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m e t e o r o i o g m a i d a t a r e c o r d ; Dave B a r r e t t , J e r r y Me a c h , a n ; J e r r y Moe \~

s u p p i i e d th e CRSTEP d i s p e r s i o n mon o! r e s u l t s ; a r a 'Ge T1 k \ e r t , B111 L u x ,

a n d Hank C o i e f o r t h e i r v a i u a r i e e n c o u r a g e m e n t , s L . p t o " t , ana c o n x n e t s of

an e a r l i e r d r a f t o f t h i s r e o t r t . He e i s o th a n k Be rn Ste 1 g e " we d an d Tw

C u r r a n o f t h e EPA f o r t a a i n g t h e t i m e t o en g ag e i n many v a i t d n i e d i s -

c u s s 1 o n s and t h e i r c o n t i n u i n g Suppor t f o r t h e s tu d y o f p r o o a u 1 l1 s 1 1 :

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fPC*1r".,L:PS wf a i r q u a l i t y managemewt

HE would 3150 11ke to acknouieoge the contr ibutions of many membersIgf t he Systems AppT1cations, I n f . s t a f f , par twcular ly Hue Liu and Tony

r |T\B"1» E n I 1 ; ; * i e n f g 6 1 s : J § s r 0 f 5 and Paul b u t f r e n d f o rTnre

e f f w a e m management 0* t h e c 0= t1" ac t u n d e f wh T| r m s wo rk »uaS CB| ' | " lr

o u t . Houra"d Bec kman p e r f u m e d t h e es s e n T1 a 1 e c i v f g l6 5 k : . u " 1 h g r e a tr I

¢'n S' IVa t1 e n L e w1 : " t h e h e i p o ' t h e wb f d p f o ; e s ¢ 1 ~ t e e n . we a sJ

Be r g and P k1 H e t n c l f f m' Zh v1 r f P9 a r t wo r k .I

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9 E x e c n w e Summary 1v

1 INTPODUCTIUN 1

3

3

2 DATA ACQUISITION AND DISPEPSION MODELING

2 . 1 *4eT.eoro1og1c a1 D a t a . . .

2 . 2 So ur c e C h a r a c t e r i s w c s 462.3 Dispefs ion Mode1 ing

73 sToc><As'1c TRMYHENT OF HEYEORDLOGICAL DMATRa t1 o n a 1 e

82 Res ampi i ng Sc hemes

USE OF Rsswvuus TO ANAJZE M FREQUSNUi l

1111

DISTRIBUTIONS OF r»1§fEos=zoL0L;1cf=xL EVENTS

Ana y sws H e t h o d . . . . . . . . . . . . . . .

Un e - Ho u r He te o r o f o g vl c a ? E v e n ts

Ma n mu m I mp a c ts 24-Hour * E ve n ts

4 . 1

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Standard ExEx Neihod5.1S t o c h a s w c E151 H e t h o d . . . . . . . . . . . . . .

Co mp a ms n n o f S ta n d a r d and S t o c h a s w

E x i x R e s u l t s . . . . . . . . . . . . . . . . . . . . . . . .

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64221 H e t m d o l o g y . . . . . . . . . . . . . . . . . . . . . . . .

2 Em1ss1on L i m i t s Ba se d on S n o r t - Te r me..6 .

A3Meteoro logica l Data Sets

EXTENSION OF RESULTS TU OTHER AVERAGING TIMESSOURCE TYP£S, AND L OCATI ONS . . . . . . . . . . . . . . . .

1

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? . 2 10 00 W S u u b b e d P a v e ' P l a n t

?.3 St. Lows Meteorology

B SUMMARY OF RESULTS, CONCLUSIONS, AND Rzconminomons

8 . 1 Surmnary o f R e s u 1 t s . . .

8 . 2 T e n t a t w e C o n c l u s i o n s

8.3 Recommendations

68Re fe r e n c e s

U 1 71 1 1

I

EXECUTIVE SUNMARV

9

This report documents a study under taken by Systems Appl icat mns

at the request of the Of f we o f Ai r O.»aEit_y Planmng and Stanaafns 0

I.S. Env1ronmenta`| Protec tion Agency in support of the i r o ngmng

n c

me L`)

ef for t to deve1op probatnis tmc techniques fo r t he use of atmosphef-r

dispersion modeis 1n regulator y de c ismn-mak ing.

Our a n a l y s ws c o n c e r n s 1 t s e 1 f m t h th e te m p o r a l r e p r e s e n t a t wv e n e s s o f

s h o r t - t e r m m e t e o r o i o g i c a i d a ta s e t s us ed i n a i r qua11t_y i mp a c t a s s e s s me n ts

Suc h a s s e s s me n ts a r e ma t h e m a tm a i d e m o n s t r a t i o n s g f u h e t n e f an e x 1 s t 1 n g 0

p r o p o s e d new s o u r c e has o r has n o t a t t a i n e d an a mtn e n t a | r q u a h t y

LS ta n d a r d a n d f o r p r e v e n t m n o f 51 g n ' i f | €. a n t d e t e r i o r a t 1 o n i n c r e me n t

p r i n c i p a l ou t c o me o f an a t t a i n m e n t d e m o n s t r a t i o n i s a J u dg me nt a b o u t t h e

ad eq u ac y o f a p r o p o s e d e m1 s s i o n 11m1t o r a r e c o m e n a a tm o n o f an a d e o u a te

IT. i s o f p r a c t n z a l impo r ta nc e t o th o s e r e s p o n s w me f o re m s s i o n 11m1t

man ag1 ng t h e a 1 r q u a i i t y r e s o u r c e t h a t t h e s e ju a gr n en ts be r e a s o n a b 1 ,

5 t a b 1 e . i . e . . t h a t t h e y be ba s e d on t h e b e s t ava 1 Ta b 1 e L c u r r e n t j e s t u n a t e

o f t h r e a t s o f e xc e e d i n g ap p1 1 c a b1 e a i r q u a h t y C o n 5 t r a 1 ' | tS o v e r th e

p la n n e d 1 i f e o f t h e s o u r c e . Bec a use c u r r e n t mo o e h n g p r a c t m e r e h e s gn a

m e t e o r o l o g i c m r e c o r d whose p e r i o d i s , o f n e r . e s s 1 ty , sno r t r e 1 a t1 v e t o

e i t h e r th e p la n n e d o r r e m a m i n g I i f e o f a s o u r c e , t h e r e p r e s e n t a t1 v e n e s s

o f t h 1 s r e c o r d , o r t h e r e p r e s e n t a t w e n e s s o f e f ms s i o n 1 i mi L S ba s e d on su c h

The length of the meteo rohagica la r e c o r d , i s o f c o n s i d e r a b l e i m p o r t a n c e

Ma n n e d s o u r c e " ' 1$ f et1 me srecord cus tomari ly useo is o ne t o f ive years

range fran 10-40 years

He h a ve d e ve lo p e d a new te c h n i q u e ba se d up on t h e ' i dea o f r e p e a t e d

ra nd om s a m p i i n g o f a sh o r t . - te r m d a t a s e t as a means o f g e n e r a tmn g ps e u d o

l o n g - t e r m d a t a s e t s e x h i b i t i n g c h a r a c t e r i s m c s 51rn11a'" t o th o s e f o u n d 1n

i vS30 17 1

- n -

a c t u a i To n g - te r m m e t e o r o l o g m a l d a t a r e c o r d s . I n e x p l o r i n g t h e e f f e c m v e

ne s s o f t h 1 5 " r e s a mo 1 1 n g " t e c n m q u e we h a ve f o c u s e d o u r a t t e n t i o n on t h e

S02 1mp ac t5 a s s o c n a te d HWU1 \5oTaT.ed c o a l - f 1 r e d e1e =; tr 1c g e n e r a t m g

f a c i h t s e s . The s h o r t - t e r m p r l ma r y and se c o n d a r y e mi n e n t s ta n d a r d s we r e

c o n s m e f e d . Bec au se c o a l - f w r e d power p ] a n t S e x m b 1 t l a r g e v a n a t i o n s 1n

e m s s m n r a t e s , du e i n p a r t t o t h e va r y 1 n g s u i f u r c o n te n t o f t h e c o a l t h a t

15 b u r n e d , we ha ve m t e g r a t e d th e P e s a m p h n g t e c h m q u e i n t o t h e p r e v w o u s h

d e v e i o o e o Exim: me th o d . The r e s u l t , a new o r o b a b m l w s t m t e c n m q u e t h a t

t r e a t s b o t h en vs s wo n s and m s p e r s i g n me t e o r o lo g y as s t o c h a s t wc ( r a n d o m)

o d a r 1 t» t1 e 5 , r s c a " ' e d S t o c h a s t m EXE! h e r e . I n th a s re po r t we do c u men t

Lomo af1S 0nS o f t h e p " e v' | o u s l y d e v e i o o e o ( " s t a r \ d a r d " } E x i x me th o d m t h w e

new s t o f h a s t w c Exim t e c h m q u e 1n d d d 1 t | 0 r \ t o a s s e s s mu , th e ab 1Mt_ y o f

S to a h a s t wf ExEx t c a d e o u a t e ` y a c c o u h l f o r t h e 1 o n g ~ te r m va r 1 a D 1 T1 ty o f

