APPENDI XB
DAT ASUMMARIES : MEAN S AN D SAMPL E SIZE S



# r L 

# L 

# L L B- lP.9 0



### DEFINITION S

SPEE D

PEA K PEAK-WI D PARTI C

RIS E AMOUN T

OTIM E 0TIME2 5 0TIME3 0 RTIM E DIFT M DIFTM2 5 DIFTM3 0 OM 9 RM 9 DIFM 9 Fas t (FAST ) o r intermediat e (INTER ) Plum e Ris e Tim e Th e numbe r o f Peak s Pe r Tes t Th e Pea k Widt hfo r Eac hPea k Th e Observe r Numbe r Assigne d (observe r number s uniqu e withi n th e thre e Fiel d Tests ) Fo r th e Florid a I I data , th e chang e i n opacit yove r th e six-mihut e observatio n period
. RIS E = + o r - dependin g o n th e opacit yincreasin g o r decreasin g and AMOUN T » 20% , 30% , 40 % Th e Observe d Tim e :>20 % Opacit y Th e Observe d Tim e >_25 % Opacit y Th e Observe d Tim e >_30 % Opacit y Th e Transmissomete r Tim e >_20 % Opacit y OTIME-RTIM E 0TIME25-RTIM E 0TIME30-RTIM E Th e Observe d Averag e Opacit y Th e Transmissomete r Averag e Opacit y OM9-RM 9

B- 2P.9 1



### TABL E B-l . MEAN S AN OSAMPL E SIZE S CN ) FORSEVERA L VARIABLE S B Y PEA KWIDTH S & PARTICIPANTS : BLAC KRT P STOPWATC HDATA

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L 

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D 1 5 3 0 4 5 6C 7 5 9 0

PARTI C 1 1 1 2 1 3 1 4 1 5 1 6 2 2 2 3 2 4 2 5 2 6 2 7

OVERAL L N 11 4 11 1

N 8 5 4 7 9 3

.. _ N 1 8 2 9 1 8 7 8 2 4 5 8

N 2 0 2 0 2 0 2 0 2 0 2 0 1 9 1 6 1 9 1 9 1 3 1 9

N 22 5 DIFTM25i /

DIFTH 3

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OIFTM2 5 0IFTM3 C

. . DIFT M -1.2 5 2.5 1

DIFT M 1.6 7 -0.1 9 0.0 4

- - —- DIFT M 4.6 7 3.0 3 1.7 2 2.3 7 -1.6 7

- -3.6 4

DIFT M 0.6 5 -3.6 0 5.0 0 -9.6 5 0.6 0 2.9 0 -2.6 8 5.5 6 2.3 7 2.6 8 1.4 6 3 . 47

DIFT M 0.6 1

—Calculatio ncoul dno tb emad efo rSTOPWATC

Hdata .
B- 3 RTIM E 126.3 2 121.0 8

RTIM E 61.2 4 123.8 3 180.8 1

RTIM E 30.0 0 54.8 3 105.0 0 126.9 2 150.C O 177.9 3

RTIM E 145.5 0 141.7 5 141.7 5 141.7 5 141.7 5 141.7 5 104.2 1 90.0 0 104.2 1 104.2 1 107.3 1 104.2 1

RTIM E 123.7 3 

## DlFH^y

.

.
DIFM9

.

.

.

- -• • 

### DIFM9

DI F 'M 9

DIFMS
• RM

9 24.6 5 .16.8 6

RM 9 10.7 2 20.6 2 30.1 2

.. . _.. . RM 9 7.9 0 8.5 2 21.6 2 19.4 7 29.9 7 28.7 0

RM 9 24.6 4 24.3 1 24.3 1 24.3 1 24.3 1 24.3 1 16.7 2 15.6 9 16.7 2 16.7 2 18.1 3 16.7 2

RM 9 20.8 0

.P.9 2 

# r
TABL E B-2 . MEAN S AN DSAMPL E SIZE S <N ) FORSEVERA L VARIABLE S B Y PEA KWIDTH S & PARTICIPANTS : WHIT E RT P STOPWATC HOATA



# r SPEE

D FAS T INTE
PEA K 1 2 3

PEAK„WI

D 1 5 3 0 4 5 6 0 7 5 9 0

PARTI C 1 1 1 2 1 3 1 4 1 5 1 6 2 2 2 3 2 4 2 5 2 6 2 7

OVERAL L N 16 7 16 2
N 8 6 13 0 11 3

N 1 2 9 8 2 4 IC I 3 5 5 9

N 2 9 2 9 3 0 3 8 3 0 3 0 2 7 2 7 1 5 2 7 2 1 2 6

N 32 9 DIFTM25-i /

. • DIFTM2 5

. •

.

0IFTH2 5

DIFTM2 5

•_, - _.
DIFTM25

. DIFTM3 0-' '

.