C SD9'S'OV c o ~ 0 1 t1 o n s . The f0CU5 o f OU' e f f o r t s was no 355 855 HUEI HE '

erv s s 1 o f 1 m: s . o b t a w e c u 5 " 1 g ' w e y e a r s o f me te o r o f o g wc d a m an d

n

t.er.h'~1ques are fe|:resenLat1ve of the em1ss1on huntsO D Q P 1

a ed r f ! " a '0r\gP- meteo 'oog : a ' Penorc, 1r~ r ms case 13'-years

¢\;: ~ : a 1 or 0* Resar1~; "f=g Te; * v~ ' . 1ues

Sr~of t- ' ef r f Me teo " o `o g 1r . a Da te S e ts

Two I*ESarf1{ 1f1g, te€*\r13e5 new aeveopeo for LMS Stud). Une 15:5

d e w g v e c t c p f e s e f v e th e Sed5of1a` c_yL E> lI \ 0wP t o De p r e s e n t zn ma r ,

me L e o f o 0g La va f w a b l e s , t r s s udS ac nwe ve o D5 f 9 s 1 r \ £ t 1 n g i n e ran uum

sa m: ` 1 n g d:T. v1 t y t o 1 n a w \ a u a se a s o n s 0* th e gwefw d a t a r e c o r d L"Da5e

The Sezonc method pfovwdes 'Fmef tempofd` resohat lor. D:pPr "|0

L o n s t r a * f 1 n g th e f andom samp" | r 1g t o 1n o v' | c ua1 mo n th s o f t h e b a s e

f> e' ~o n. Th es e two 1esamg'1r~g sc hemes a r e k n o w as "s e a5 o na ? samp¥1ng and

° m o " t " ` 5 sa m; 1ng " " e s p e c t 1 v e 5 . n sc hematwc r e p f e s e n t a t w o v g f t h e

mor~ t" "5 me th o d r s p f o w a e d m V ' Qu * e 3 L.

B o th th e m o n t h h and sea son a7 sc hemes n e f e appW1eG t o o n e - , f a ve

n o severyear subsets of a 1?-year me1eoroog1r.a r e wr a from the

P m l a a e l p m a met o p o H' L a r a r e a Mean an a v a r m n c e s o f t h e f r e q u e n m e s o f

o c n u - f e n c e s 0* se ve r e ? U n d b 0* me L e o f o Yo g I c a 1 e v e n t s W - 9 - » s r a o w h t y A

8 f\

c o n d i t i o n s ) and c o mb 1n e t1o n s o f r r e t e o r o l o g i c a l e v e n t s ( e . g . , o c c u r r e n c e o f

p e r s i s t e n t u n s ta b 1 e c o n d 1 t 1 o n s ) we re c a | c u ' I a te d f r o m t h e 1 7 - y e a r r e c o r d .

Th e " 1 o n g - te r m " ( 1 7 - y e a r ) mean an d v a r m n c e s o f t h e oc c u r : - en ze s o f t h e

i n d i v i d u a l e v e n t s and c o mb i n a t i o n s o f e v e n t s we re c o m p r e d w i t h th o s e

o b t a i n e d f r o m b o t h re s a mp I 1 n g sc he mes f o r t h e o n e - , f i v e - , and s e ve n - y e a r

Het.eor'o|og1ca1 events were 1dent if1ed and def ined based upors u b s e t sI

j u d g me n ts a b o u t t h e i r i mp o r ta n c e ln Te a d m g t o 1 a r g e i mp a c ts f r o m 1s o1 aL ec

p o i n t s o u r c e s w i t h ta 1 1 s t a c k s .

H 1 t h i n th e s a mp l i n g e r r o r s , nO m f f e r e n c e s an th e o b s e r ve d and

y c a k u i a t e d f r e q u e n c i e s o f o c c u r r e n c e s f o r e i t h e r r e s a m p l i n g sc heme wa

n o te d f o r a \ | e v e n t s ( e i t h e r i n d ww i d u a i o r 1h c o mb wn a t wn ) and a l l s u b s e t s

o f t h e 1 7 - y e a r r e c o r d . Ho we ve r , f o r e 1 t h e r r e s a mp h n g sc he me , a 1 f f e r e n c e ~

i n th e 0 b S e r ve d an d c a l c u l a t e d f r e q u e n u e s we r e no te c l b e twe e n c omt>1nat1on

1 Thus, for exarnp1e, resamphng (usmgof events and ind1v1duaT eventse i t h e r sc h eme s) f r o m a f 1 ve ~ y e a r s u n s e t p r o v m e d c o mp a r a n le eSt.1rnateS 0

t h e 17-_y ear mean number o f o c c u r r e n c e s pe r y e a r o f , Sa y , " p e r s i s t e n t "

two h o u r s o f A 5tan11| 'L_y c o n a 1 t | o n 5 o r f o uu n s t a t d e c o n d i t i o n s , e . g4

h o u r s o f B S ta b 1 1 1 ty c o n m m o n s 1n a 2 4 - h o u r p e m o d . Re s a m p l m f r o m a

f w e - y e a r s u b s e t a Ts o pF 0v1 de d c o mp a r a n le e s u m a t e s o f t h e 17 - y e a

va r i a n c e i n t h e number o f o c c u r r e n c e s pe r y e a r o f " p e r v s t e n t u n s t a n l e

F u r th e r m o r e , ea c h r e s a mp h n g r e p r o d u c e d t h e To n g - te r m me a ncond1tionsJ number of Occurrences per year of sing1e hour eventS (e.g A staD11\1

c o n d i t 1 o n s } when a f a ve - y e a r s u b s e t was u s e d . Ho we ve r , l a r g e d m f f e r e n c e s .

b e l i e v e d t o be w e l l o u t s x d e sa mp 1i n g e r r o r s . we re n o te s b e twe e n th e i o n o -

te r m va r 1 a n c e i n t h e number o f o c c u r r e n c e s p e r y e a r o f s1 n g1 e ho u r e ve n c s

an d th e va r i a n c e o b ta 1 n e d us 1 n g a f i v e - y e a r s u b s e t ana e i t h e r re s a mp lwn g

sc he me ; 1n a11 c a s e s t h e va r i a n c e s e s t 1 m a t e o f o r any f 1 v e - y e a r s u b s e t wer e

Iess than those est imated from the 1?-year recom

>

C u m p a n s o n o f S t o c h a s u c anaS t a n d a r d E x f x Ho ne ] Re s u i t s

The 1?-year Pmladelpnia meLeoro1og1ca1 data record was used w|t.r : the

CRSTER dispersion mode] to ca'|cu1aLe 24-hour average 'Impacts nssomatec

3 3 0 1 7 1 v i

[ P B ~ | \ D f l h E B S T . E " r 1 ~ ~ u 1 \ S L | | , f § l j c : a 1 - r ~ r " r n g p o e ' £ 1 5

The result ing nor-maT1zed dis :=-rsio ' c1"ma'»= ue'e a.5'E'f i n

standard rv6 stocnastu: Elf .: mr"e1 'i f1g.P

Co*=;=a'1sor\s of 'es-.Hts g'F ap| : 'y1ng the tuc £xE: fec hni cue s t o t he

, »L » e+" '.:+ r *| 0f1S 5 f Tw-P \ A c ' m e m B..adm? s e t s o f no me u e - 0 i54>» * i ; aw0e x p e c t e d e r c e e d a n c e ' a r e s »f r@ a" c Dy ~ * l \ ` t | " ' . : * \ c - = T i 1 e t 1

afgumwnts suggest that 1»1¢.f= p'ooa b1`1t y o ' ~io at i o r .wfJv) va "e§

c a L . a t e C by thw stochas:1c Exim p~:hoa =1o»Id ue ; '&E1é' t ' a n :hose

r.a' :a .Ta1.ec by the s1.af 'erd nv 'nod. the a. t uaI d1"e 'e ' | c es L..-weo u t t o b

swa 7 'O ' the P*\"arJepP"a s ' t P . A s m xggn usmg St. Lowsmeteof cfogy ans a 100( "'» po=~=-' M e " nnthout Scrubbing s r' theNvU\ e s : 1 ma te s o b ta vn e c ' f f t h e s ta c h a s t wc E x i x me th o d ue * = s u b s t a n t ma

g f e a t e f t h a f t h o s e o b ta wn e o ' f o r t h e s ta wd a f d ExE : me t h o d . S t o c * ¢ s t i c

' l l : f e s d t s f o ' b o t * t h e mof~t.f _» a n : s f = s o n a ` * = s e n : 1 i n § s

»=ea" r 'Ide'=11- :a Nvf w ann e x v u t e d e=ce»= a n : e r e : a e e * i l r ¢ ° er "~s pwducec

roi*asm a'1C stafwoaf c £151 fe r owe- e"f " r | : - EB' subseSF p e w a s o* the Ph1adeT:'P'a reco 'd Sh0\»»?1 sunstee*t1a! va"1: ' io "' 1 r

¢f"*|J" arp?-;ZeG erceecafsr v na wa '»sL.1ts from one p e r i o d t o

VP'y few C55 t h! " 23 pe ' :er\ t } 01 t h a i ! 'l'i1|_;q\:. ||='g | | i fh1P ' \ @ \

va

an e r c e n t o* t np e va ues c a 1 c J 1 a te d DJ s t a n c = " a ExEx f o r f i r e 1 t 1 r e 15

: e " o a . V a ' 1 a t ' u " s ' s f s t o c h a s t 1 c E n i x u " * e j u s t as ! a " J e a s th o s eI

x

.Q ; \ . ` a t ' o"s

559 55 th e 1 r . a ; t 5 g f t h e ab o ve - mef wwon e d ~r a " | a D 1 11 Ue 5 'rn Ex