. DIFTM3 0
•

.

.

DIFTM3 0

DIFTM3 0

.. .
OIFTM3 0
• DIFT

M 1.3 8 8.7 5
DIFTM 1.9 9 4.4 7 7.9 4

DIFT M -4.4 2 11.4 0 9.4 6 3.1 1 2.7 4 -0.8 8

DIFT M 5.3 1 5.5 5 1.7 7 6.4 5 

## 11.e o -2.9 0 4.7 0 2.8 9 4.8 7 0.2 6 6.1 4 13.6 5

DIFT M 5.0 1 RTIM

E 121.8 9 •115.7 4
RTIM E 59.1 3 123.0 0 159.5 6

RTIM E 37.5 0 65.6 6 123.7 5 131.8 8 154.7 1 178.2 2

RTIM E 116.3 8 116.3 8 114.5 0 119.6 1 114.5 0 114.5 0 123.8 9 123.8 9 112.0 0 123.8 9 125.7 1 121.1 5

RTIM E 118.8 6 DIFMS-y

. •
DIFM 9
•

.

.

0IFM 9

DI F •M 9

DIFM9

. RM

9 23.4 1 15.2 7
RM 9 10.0 8 20.3 0 25.4 7

RM 9 8.2 1 10.3 3 23.7 9 20.6 9 30.1 1 26.4 1

RM 9 18.9 0 18.9 0 18.5 8 19.3 7 18.5 8 18.5 8 20.0 4 20.0 4 18.9 2 20.0 4 21.5 6 19.9 6

RM 9 19.4 0

— Calculatio

ncouldno

t b e mad e fo r STOPWATC

Hdata . 

## B-4

### TABLE B-3 . MEANS AN DSAMPLE SIZE S (N ) FO RSEVERA

L VARIABLE S B

Y PEA KWIDTH S & PARTICIPANTS : BLACKRT P FREQUENCYDAT A SPEED FAS T INTE
PEA K 1ro 

### 3 N

11 4 12 1
N 9 0 4 8 9 7 DIFTM2 5

-0.9 2 -14.0 1
DIFTM2 5 -5.3 3 -10.0 0 -8.6 6 DIFTM3 0

-4.7 4 -36.2 0
DIFTM3 0 -14.1 7 -22.1 9 -26.6 0 DIFT

M 0.6 6 5.9 5
DIFTM 2.1 7 3.7 5 4.3 3 RTIM

E 126.3 2 121.1 2
RTIM E 61.0 0 123.7 5 181.7 0 DIFM 9

-1.3 7 -1.6 5
DIFM 9 -1.1 4 -0.8 0 -2.2 1 RM

9 24.6 5 16.8 3
RM 9 10.6 3 20.5 0 29.9 6



### PEA K K_WI D 1 5 3 0 4 5 6 0 7 5 9 0 N

1 8 3 C 1 8 8 5 2 4 6 3 DIFTM2 5

0.0 0 -6.5 0 0.0 0 -11.6 5 -0.6 3 -10.0 0 „.. __..._ . .. .



### DIFTM3 C -5. 00 -15.5 0 -3.3 3 -28.7 6 -3.1 3 -29.7 5 .

DIFT M 1.6 7 1.0 0 0.8 3 5.8 2 1.2 5 3.2 5 —

RTIM E 30.0 0 54.0 0 105.0 0 124.7 6 150.0 0 180.0 0 • . .



### DIFM9 0.7 9 -0.6 0 -1.6 9 -1.7 2 -2.2 6 -2.0 3 —-

RM 9 7.9 0 8.4 4 21.6 2 19.0 7 29.9 7 28.7 0 

# [

; 

## [ | 

# 1 L \\ 

# I 

# [ 

# 1 L L [ PARTI C

1 1 1 2 1 3 1 4 1 5 1 6 2 2 2 3 2 4 2 5 2 6 2 7

OVERAL L N 1 9 1 9 1 9 1 9 1 9 1 4 2 0 2 0 2 0 2 0 2 6 2 0
N 23 5 DIFTM2 5

5.5 3 0.0 0 1.5 8 -17.3 7 -8.6 8 2.1 4 -13.5 0 -10.5 0 -3.7 5 -12.0 0 -5.7 7 -26.2 5

- - - - DIFTM2 5 -7.6 6 DIFTM3 0

-6.3 2 -10.2 6 -15.7 9

- 3 3.1 6 -28.4 2 -5.3 6 -21.0 0 -17.2 5 -28.5 0 -27.0 0 -11.5 4 -44.2 5
DIFTM3 0 -20.9 4

B

DIFT M 13.4 2 6.3 2 11.0 5 -1.5 8 6.3 2 12.8 6 -8.2 5 -1.5 0 3.7 5 1.5 0 5.1 9 -5.2 5
DIFT M 3.3 8

- 5 RTIM

E 100.2 6 104.2 1 104.2 1 104.2 1 104.2 1 116.7 9 141.7 5 141.7 5 141.7 5 141.7 5 131.5 4 141.7 5

RTIM E 123.6 4 DIFM9

1.5 7 0.9 1 -1.0 5 -4.4 2 -0.5 2 -0.9 8 -2.1 7 2.6 3 -5.3 8 -4.1 2 0.1 8 -5.0 0

DIFM9 -1.5 2 RM

9 16.3 7 16.7 2 16.7 2 16.7 2 16.7 2 19.0 3 24.3 1 24.3 1 24.3 1 24.3 1 21.8 5 24.3 1

RM 9 20.6 3P.9 4 

# r
TABLE E-4 . MEANS AN DSAMPLE SIZE S <N

> FO RSEVERA

L VARIABLE S B

Y
SPEE D FAS T INT E

PEAK 1 2 3

PEAK_WI D 1 5 3 0 4 5 6 0 7 5 9 0

PARTI C 1 1 1 2 1 3 1 4 1 5 1 6 2 2 2 3 2 4 2 5 2 6 2 7

OVERALL PEAKWIDTH S & PARTICIPANTS :

N 1 6 8 1 6 7

N 9 0 1 3 2 1 1 3

N 1 2 10 2 2 4 1 0 1 3 6 6 ?

N 2 7 2 6 2 5 1 7 2 7 2 5 3 0 3 0 3 8 3 0 3 0 3 0

N 33 5 DIFTM2 5

-1.3 4 -5.0 3

DIFTH2 5 -5.5 0 -4.5 5 0.2 7

DIFTM2 5 0.0 0 -2.0 6 -0.6 3 -1.1 9 -0.8 3 -11.5 0

0IFTM2 5 -3.3 3 0.5 8 -23.4 0 -7.9 4 1.6 7 -19.2 0 4.0 0 -0.5 0 4.3 4 -13.0 0 2.5 0 7.0 0

DIFTM2 5 -3.1 8 DIFTM3 3

-2.6 8 -28.0 2

DIFTM3 0 -12.1 7 -17.5 0 -15.2 7

DIFTM3 0 0.0 0 -15.1 5 -1.8 8 -13.8 1 -3.7 5 -33.5 0

DIFTH3 C -10.5 6 -4.0 4 -40.2 0 -15.0 0 -19.4 4 -39.0 0 -7.0 0 -7.5 0 -15.7 9 -22.0 0 -4.0 0 -5.5 0

DIFTM3 0 -15.3 1 WHITE RT PFREQUENC YDAT A DIFT M 0.4 5 19.0 4

DIFT M 2.3 3 8.4 1 17.1 2

DIFT M CO O 14.8 5 3.1 3 10.1 0 0.4 2 10.5 0

DIFT M 10.0 0 8.0 8 3.0 0 1.7 6 14.4 4 0.0 0 9.0 0 8.5 0 13.0 3 3.5 0 14.5 0 24.0 0

DIFT M 9.7 2 RTIM E

121.6 1 113.3 5

RTIM E 60.0 0 122.0 5 157.9 6

RTIM E 37.5 0 66.1 8 123.7 5 129.5 0 152.5 0 177. 00

RTIM E 123.8 9 121.1 5 118.8 0 109.4 1 123.8 9 118.8 C 114.5 0 114.5 0 119.6 1 114.5 0 114.5 0 114.5 0

RTIM E 117.4 9 DIFM 9

2.1 1 0.7 1

DIFM 9 1.1 1 0.1 1 3.1 6

DIFM 9 2.0 7 1.6 8 3.2 1 2.4 4 -1.9 4 0.3 7

DIFM 9 3.7 4 4.0 4 -3.4 9 3.2 5 -3.1 2 -3.4 0 4.2 2 1.2 3 1.6 5 0.6 1 5.5 2 1.8 9

DIFM 9 1.4 1 RM

9 23.3 9 15.0 0

RM 9 10.2 1 20.1 3 25.3 0

RM9 8.2 1 10.3 6 23.7 9 20.4 2 29.8 4 26.1 9

RM 9 20.0 4 19.9 6 19.8 5 18.6 8 20.0 4 19.8 5 18.5 8 18.5 8 19.3 7 18.5 8 18.5 8 18.5 8

RM 9 19.2 1 • J



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### TABL E E-7 . MEAN S AN DSAMPL E SIZE S <i\ ) FO RSEVERA L VARIABLE S B Y RISE * AMCUNT . AN DPARTICIPANTS : BLAC KFLORID A I I DAT A 