.11ato' "y pI 0 c eS s _ »-15s1or~ 1 i m1 t de te r r n 1n a t1 o n S (b a se d os u i t s on

assumed c r 1 t e r 1 ¢ o f a11o w1ng no ; x f e th a n a 10 D 9 r QP ' t N w u v e na

uswg both the standaw: and StocnaS1|c Exix ":"U\0US '\e g ' \c mc o a ` S u l f u r c o n t e n t w' c h n r ~ t s t " e 1U { ' - r " ' Nw v c r I e f i a was

S1mp}e s u f f o q a t e f o r av a c tu a a 1S § ]o n 1 1 m1 t .

a s a

A COmpaV1S0I! o f comQ 1 a n ' ;1=0f\1et+"h|; mean c os? s u T ' . . f w" ' = >

uetermmed us ing both t stanaard an1 s1e;.*1ast1c ExEx methods on one- and

a w

I

f ive- year subsets o f the Phi ladeiphia data set showed Hess var ia t ion fr0rr

one base period to the next than might be expected based on the compamson

These re5u1t5Our f ind ings are summarized in Tame 6-2of NPOV resu1ts

ind i ca t e t ha t emiss io n limi t dete rminat i ons ba sed on 5-year base periods

have a f a i r iy high probab1|1t_v of be ing wi thin 1 5 per cent o f a repre-

sentati ve Fong-term va1 ue Emission limts determ1naL1ons based on one

y e a r d a ta s e t s d i d n o t p r o d u c e su c h S t a b i l i t y

pli cat ions t o Other Ave ra in Tunes. 9 9S1t.es and Sources

As a may o f t e s t i n g t h e r o b u s t n e s s o f t h e r e s u i z s dws c u s se d s o f a ,

£xEx mo d e l i n g an d c o m p l m n t g e o me t r i c mean coaT s u l f u r c o n t e n t d e t e r m u a

t i o n s we re p e r f o r me d f o r t h e f d l o w i n g s | t u a ! . 1 o n s

3-hour average concentratmns>

A 1000 Nh scrubbed, coai - f1red power plar>

A 1000 Mx. unggrubbed power piafwt usmg, f|vE yeafs of>

Loui s metenroioqyS!

Mthough calcu1at1on5 for each of these scenahos were neaessawiy of a

Hmi te d nature, the re sult s were generaHy conswstenr u n th th o s e d e s u a b e d

above, thus suggest ing that conglusmns reacned on Lhe N515 of Uv s wC"¥

m g h t be e x p e c t e d t o P1010 f o r o t h e r U t e s . dvef ag wng U m e s a n d |DOw€

Conf1rmat1or= of th | s reSul'L must auam fur ther ca1cu`>a11onsphnts

Tentat ive Condlusions

Based upon the resuH.s discussed above, we draw Lne fo1'ow1ng

conclus ions

v1 i 10 3 0 1 1 1

f w f f - 15 no s= : f 1i 1' 1c an t m f f e r e n c e b e twe e n r e s u l t s o b t a i n e d f r o n

TMP m<\fL'"T Mf t 9 6 5 0 0 5 s a m p i i n Sc he mea..Y

r resarm t e f h f Su e , when a p p l i e d t o d a t a s u b s e t s f l v e

y e a r s i n l e n g t h , p r o v 1 o e s c o mp a r a b le e s t i m a t e s o f t h e mean an d

va r 1 a n c e o f th e number o f o c c u r r e n c e s p e r y e a r o f c o mD i n a t1 o n s

o f me te o r o 1 o g ; a I e v e n t s o b s e r ve d 1n th e l o n g - t e r m ( 1 7 - y e a r

Ph 1? ad e1 ph 1a } r e a o r d . The se c o mb 1 n a t i o n s o f e v e n t s a r e b e l i e v e o

Lo p r o d u c e th e g r e a t e s t c a 1 c u Ta te o 2 4 - h o u r a ve r a g e i mp a c ts f o r

power p a n t s u wtn ta 1T S t d ' n S and oc u r a t ap o b s e r v e d f r e q u e n c y

o f a p r r 1 1 ma te 1 y 0 " : e p e r y e a ' . For o n e - h o u r m e t e o r : o g i c a 1

e v e n t s w t h mea Bnnna f r e a ¢ e n c 1 e s o f o c c u r r e n c e muc h g r e a t e r

1

t h a n L " E , ne he r r e s a x h n g f .e _f 1n | \ i . e, when ap p1 1e d t o da

sets from one to seven _YEQVS rn le ngt h, reproou:es the vamance

*ound tn T*=»= Tong-tem P e a r c , 'in aU cases the varmnces uEP€ur wd e r e s mma te d . The se c o nc 1u s1 on = a r e ba s e d s t m c t l y gn an

ar»aTy s1s o f t h e Ph1? adeTpn=a ff~eteo»"o1:q1ca1 d a ta a~c th e r e ' o ~ e

fu may be i nt e d e m w t

B o tn th e s t o c h a s u = 2 s t a n d a r d ExE== t e c r w c u e s proud-ze

e f f e c t 1 v e ' y 1n:¢=nr.1c a1 m. |x1-mm e n s e c t e a ex:e e da n :e e r e s u l t s

T|\1S c o nc 1 u5 1o n " x n o t a . » a r t o be v i e de n e d e n t

[ P f f e r e n c e s m NPCs. r e s u i t s c a 1 c u ' a t e d by t h e s t a n d a r d £xE

me th o c ana : n e s t o c n a s t wc h i ve t h o d a r e s 1 t e d e p e n d e n t .

n mp a ' a t e va ` » s we re f o - wd a ' ow~ s t e ( P n i ! a a e p h 1 a ) , wh er

a t a n u t h e f ( b t . Lo u ws ) s t ; " s t 1 L E\ \ p" 3 c J c e d 5 1 g n 1 f = : a n tT

wgnef va1ues v a n md Stamzgrd E

\ ssmr" 11m1ts calc ; JT G u o n the 'Jasm u one year o f1 ~ t e o f 0 I o 9 ' c a 1 d a t a a d : t n e CF1* .er1on t h a t t h e NPUV b e i e s s th a n

o r e q u a l t o 10 p e r c e n t Sh0\~ a r e l a t i v e l y h1 gh d e g r e e o f

va r 1a D H u t ; f r o m on e y e ar t o th e n e x t , t h u s i n m c a t i n g t h a t

r e . 1 a t o r y d e m s mf n s ba s e d ap o " a s i n g l e y e a r o f d i s p e r s i o n d a t a

c o n ta mn a r e T a t i \ e y m g h d e g r e e o f u n c e r t a t n t y . T m s a p p e a r s

3 3 0 :

l x

\ Th e r e 15 no s i g m f m c a n t d i f f e r e n c e b e twe e n r e s u 1 t s o b t a i n e d f r o w

th e mo nth1 y and sea son aT s a mp l i n g sc he mea .

E u th e r re5 amp11 ng te c h n i q u e , when a p p l i e d t o d a t a s u b s e t s f 1 v e

y e a r s i n l e n g t h , pr o v1 d e S c o mp a r a b le e s t t m a t e s o f t h e mean an c

ve r 1 a n c e o f t h e number o f o c c u r r e n c e s p e r y e a r o f c o mb i n a t1 o n s

o ' me te o r o 1 o g 1 c a 1 e v e n t s o b s e r ve d i n t h e 1 o n g - t e n n ( 1 7 - y e a r

Ph 1 Ta d e 1 p h i a ) r e c o r d . The se c o mo wn a t i o n s o f e v e n t s a r e b e i we ve d

t o p r o d u c e th e g r e a t e s t c a l c u l a t e d 2 4 - h o u r a ve r a g e i mp a c ts f o r

po we r p Ta n ts w1 tn ta 1 1 s t a c k s and o c c u r a t a r o b s e r v e d f r e q u e n c y

o f a p o r o x1 ma te 1 y on c e p e r y e a r . For o n e - h o u r me te o r d 1 o g i c a 1

e v e n t s w t h mear ann ua1 f r e q u e n c i e s o f o c c u r r e n c e muc h g r e a t e r

\,

Q

t n a n o n e , n e u t h e r r e s a mp h n g te c n r r l q u e , when a p p h e o t o d a t a

s e t s f r g m one t o se ve n y e a r s 'rn l e n g t h , r e p r o d u c e s t h e va r i a n c e

f o u n d tn th e To n g - te r m r e c o r o , 'i n a l l c a s e s t h e va ma n c e s we re

unaerest1mated. These conc1us1on< are based str1c t1y on an

awa1ys15 of the nr1'adeTpn1a meteoro1og1caT data and therefore

t n ? ) md: be s u e 0r . e r 1 Ge f t

B o th m e s L o f . h a s t~ ; a n : sza naa f a ExFx t e c n m q u e s p r o d u c e

e f f e c t 1 v e y 1f -denf . 1c a1 mammum e p e c te d e xc e e d a n c e r e s u l t s

* M s c o n d u s v o n md; n o t ap p e a r t o be s i t e d e o e n d e n t

U f f e r e m : e s m NPQN r e s d t s c a 1 c u ' a t e d by t h e s t a n d a r d ExEx

me th o d and th e s t o c h a s t wc Un i x me th o d a r e s 1 t e d e p e n d e n t .

Lompaf atfe values were fouf1d at one s n e (Pnilade1pn1a}, whereas

at another ( bt . Lows) stochastw. Enix produced s ign1f i cantTy

Nghe " va1ues tnan md standard Enix

\ £m1ss1o1~ l1 m 1 t s c a l c u l a t e d up on th e Das1s o f one y e a r g f

me t e o f o lo g h z a l d a t a an d th e c r 1 r . e r 1 o n L n a t t h e np o v be l e s s Thar~

o r e q u a l t o 10 p e r c e n t Show a r e l a t i v e l y m g h d e g r e e o f

va r 1 aD 1 l1! . y f r g m on e y e ar t o t h e n e x t , t h u s 1n c | 1c at1n g t h a t

r e g u l a t o r y de c 1 s1 o n s ba s e d upon a s i n g l e y e a r o f d i s p e r s a o n a a r a

contam a re1at1ve!_y mgh degree of unc er t a i n ty . Tms appears

B30I X

ta be true of ca1cu1at1ons based upon both the standard ana

stochastic ExEx methods and does not appear to be s1te depen

dent

(6) E mi s s i o n l i m i t s c a 1 c u 1 a te d on t h e b a s i s o f f i v e y e a r s o f

ne te o r o 1 o g i c . a 1 d a t a an d t h e 1 0 p e r c e n t NP OV - a t t a i n me n t

c r i t e r i o n , u s i n g b o t h t h e s t a n d a r d and s t o c h a s t i c EXEJ: me th o d s ,

sh ow f a r ' l e s s v a r i a b i i i t y f r o m o n e p e r 1 o d t o t h e n e x t t h a n d o

th o s e c a 1 c u 1 a te d u s i n g o n e - y e a r d a t a s e t s . Th us we t e n t a t w e l y

c o n d u d e t h a t r e g u i a t o r y d e c i s i o n s ba s e d up on f i ve - . y e a r d a t a

I

sets conta in a much lower degree of uncer ta inty Indeed, Such

five-.year-based emission l i mi t s appear representat ive o f those

obt a ined wi t h t he 1?-year record However , th 1 s te n ta t 1 ve

condus ion is based so1e1_y on ca1cu1ations made for one s i t e

(P ni hdei ph i a ) and therefore we have no knowiedge of the degree

to uh1 ch i t may ho la at otner \oca1\ons (c f conc lus ion 4

above)

6 3 0 1 7 x x

|

xuwonucrlon1

1|

A | r q u a } i t y ' Impac t a s s e s s me n ts mac e o n th e b a s i s o f at. mo sph er 1c

d1s pe rs 1o r1 m o d d i n g a r e , by n a t u r e , ba s e d on i m p e r f e c t and i n c o m p le t e

Among the prunary sources of uncer ta inty arei n f o r ma L 1 o n

So ur c e d a ta t h a t i s Of ten o f l i m i t e d te mp o r a l r e s o i u t i o n

o r t h a t i s ba se d on a s s u m p t i o n s r e g a r d i n g o p e r a t i n g

c o n o i m o n s { e . g . , 10 0 p e r c e n t 1 o a o } .J

o f o n l y one t o f i v e y e a r sThe a v a w i a b i h t y , i n mo s t c a s e sH

o f me te or o To g1 c a T d a t a , wh i c h h a ve be en L o l l e c t e d a t a

511.6 severaW te n s o f i n i o m e t e r s f r o m th e s o u r c e o f

em1ssions

No hmmm a t mo s p h e r i c d i s p e r s m n moae1 p r o v m e s p e r f e c t

Al l cur r ent ly used models arec oncent rat 1 on est i mates

p r o n e t o a c e r t a m amou nt o f o v e r - an d u n d e r p r e d 1 c t1 o n

Tak en t o g e t h e r , a l l o f t h i s m p e r f e c t i n f o r m a t r o n c a n I e a d t o 5 1 g n 1 f 1 c a n t

u n c r t a i n t y 1n t h e i n t e r p r e t a t i o n o f d ' i s p e r s 1 o n mo n e h n g r e s u h s , wh i c h ,

i n t ur n, (.ou1d serio us ly confound the dec1s1on-making process

Th1s study addresses the 1ssue of using meteoro log1r.a1 data sets

In t h i s contex t , the fo11ouing questmnsc o v e r m g H m i t e d t i m p e r i o d s

reouw re c o ns 1 de 1 'a t1o n

How r e p r e s e n t a t w e a r e d i s p e r s i o n e s t i m a t e s ba s e d o n one

t h r e e , o r e ve n f w e y e a r s o f me te o r o 1 o g 1 c a 1 d a t a ?

>

01 7

Huw ' large are the effec ts o f us ing meteor*o1ogica¥ data

sets that are not tempo;-a11y representat ive on emiss ion>

Hmit deteminationsff

I n t h i s report we at tempt t o prov ide some of t he answers to these

Huch work remains to be done, however, before a fu11 underquest ionsJ

I n t h i ss ta nding o f t hi s t empor a l representat iveness issue i s reached

a d1scuss1on of what we havesense ue present here a progress repor tThe c o n c l u s i o n s we h a vedone and what we have 1earned from doing i t

Ho we ve r , we d o b e i i e v ereached are necessarihf tentat ive ann incomp1etev

tha t t he y r e pre s ent a s ign i f i ca nt f i r s t step in t he ri ght . d i re c t io n

l

\3

1 |

\

a s o x v 2 2

2 DATA ACOUISITIDN AND DISPERSXON MODELING

2.1 METEORULOGICAL rm/4

For the purposes of t h i s s tudy , a meteoro|ogica` data set of

s uf f i c i e nt Tength so as to be repres entat ive o f t ne ' lo ng-t er m" dispers ion

condi t ions at a partie-.Har site waS needed. This br i ngs us to the

quest ion of gus t what is meant by "iong te rm" i n t h i s c o n t e x t . Meteoro-

lo gi na i f actors a f f e c t i ng e f f lue nt di spe rs io n e xhi bi t v a r i a b i l i t y o v e r a

tremendous range o f t ime scales Stret ching from a few hours to severai

mi111or\ years or more (in t he ca se of ur ge- s ane c I 1 ma t o lo g ic a I

c h a n g e s ) . Th e r e f o r e , e ve n t h e l o n g e s t m e t e o r o l o g i c a l r e c o r d may p r o v e

1 n s u f f i c 1 e n t 1 f on e i s i n t e r e s t e d i n s t u d y i n g t h e e f f e c t s o f a l l p o s s i b l e

v a r i a b l l i t y . S u r e l y , h o we ve r , l u n c o mi n g o f t h e n e x t i c e ag e i s o f n o

c o n se q u en c e nn t h e s tu d y o f a i r q u a l 1 t y i mp a c ts a s s o c i a t e d w1 th a c o a l -

f l r e d power p l a n t ! i n l a g h t o f t h i s , i t seems r e a s o n a b l e t o c h o o s e a s a

t1 me s c a l e t h e a ve r a g e e x p e c t e d l i f e sp a n o f su c h a po we r p l a n t - - a p p r o x 1 -

m a t e l y 3 0 - 4 0 y e a r s . One may be te mp te d t o c h o o s e a s h o r t e r t1 me s c a l e

ba s e d on t h e e x p e c t a t i o n t h a t t h e i n t e r a n n u a ! va r 1 a t1 0 n S o f th e me a n

d i s p e r s m n c o n d i t m n s a t a p a r t i c u l a r s i t e a r e q u i t e sma1'| Ho we ve r , a t

'is impor tant to keep in mi nd t ha t the metnocls current1_y used in a1r

qua ht y impact assessment re ly he av i ly o n c ha r ac t er izi ng d i sper s io n

condi t ions whi ch o ccur oniy i n f r e que nt i y , e . g . , once or twice i n a given

one- or even five-Year per io d. L i t t i e i s known about the spectrum of the

peak ai r quai i t y i mpac ts a ss o c i at ed w i t h such ra r e e v e nts o r i t s pr ac t i ca i

impact on the regulator y dec is io n-making process . In f ac t, t h i s i s t he

'issue wh|ch 1s at the very heart o f o u" s tudy . In v i e w o f t h i s , t he

30-year t ime sca1e seems approprnate.

A rev iew of ava1labIe meteoro logica l data sets c o ns i s t i n g o f a l l o f

the parameters requi red as input ny the CRSTER preprocessor a1gor1tV\m

3DI ?

(EPA, l977} was co nducte d by s ta f f mmbers of the Source Receptor AnaI_ys\s

Bra nch of the Off i ce of Mr 0 u a \ i t y Planning and Standards of the U.S.

Mt ho ugh a s u i t ame surf aceEnv1ronmenta\ Protectmn Agency (OAOPS/EPA)

data set covering 30 _years (1951 - 1981) was found, the upper a i r : la ta

requi red by the preprocessor program is ava i la bie f or on1 y the 1a s t 1?