# 1

rRIS E

• • •

-

-

- AMCUN

T 2 0 3 0 4 0 2 0 3 0 4 0 N

2 0 2 0 2 0 1 0 1 0 1 0 DIFTM2 5

-106.5 C -45.7 5 12.0 0 -166.5 C -82.5 0 -30.0 0 DIFTM3 0

-172.5 0 -105.7 5 -36.0 0 -216.0 0 -132.0 0 -93.0 0 DIFT M

-58.5 0 •12.0 0 5 0.2 5 -88.5 0 -25.5 0 25.5 0 RTIME

360.0 0 315.0 0 285.0 0 360.0 0 270.0 0 255.0 0 DIFM 9

0.2 4 0.6 1 2.2 2 -2.0 4 -0.2 9 1.3 5 RM

9 29. 0 31. 1 34. 8 27. 7 25. 0 24. 5

i-JSt

PARTI C 1 2 3 4 5 6 7 8 9 I C

OVERALL N

9 9 9 9 9 9 9 9 9 9 -

N 9 0 0IFTM2 5 -185.0 0 -35.0 0 -23C.0 0 25.0 0 -18.3 3 -21.6 7 -1.6 7 -118.3 3 -36.6 7 0.0 0

DIFTM2 5 -62.1 7 DIFTM3 0

-213.3 3 -108.3 3 -248.3 3 -26.6 7 -100.0 0 -90.0 0 -88.3 3 -200.0 0 -93.3 3 -20.0 0

DIFTM3 0 -118.8 3 DIFT M

-91.6 7 0.0 0 -175.0 0 41.6 7 31.6 7 25.0 0 28.3 3 -23.3 3 6.6 7 13.3 3

DIFT M -14.3 3 RTIM E

311.6 7 311.6 7 311.6 7 311.6 7 311.6 7 311.6 7 311.6 7 •311.6 7 311.6 7 311.6 7

RTIM E 311.6 7 DIFM 9

-6.4 4 -0.9 8 -11.6 5 17.1 2 0.8 2 2.9 5 0.5 7 -4.8 5 0.4 3 7.7 7

DIFM 9 0.5 7 RM

9 29.7 1 29.7 1 29.7 1 29.7 1 29.7 1 29.7 1 29.7 1 29.7 1 29.7 1 29.7 1

RM 9 29.7 1



## B-9P.9 8

" E * -—-*-*-*^r**»-(J--**>~ -aa>V--.-:=rr

. U. '. • .•v J f>^J-vaajer..a>-_ | .- 1

. ^ TAEL E E-8

. MEAN S AN D SAMPL E SIZE S CN ) FO R SEVERA LVARIABLE S B Y RISE * AMCUNT

. AN O PARTICIPANTS : WHIT E FLORID AI I DATA IS E

• • 4 >

-

-

- AMCUN T

2 0 3 0 4 0 2 0 3 0 4 0 N

2 0 2 0 2 0 1 0 1 0 1 0 DIFTM2 E

36*.7 E 26.2 5 5.2 5 -13

. 5 0 58.5 C 27.0 0 DIFTM3 0

-22.5 0 -14.2 5 -27.0 0 -69.0 0 -9.0 0 -7.5 0 DIFT M

79.5 0 50.2 5 33.0 0 0.0 0 84.0 0 43.5 0 RTIM E

262.5 0 307.5 0 307.5 0 360.0 0 255.0 0 315.0 0 DIFM 9

6.8 4 7.4 6 6.3 7 5.8 3 5.6 9 10.2 1 RM 9

25.I- i 31.6 0 31.6 6 30.5 0 25.7 i 29.9 6



### PARTI C N DIFTM2 5 DIFTM3 0DIFT MRTIM

E DIFM 9 RM 9 1 9 13.3 3 -18.3 3 46.6 7298.3 3 6.4 9 29.2 2 2 9 40.0 0 -8.3 3 55.0 0 298.3 3 5.5 0 29.2 2 

### 3 9 3.3 3 -30.0 036.6 7298.3 3 3.8 1 29.2 2 49 43.3 3 3.3 3 56.6 7298.3 3 16.2 429.2 2 5 9 33.3 3 -16.6 760.0 0298.3 3 7.3 1 29.2 2 69 -21.6 7-96.6 736.6 7298.3 3 1.5 4 29.2 2 79 46.6 70.0 060.O C 298.3 3 6.3 3 29.2 2 8 9 -15.0 0-116.6 740.C C 298.3 3 -0.2 629.2 2 9 9 55.0 043.3 3 56.6 7298.3 3 9.1 1 29.2 2 1 09 33.3 3 3.3 3 55.0 0298.3 3 14.0 2 . 29.2 2

1 1 

# I [' 

# I 

# L L [ 

# L OVERAL L N 9 : DIFTM2 5

23.1 7 DIFTM3 C

-23.6 7

B-1 0 DIFT M

50.3 3 RTIM E

298.3 3 DIFM 9

7.0 1 RM 9

29.2 2