Nevertheless , th is dat a set turne d o ut to be theyea rs of th1 s peri od1The surf auebest ava i lable and so 1t was chosen for use in o ur study

data i s from Phi1ade1phia anc the upper a i r data i s from Du11es ai rpor t

j u s t o u t s i d e Ha s h i n g t o n D . C . we sh ou 1d p m n t o u t t h a t 1.h1s 1?- . y ear p e r w d

r e p r e s e n t s Ove r 50 p e r c e n t o f t h e a ve r a g e I i f e span o f a c o a l - b u r n i n g

we hone wiN st 1 H be suf f+n;|ent for o urpo we r p u n t a n d , t h e r e f o r e

PUVD0ses

.>SOURCE CHARACTERISTICS2.2

Sourc e charac t er is t ics o f a con1-f i red ele c t mc generating pla nt

ty pi < ; a1 o f t h o s e f o u n d i n th e r e g i o n r e p r e s e n te d by th e me Le or o1 og 1c a1

. i a ta s e t we re r e q u i r e d f o r us e i n an a tm o s p h e r i c ms p e r s w o n mo d e h A

Search was conducted of a data base (res ident on Systems. App1icat1ons

power plants to ident i f y a11 nor thPrime computer] of a11 major U.SDue to the c hf f ere nteas tern, coa1-burning uni t s o f 300 HL or more

n a t u r e o f s c r u b b e d an d u n s c r u b b e d u n i t s , i t was d e c i d e d t n a t p a r a me t e r s

for two representatwe p1ants would be determined: a 300 to sud MM

unscrubbed uni t and a more modern 1000 Hb. scrubbed un| t that m1ghT.

represent the upper-s ize l i m i t o f fut ure power plants iocated in urban

£ach uni t was assumed to be associated wi th a s1ng1e stack Aa r e a s

quick exam1nat ion of the re s ul t s o f the da t a f11e search suggested tha l

the parameters l i s t e d in Table 2-1 are f a1r1y typ ic a l of the unscrubbed

Parameters fo r t he scrubbed uni t were determtneo by es t i r natmg theu n 1 t4

ef f ec t s o f scrubbing on the s tack gas ex i t ve loc i ty and temperature of a

hy pot he t i c n 1000 MH power p1ant used i r an ea r 1 i e r study (Bur ton,

B o th t h e s c r u b b e d an d u n s c r u b b e d v e r s m n sStoeckenhzs, and Nnrd in, 1982)

of th i s source are Hs t e d i n Tab1e 2»2

8 3 0 1 7 2 A

5 To' w e mo mL : L i 2 - 1 Bour < C"<: d . i f

un s c r u b b e n c o a h f m r e u :» mf r ; : | d n [

L5 . 3 m

a 1 5 ° x

Stack marnetef

ta c k ' e mp e f a tu f ro

35taLh veioC'I }

frm 551 gn :Le corfespon553.6 5MV-5 u

the mme1ec LUUL Hu1 . 5 < \ - u e c r s a f a ; L

ec »J~

U» ; " , t : ¢vcFS1DV\D

> L r L " ~ I

| | |@ " 5 | 0 r \

pes e '*92TbLa.r he m

6bd. a dwame

6 413.14 st e mp e f a tu f e

42 mma n v@?.JL

nws sn of r a t e L o r f e s n o1 : SLU

. iMa<

a : s e o wh L 0 P ju 0 L t1 0 n ~ t h Ph1 13 J e1 ph 1a

U\ d L o n g u n c t c n u ' t h Q t . \ 5 me

616

Qa>>.. "1;" uf t h a t 4'rm~ -»~vss'or» n w i ¢ ; u M

t " eH e a? 15 .~ofJa 1f co»:U T L ; r: ? . T w a c t . N t m s g m

rb..ff1e0 'in V1 5 r dn

heQ tunes one '11"JS»i1'Lh a S u l f u r C0|"|t.z.]T. OT 1 I D SOZQMHETU we

ar: be f o u n d by 1 . . ' U p ! . f 1 n g 1 ' e ve ur g'|v¢=

w e s u u b b m g e f f \ c 1 my

5

I

I

DISPERSION noumus2.3

Dispersion | \ode'| ing for the 17-_year meteor-o1ogica1 data set was

carr ied out separate1y for both the 400 Mu unscrubbed and moo nu scrubbedI

units by oAoPs;£PA. One-hour average concentrations were es timated at

receptors using the CRSTER dispersion model (EPA, 1977). Results were

obtained assuming a cons tant emission rate equiva i ent to a coal su1fur

co nt ent o f 1 Ib S02/HMBtu (see TaD|e 2-2) and hence are ref er re d t o as

180

9

n o n n a H z e d c o n c e n t r a t i o n s

I

I

I y

6B301 7 1

I

STOCHASTIC TREAYMENT OF nU£0r<oLor,1cAL DATA3 I

\

RATIONALE

He are searching for methods by wh1ch the xnformatmn conta ined in a

s h o r t - t e r m [ 1 ~ , 3 - , 5 - , o r ?- y e a r l o n g ) me t e o r o i o g wc a l d a t a r e c o r d c an be

us e d t o a s s e s s t h e a i r q u a 1 \ t y i mp a c t o f a s o u r c e t h a t u 1 I | y i e l d r e s u 1 t s

s1m| ` | ar t o th o s e urmc h wou1d h a ve be en a t t a i n e d ha i l a i o n g - t e r m d a t a Ir e c o r d be en a va 1 1 a b 1 e . Suc h me th o d s , i f s u c c e s s f u l , wo u ld a l i o w t h e

d i s o e r s i o n rnode1er t o p r e d 1 c t ( w i t h a h1 gh d e g r e e o f re 11 a bi ' L1 f . y ) t h e

l o n g - t e r m f r e q u e n c y w i t h u m c h c a k u l a t e d a d ve r s e i mp a c ts a s s o m a c e d »n1. r

a s o u r c e w i l l o c c u r , u s m g o n l y , f o r e x a m p le , a s m g l e y e a r o f

I

Ir ne= teor n1ogic a1 Cana

He envwsion these methods as c0n51st1n9 of Monte-Car10 s1rnu1at1ons

wh er e1 n t h e me te o r o l o g 1 c a l d a ta i s no lo n g e r v1e weo as a p r e d e te r mx n e e

t1 me s e r i e s o f e v e n t s b u t r a t h e r as a l a r g e c o l l e c t i o n o f i n d e p e n d e n t

e v e n t s t h a t c an be us ed t o c o n s t r u c t an i n f i n i t e number o f t i m e s e r z e s . '

51n c e th e c o l l e c t 1 o n g f e v e n t s f r o m u n i c h th e t 1 m e s e r 1 e s a r e c o n s t r u c t e d

i s a s s e mb le d f r o m a s h o r t - t e r m d a t a s e t , o u r wo r k i n g h y p o tn e s 1 s i s t h a t

I

t h ws £ o 1 1 e c t1 o n a d e q u a t e l y r e p r e s e n t t h e s e t o f a11 p o s s wb le e v e n t s .

t h 1 s t u r n s o u t t o be t r u e , t h e n a s e t o f t i m e s e r 1 e s c o n s t r u c t e d f r o m

th e s e e v e n t s w 1 l 1 , f o r a11 1 n t e n t s an d p u r p o s e s , e xh 1 b 1 t c n a r a c t e r 1 5 t 1 c

1

5

f

d e s c r i b ety p 1 c a 1 o f a l o n g - t e r m d a t a r e c o r d . I n t h e t o l l o \ 1 n g 5?LL 1Un> h e

i n d P t a 1 l t h e pa r t 1c u 1 a r p r o c e d u r e s s e 1 e c ta d f o r u s e i n tn 1 5 S tu d y

' As us e d h e r e , t h e s e i n d e p e n d e n t e v e n t s a r e def aned su c n t h a t t h e y t a k e

t o c o r r e l a t 1 o n o f me te o r o 1 o g 1 c a 1 ph en omer a a n d t h e

c o r r e l a t w o n b e twe e n me te o r o 1 o g 1 ; a ' » e r 1 a b 1 e S .1 n t o a c c o u n t th e au

1330 1?

I

I

RESAMPLING SCHEMES3.2

Resamp1ing schemes are bas ica lly Monte-Cario Simulat ion techniques

de s1 g ne d t o i n f e r i n f o m a t i o n a b o u t a p o p u h t i o n ba s e d up on a s \ n g 1 e

ra nd om sa mp i e dr awn f r o m i t . l n t h i s s e n s e , r e s a m p i i n g sc hemes a r e

r e i a t e d to mo r e t r a d i t i o n a l p a r a m e t r i c t e c h n i q u e s , su c h a s c a l c u i a t i n g a

c o n f i d e n c e i n t e r v a i f o r t h e me a n o f a n o r m a i l y d i s t r i b u t e d p o p u l a t i o n

ba s e d upon th e i n f o r m a t i o n c o n ta i n e d i n a ra nd om sa mpi e dr awn f r o m 1 L .

The g r e a t a d v a n t a g e o f r e s a mp i i n g sc hemes i s t h a t t h e y a r e ve r y g e n e r a i .

n o n p a r a me t r i c t e c h n i q u e s t h a t c an be us ed t o e s t i m a t e t h e d i s t r i b u t i o n o f

I

0

A r e s a mp vi n g sc heme c o n s n s ts QTany s t a t i s t i c one might be inter es ted 1n

f iv e bas ic steps

Draw a ra nd om samp1e o f s1 z e n f r o m t h e p o p u l a n w n(1)3

Using Just the eIements 01 Lnis random samp'le, sampie

wi th replacement n t1mes thereby generatmg a new random(2)

samp1e of s i ze n, a11 of whose elements came from the

o r i g i na l random samp1e (some eiements may have been usedI

Th1s i s wh a t 1s me an t by r e s a mp h n gmore than once)

Compute the s t a t i s t i c of i n t e r e s t , u , from T.h1s random(3)I s a mp le

thus generat mg a TargaRe p e a t s t e p s 2 an d 3 many t i m e s(4)Set of e

No te t h e d i s t r i b u t i o n o f e an d us e t n i s 1 n f o r m a t1 o n t o

c o mpu te th e e r r o r o f e s t i m a t i o n o f t h e t a r g e t p a r a me te

o f t h e p o p u l a t i o n , e .

(5)

1

F o r t h e p u r p o s e s o f t h e c u r r e n t . S t u d y , r e s a m p l i n g t e c h m q u e s a r e us ed

to i n f e r t he lo ng- t er m d i s t r i but i o n o f peak concentrat ion events based or

In t h i s case, thet h e i n f o m a t i o n c o n t a i n e d i n a s h o r t - t e r m r e c o r d

B83 01 7 2

I

re ferred to above 15 the snor t- term (1, 3, 5, or Tye ar"rar J ~m sa mle

M e m e n t s " t o be res amp1 ed a r e i n d i v i d u a l|1e's»oro1 ; 1 c a } re:<~fr:| arc. t h e

nl

Io a , s . S1 n. e ea o UE) o f t h e sam; e s un 1 Que ' y 1 d e n t i f 1 e d w i t h a

c o mo1 n a t1 o n o ' m e t e o f o l o o ' a1 Lo s p e r s 1 o n } c o n d i t i o n s , ea c h r e s a mp i e d s e t

g f da y s c o r r e s o o vs s t o a r e s a mp i e d s e t o f me te o r o 1 o g 1 c a I c o n o wt i o o s f r o m

whwnh th e s t a t w s t i c o f i n t e r e s t ( é l c an be ce c o ¥ a t e o . Swnce t h e

ms eo f o 1 o g 1 c a 1 d ' s o e r s 1 o n c ooG1L1 0n5 f o r on e da y uo1 que 1y d e ' 1 n e a

no rmaT1z e cuH e f t ' e f 1 o n , ea c h r e s a mp 1 e : s e t o f da y s a l s o c o r r e s p o n d s t o a

1"»=,5"3§e{1 ar t : ' nmf na i z e d c c w c e r t f e t x f s . He H113 make us e o f t h i s

iI

II

~a. a ps e uo . 1 ? - v e a f me te o r ¢ og1r.a1 d a i{ 0| l| P31 i r f 5. F: exam

P g e ' e r a t e d h x d r a w i n g 1? r l n a o m sam; e s ( 1? " s a m c i e y e a r s " ) o f5 E 1 c a n

I365 days. each frJ " a single ye-r o f met.ec'o1r.Ȥ1::a1 data (l"'0uln as 1

ba s e p e r = o d " } . The r e s u l t 1 n g 1 7 - y e a ' sa m; e r e c ~ " d c an oe us e d t o

e 5 t \ m a i 9 th e peak 1mp ac t5 ( e . g . , Hu mlc

uu aW \ t y s L a n o a r o } ¢ §oc 1af@d wwnn a so u

o f ex e e d a r - e s o ' a g 1 ve n a w'

r c e t n a t uouWd h a ve been * n " d n

ecord be»f ava1lam u d 1

m e a L tu a 1 r e s a mp l i r f ; I.BC.hn1JHES e mn 1 c ; e : f o r t r w , reI: "es<»

a " i a t 1 o n s o n t.n15 s i m p l e e x a m p l e . l n s t e a a f ; h a a s * g c

I|h r o u g h o u t t h e Erase p e f m d , a mo n t h ' s o r s e a s o n ' s w v i h C'

f r o m <1 1 o f i r e J ay s wh w e t e ue: -10d th a ? c o r r e s r o n c LLrandomly 'FW 1

i a y s a r e a vm

n t h o r se e ' 5 o r . Fo r exa - \ p 1 e , 3 1 06 1 5 a r e ra ~ c o : vl y dr a wn u i t nthak rr

h \1 Ui|Oerp. S Er 7 ` e e1 nf.o d "a r yd Jwe Je o hc e wnt f

mf 'e t w " ore JB"J&fbe lo n g e f th a n C' a r l j f arm I n s

t , 28 1'5'y5 a r e ra n d o mly d r a w f f o ' the Februe days 'rs f "r be

1n. .eJ u m ! 3n% da y s ha ve be en( 5 T S1 f U C P1 5 5 s e £ ` L l 0 " ' PW m o d

kn wr as th e mc r ; " 1 y m e t r ;0 f r sampae y e a r . Th1S 1 s 0

H 5e a a c " ¢ 1 me tn n d wo r k s 1n an ana1o QJ u5 ma n n e r , w11 ho s e n , t * s '-~ rm

i

acl" sreaor be ng treated 5n*,~"&'r

The p u r p o s e o f a t i o f t h u s s a w : \ 1 n g s o p h 1 s L i c a t1 o n 15 to md 1 Uta H t " e

n t e g r w t y o f ¢ J mv" § o r se n5 na1 D e r \ u d 1 c 1 t 1 e § t n a t may e x i s t i n t h e

41 6 . S1nc e SuCh pe 1 o 3 1 c 1 t1 e s a r e known t o e x \ > t 1n mdPy me Le o ro 1 og 1 c a 1

§e:é"I11S e . r o p r 1 ¢ * e t o U'»r r n e s e me th u c s f o r o u r s tu d y¢@r15lu'Ps. 'lt

gB30

I

o

1 .

;: 5 I

é iJ

I

/I

o

/\i§ , /

l

2

\2\i;f/ " \ " \\;

/{*,; |¢

\?\

\,f

»\.1 E..J

\f \

f k ,

~ /T "

§=- . . . . - -

\) fxe.

_ 1. r

|

| . . . f t .

~ _ _ . - - -

1 r

B3C1? I f

I

;~»a use o m wi n \L. TU :»~f.~.& iTR ~;T1 "|5 OF MN UGICLL E, 'N Io

ANALYSIS MUHOLa

A5 a ua ] g f e ¢p1 a1 ni ng the 2 " rf t \ ¥ F" \ ! § § o f the 'khalf l 1ng scne

LEV 4 on f5¢| t " $15 o fd e s c * \ b e d Ln a p t e r 3 , we

n \ e n g t h made UD o f C0nL1gu0J S } r 4 F S f -m * ' e 1 ? - es a v e ' , p a r s

, gf#ford aescrwbc- ln Seaman 2.1. A | 5 6 11m+ %o1*01 wa l d

P~r5 fo r # ic h nase ;Pr1Qu L530 were generated uswng buzn the" C Gs< '» ns ' ans the l'rec.\»nc1e5 of 0CCuPr

J r \ th1y e s o n a l \

<LeoroIog1ca » e " t s (such a A s '¢3111ty "L u 'S } , Exp"P55e { 1 ~ dU

n@<ef ar, ne ueiwfvwmt s of nu" \er of e ~" I

t o th e a:LuaW d' | s &r1D ut1o f1s |] " " " | \ x: f 1 f r I

St"1bu'£lon p r e U

H 0

e 1 " - y e a f d a t a r e c c f d . E C a g f e f e n t D~ wP E " t

u 1 0 t e n d t o 1 n d ' L a t e t h a t t h e r e s a m p i m n g s c h e

T18 i n

I S c e

o d I C

IMe >' A

e Un i U 0n1_y ...nonc e s ; f 1 D 1 n g th e lo n g - * v ° m dws pe r swo n c o n d 1 t1 o n s a t a

t h e i n f o r ma t1 o P c o Hi a 1 ° e d 1 r a s h o r t - t e r w F e c o r 0 .

AL EVE\ - H i m MLTLURU

on we p r e n t r u§ 5

u m a % w 3 o c c u v m g d u f m g a J r

1 Tor w e HUIHLJEV of n o u r s 01 a Q1

*fese d 1 s t r f b ut h i s 5

s t abwhty fussthe nr s ene d 1? . e a r r e c e w , t he nbsawe5

o n s u i cuTe Qd1 9 ; I ) , and S \ f .»

o f <1 e y a"S ef wf a te f l ' f m oPar r e c o r d

DrC|"U\£*\ b8Cauti= I t c ara we l Cree ;1er10ds. The 15-gear peEr me 0 n ' 3 m1

eTie" i n t o 1 - , 3 - , and 5-yeanew ' a md I f lee " :.he s ta t i s t ic s o f t he 15 -y ea r pe r1 0C Las

*'»- ; 1 7 - y e a r pe" roc \ ( a s Shown i n Tab?f¢ a1n

wasf ar! ! 10 \ ; ' \ r 'Ne 15-year perwa as | conven' ie'~t5 ?

1L

subst i tut e for tne ` |0 ng-te rm r ecor d whe n ta king 3- and 5-year subsets.

Due to the Hrge amount of nu11er1r.a1 data 1nvo1vea, grapmcal smmames

h a ve be en p r e p a r e d f o r or.1y t h e mo re 1 mp o r ta n t r e s u l t s

F i g u r e 4 - 1 p r e s e n t s th e mean and S ta n d a r d o e v 1 a t1 o n s o f t h e number 01

h o u r s p e r y e a r o f A s t a b i l i t y . The two b a r s on th e le f t s i d e o f t h e

f i g u r e s r e p r e s e n t t h e mean an d s t a n d a r d d e v wa t i o n urh mn we re o b s e r v e d tc0

occur 1n the 15-year recorc (1966-1980) The se va 1 ue s u e " e n o t o b ta 1 n e o

w i t h th e re s a mp | 1 n g sc he mes I n s t e a d , t h e y we re ub ta wn e o s1m; !3, by

c a 1 c u | a t i n g t h e number o f ho\ . rS o f t h e g i v e n s t a b i h t y c l a s s m ea c h n f

t h e 15 c a le n d e r y e a r s and th e n f i n d i n g th e me a n and va r 1 a n c e o f t h ei

r e s u i t i n g 15 n u mb e r s . The o t h e r b a r s i n t h e f 1 g u r e repreS&r '| 'L t h e means

an d s t a n d a r d d e v i a t i o n s c a 1 c u 1 a te d f r o m s e t s o f 500 s a mp le e a r s ge ne f atef

by mo n t h l y and se as o na 1 r e s a mp Hn g u s i n g ea c h o f th e t h r e e f w e - y e a r ba s e

periods : 1966-19?[}, 1970-1975, and 19?'6-198i S e v e r n ob s e fva tw o n s c a

be made based on these resu1t5

> B o th th e mo n t h l y and s e a s o n a l r e s a mp i i mg sc hemes u w

e s s e n t i a h y th e same r e s u l t

> The mean number o f h o u r s o f A stab111L_y do es n o t c ha nge

S i g r \ | f i c a n t1 y f r o m one ba s e p e f m d t o th e nexT

> The va m a n c e r e s u l t m g f r o m t h e r e s a m p l m g sc hemes do no

va r y si g n1 f 1 c a n t1 _ y f r o m one b a s e p e r m d t o t h e n e x t arm

Lney a r e a l l l e s s th a n t h e va r 1 a n c e 1m th e o b s e r v e s 1%

year record

Th1s l a s t o b s e r v a t i o n s u g g e s ts t h a t t h e r e s a m p l m g sc hemes h a ve f a 1le d no

s imulate the amount of v a r i a b i l i t y t h a t exwsts ln a long-term record

Results simi lar 'Lo these were found fo r ea ch o f the ot he r Pasquwl

s t a b i l i t y c l a s s e s and f o r b a s e p e r i o d s o f o n e - , f a v e - , an d s e ve n y e a r s 1n

l e n g t h ( T a b le s 4 - 1 t o 4 - 4 ) . An a n a l y s i s o f t h e number o f h o u r s p e r y e a r

d u r i n g wh i c h t h e m n d sp ee d f e l l wi t n wn one o f 11 c a t e g o r i e s a l s o p r o d u c e

s i m i l a r r e s u l t s ( T a b l e 4 - 5 ) .

x283 01 7 2

9

U H{

1Iw IN

f

"I -I I + I ' L . +

i :| |

4 - r 4 - - 4

I4

I r--- 44 + 1

l 1lgI 1 | _

IE1 1 f _

I V J #71 =rw f - »

§\ \1 U4

4 5} \\ 4 ;i1

I/ 1LL . 4

- . .

-,P _,Tv §uPr "3G

_ nau d S P

I l p rFa

iw, Q

FIGURE 4-1 fnr. s r ison nf '-easona and rf..1+h1y sam'inp srPeme= wean andstandaf c .' \ \ "i f " | 0 * n u ; of H. . vs :»:- wear " ; . S 1 a : " " L . . ( E r a 1a:e

o b s e f v e d " p r e s e n t t h e rr av ia t i on - ross i ns tre cc fo w mo m resampl mg

TABLE 4-1. Samp!e means and standard dev1at1ons of number of hours peryear by s t a b i l i t y c la s s for the month1y samp11ng method: five-_year baseperiods ( u - samp!e man; s = samp1e s tandard dev ia t ion).

Observed Val ues \'éT1fe§ ]bta1ned by Stochast ic Semming{Hnnth1y] on Base Periodsf o r t h e P e r i o d

s u b w a yC1ass

1966 1980 19ee-`197o 1 - 1 s - 19§E1 s Su Su u su

A 32 .O 1] .2

48.3

54 .2

31 .4 6 3 ?.5 31.9 7.25B

c

372.3

905 .7

s 2 4 29.9 385.6 3I \II

o 39.2 873.0 38.3 938.5 4

D 4958 .3

1381 .6

0 0957.4 125.0 5051.0 123.0 4863.1 13

E

F

o 1394.0 50.3 1336.0 45.7 14 51.6909.3

207 .3

73.9

34 .0

3 47.8 877.7 47.0 9a4.e 4

G 2 22.6 214 .o 23 208 .7 22 _7

TABLE 4-2. Sam|:|1e means and standard dev ia t ions of number of hours per yearby s ta bi ' !1 ty das s fo r t he seasona1 sampling method: fwe-yea r base oemods(u = sample mean; s = sampie standard de v ia t i on) .

obéervea valuesfo r t he Period

v a i bé obzainea by Stochast ic Sampling{SeasonaT) on Base Periods

1966 19 !̀O 1971 19?5 19?6 198DStab1HtyC1ass

1966 1980s Su u su Su

A o 1 30 .9 7.4 33 .2 3 3 mB 3 4

7 5

9 3 o 31.4 38 32.2c 6.0 40.8 871.3 37.4 942.0 42.3

3.7 125.0 5061.4 118.0 4850.7 x2s.cD 4955 .3 191 .U

1381 .6 51 .Oi

E

F

139

9o4.n 46.5 871.9 42.5 94

202.3 22,5 2 1 m 22.2 20

6.9 49.1 1337.1 45.0 H 1 50.8

50.3

23.0

3 7

3 3G

c a a n s x4

TAHZE &-3. Silmp1E means and standard dev ia t ions of number ofS e ve n - y e a r ba s e p e r i o d sho..f's per year by ST. lhI |1Ty dass

w = s lmp1e man; s - samp=e standard dev i at i on)

véJe§ Obtained by StochastSam; mg ( m n t r m On B859

Periods¢>'»E»1 ' i e LP

di w 19?2 1Q'? _ 19?| 1

S5\ . » 6 5 S Su U

?.U.53 6.8A M 13

as

55

'xoZ9

38

E . H U

9 1 ? O

I3

EL

D 223 5( 113 sa b u491450

A2

1E`$ 167

89

A8

r 1 4

5 QL

21218la If

\

1\

j

15l" O1'»' a

\co r0:

a nF

. :9 ur C N N n n

. . .| ~ 1 + c r a n c c : JN M c : u n 1 e u

c9 -o

| \c a

c h

t U C r u H 1 a. . .

a s u c v .. e u Ff u C A . 1 u h e u

o n| .

PM..

c r

a

' H 5

u aM

F i

i fu c

r .

-

e -1

c

n oN

N

u rur

|

a nr \

Q

a nn -n

c

I :-

. -

"

vaur

0..

uf1

c v

\ . :1

m.

i x .1 |

r :

af

l " \l \ .

l

$u _ L n ¢

LasI .3 5I L

l rA

n n

.Uv -

c rI

r

N

U * |.

e c zh M

f :

en::

-

\ . U

r - u : "r r - l \

m l m ' n r H . o v. : xc \ D u rvI n c r n z ¢\. s : c u : | " \ r n

|anas

u

5a. -

1 :1 :J

u

a nn

Ll u4: .

L .mQ

a :

L

. c

1 :c

. :4

1 :

;»

§ |

I.. ..

c

F 1

.U

6 .n .c

-

-

1- .

"c r

n n

u cl x

r

..\ \ .

u e

l "

. f

In .

F

4 :l n .

'

Ur x .

u r

\ c

Pmr

L f

u cM

-

» nl "

R ..

4 :

1 |: :

c

u c-

-

C

\ C

u

1 :

l x .u r

xc

rl

1

u r

-. .

I -P

r

:u l

1

r u

f

a sN

U.

:l \

¢\ .

1 :f \ .

S.,`é.~E

3 ; -u

=u ~¢¢

~ r m

»-==

¢ =

1<

¢< v

| \

uD cv

'§|__

i§

| ;

-

.u cc r

u aU

Cc r

w a

a o¢\.

l x

u nl l :

r -

1u n

s o

N

cm

¢

ure u

N

e r¢\ .

M

n rA

r -.

u cm

F .

1 :1

c s

. :1

e c

F"

c

u r. -» -

1 :

I "r u

-

C

u c

_. -

1 :

ur\ .

'

l \1

c c

-1 |

|

l

a n

cF

N

1 :l

1

n r

U

n cur

F

U "Q

-

0

.

:N

a

.5o .

| -

Nl \ .

n| :r a

,

L Q : - T

v.=

E.2

C

U

E

K

_U_ : : _ _ § _

. _# P

\ . i 3

___?m_

16

TABLE A-5 Sample means and standard dev iat ions of number of hours per year bywi n d spe ed H a s s : f i v e - y e a r ba s e p e r i o d s ( u = s a mp le m£ a n ; s = san»p1e s t a n d a r d

d e v i a t i o n ) .

Observed Values Values Obtained by Stochast ic Samp1ing(Monthly) on Base Periods

1966 1970 1971 1975 1976 1950for the Per1od

Hi n d Speed

U a s s ( m/ S )1956 1980

1s s S su 13 u u

1 300229

554

666

944

921

90

66

169

472

668

945

908

Z2

34

221

452

652

940

920

24 30

25

75_

25

75-

50

OO

75

25

75

50

.GU

50

31 434

682

31

38

as

38

57

63

86

40

17

75

75

aa 38

41

37

54

62

B1

42

1*

42 951

93461 37

1829

1500

m 7

1837 73 1857

1804

1568

59 1819

1760

1563

8 61

86

40

'50-11 33 145

11 .OU-13.50

13.50-17 .50

330 sr

1%

319 366 302

54 15 55 6144

6.6 5.817 7 6.6 4.2

1

8 3 0 1 1 3 17

s

4.3 MAXIMUM IMPAU 24-HOUR EVENTS

Bec au se we a r e p r 1 ma r 1 l y i n t e r e s t e d i n 2 4 - n o u r [a n d t o some e x t e n t

3 - h o u r ) a ve r a g e 1 mp a c t s , i t 15 i n s t r u c t i v e t o e xa mi n e th e f r e q u e n c y

| di s t r i but i o ns o f me te o ro lo gi ca l events which are known to be assomated

with peak 24-hour average impacts . A charar.ter izat1on of such events has

recent?y been deve1oped by Systems Applicat ions as part o f a power plant

S c r e e n i n g a! g o r 1 th 1 1 d e ve To p e d un d e r c o n t r a c t t o t h e u . s . EPA.1

Bas ica llv

t h i s s tu d y showed t h a t a CRS TER- ty pe Ga u s s i a n mod el w i l l c a l c u i a t e peak

2 4 - h o u r a ve r a g e i mp a c ts d u r i n g da y s i n wh i c h s e v e r a i h o u r s 0 * a s i n g l e

s t a b 1 1 1 t y c l a s s o c c u r r e d w i t h t h e wi n d b l o w i n g i n a c o n s ta n t 1 0 ° s e c t o r .

F u r t h e r mo r e , i t was f o u n d upon e xa mi n i n g s e v e r a i me t e o r o l o g i c a l d a t a s e t s

t h a t th e ma xi mu m number o f h o u r s o f a g i v e n s t a b i l i t y c l a s s a t t n e same

wi n d d i r e c t i o n d i d n o t va r y a g r e a t de e ] f r o m s i t e t o s i t e and t h a t t h e

va 1 ue s shown i n Ta b i e 4 - 6 u o o i d p r o v i d e c o n s e r v a t i v e i mp a c t e s t i m a t e s i n

»

a l mo s t A H c a s e s . Ta b i e 4 - 6 a l s o s e t s f o r t h t h e max1munn 24 - ho u r a ve r a g e

g r o u n d 1 e ve 1 i mp a c t o f t h e 60 0 MH un s c r u b b e d power p u n t ( T a b le 2 - 1 ) f o r

ea c h o f th e f o u r p o s s i b 1 e wo r s t - c a s e s c e n a r i o s a s s u m mg a c o n s ta n t

e m i s s i o n r a t e o f 1 g f s .

Using the definition of peak 1mpac.t evenps set for th ln Table 4-6, aJ

procedure ident i ca i to t ha t used for the one-hour events was car r ie d o ut

to de t e rmi ne t he d is t r i but i o n of the number o f c r i t i c a l events of a given

type per year for various peri ods . The res ui ts for the three f ive-year

base periods are presented in Fi gures 4-2, 4-3, and 4-4 for the A, B, and

D S 1.a bi | 1 ty c r i t i ca l events , re spec i i ve ly . These res ul ts are qu1te

di f f e r e nt from those for the one- hour eve nts . Means vary from one permd

to t he nex t a nd are much sma i le r t han those fo r t he one -ho ur eve nt .

V a r i a n c e s o b t a i n e d by re sa mp 11 ng f r o m i n d i v i d u a l ba s e p e r i o d s a r e i n SUITE

c a s e s g r e a t e r an d i n o t h e r c a s e s Eess th a n th e o b s e r v e d va r i a n c e i n t h e

1 5 - y e a r r e c o r d . I n c o n t r a s t t o t h e r e s u 1 t s f o r o n e - n o u r e v e n t s , t h e s e

n EPA contrac t no. 58-U2-3582 Pr e1 1m1n ar y r e s u l t s we r e o b t a i n e d by

A . An de r so n o f Sy stems A p p l i c a u o n s . I nprivate conrnunicat ion wi th G

8 3 0 1 7 2 IB

*1L°' L b . F<*ima1ef' 1T'»Bxim.J1" "q h e s t 24.hour average concent.rat1on5aa5..f* 1 ; co1"=.*H l w1r1?' d1=efr'o|" and worst-Case wind SDEEU.

Maximum E r b n d - L e ve 1

C o n c e n t r a tmo n *D i s t a n c eU r a t an

0 y Class of Event t o Maxi rrmr '

(Q/m? kmLx \- 's

A xn 2

A

998

13:

635

833

3.9?6 x lp

4.151 x 10

4.=5= A ]n

B

e(

T" I JL

Q

C o n c e n t r a f i o n wh i c h wo u ld oc c u r wa d e ' t n e g i v e n c o n c : i o n s f af t h e436 Hu \ . '< . c rub ed power p1a : {Ta n 1 e 2 - 1 ) I§sur=" '1g a c n n s t a n t e n vi s s i

1e o f l u

l i83017

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0 -. . _ _ . . . - - . V - - - _ . . . . - . _ - , - - . . . _ . . v\ . ¢ . - - , = - - . . . . . r

O b s e r ve r15 ~ y ra r

Rec o rd1 9 6 5 1 9 8 0

196 6 l 9 ? fJ Ba se

Permnd\ 9 T1 '

P g ruoaw g Ba se | 9 3 6

P e rund

a s e

I

FIGURE 4-2. Comparison of means and s tandard dev ia tions of the numberof c r i t 1c a 1 events per y ear for di f f erent sa mpli ng s chemes. Cri t icaT eveni s two hour s of A s tab i1 i t .y . (Bars 1abe1ed "observed" represent the meanand s tandard dev ia t ion across the 15-year record wi thout resamp1ing. ]

Z083 01 7

1

£1 Q

V

2- " 1 m o r e

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a

r

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oo ' va l Ba 5 1 9 * l . \ 9 r Bas e

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f the r .JVC H\. .-mpar"s.nr of I I IEa S a= : i st<= r . : ard d e vi ¢ : Z= : ne f l s p&r y e a r f u ' c a f f e f e f t . s a m ; f i r . ; s c h e n mc f E =;1 ab '1 1t j- i B a r s ' l a n e 1 e d ' 0 b ! ~ e r ve d " r e n

: de \£ ¢ t~ ;= = a ; r . : § 5 t h e 1 5 - y e a r F'e ;0r : ! H" lh Clu

F I I RE 4 - 3

c f 1 t 1 a1 e C r 1 t 1 c a l e v e f " 15r e s e n t t h e meahrL

d r reSamp' mu.)"

r :

a

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Sam( 1 1nf Sanli 1 nScheme Scheme

5|" " 1

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r /c

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1966 - 1986 B as eP er uud

IEUE 1985 B as f

"GrammOb se r ve d15 - y e a r

Rec o rd196 6 - \ 9 B f

] 9 T 1~ |

P e r1oo9 ` 5 B

9

FIGURE 4-4. Comparison of means and s tandard dev ia tions of the numbero f c r i t i c a i ev ents pe r ye a r fo r d i f fe r ent sa mpi ing schemes. Cr i t i c a levent i s 13 hour s o f D S t abi l i t y . (Bars labeied "observed" represent themean and standard dev ia t ion across the 15-year rec ord wi thout re s a mo i i nd j

22

83 01 7

resampling var1anf .e5 appear to be comparable to the observed variance i n

Ana1y5es for one-Year base periods produced s irniiarthe long- ' term record

re su ' t s (Table 4-T res ui ts forOne c o n s i s t e n t f e a t u r e d o e s s t a n d o u t

both the 5easona1 and monthly resamplwng schemes are qu i t e s t mi h r , as wa>

the case for the one-hour event ana1ys1s.

1 Based on the hunted ca1cu1at .ons presented here, i t 15 not poss ible

t o i d e n u f y t h e r e a S 0 n { 5 ) f o r t h e a p p a r e n t d 1 f f e r e n c e s i n t h e 2 4 - n o u r ana

Ho we ve r , i t i s tem| J t1ng t o s p e c u h t e t h a t1- hO f e s u H . s deSr . r 1bed a b o ve

t h e r e l a t w e s c a r c i t y o f t h e 2 4 - h o u r e v e n t s ( n o t e t h a t i n s o me y e a r s no

o f a y v e n ty p e o c c u r r e d ) nas s o m e tm n g Lo do n\1T.h th e r e 1 a t i v ee v e

l n c o n s i d e m n g th e s e r e s u T t s , 1 t s h o u l ds u e s o f t h e vB r | a r | ; € 5 o b t a i n e o

th e y we re o b t e m e d f r o m d a ta c m l e c t e d a t a sin g` !Pi n m m d th e*W KPJT

I t 1s p0 s s 1 b 1 e t n a t an an a Ty s 1 s p e r f o r me d f o r as 1 t e ( D h 1 l ¢ : e I p h i a

SHP wmT<1 prndure W f fe fe nt re sult sda ffg fn n f

23850 1 ;

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5 AWLICATION or RESAMPLZNG SCHEM§S To THE ExEx nswou

o

l n t h e pr e c e d wn g c h a p t e r two r e s a r n p l i n g sc hemes ( mo n th l y and

s e a s o n d ) we r e us ed t o r e s a mp le a s h o r t - t e r m me te o r o lo g i r . : a 1 d a t a r e c o r d

and th e r e s d t w n g d 1 s t r i b u t 1 o n s o f me t e o r o lo g mz a l e v e n t s we re c a l c u -

In t m ; chapter we turn our a t te nt i o n t o t he problem of us mg t heWatedr e s a m p l m g sc hemes i n ma k i n g e s t l m a t e s o f peak p o l l u t a n t c o n t e n t a t m n s

r e s u l u n g f r o m t h e em1s s' | ons o f an i s o l a t e d p o m t s o u r c e . i n n r t w c u l a r ,

we wa nt t o e x a m me th e Imp a c ts o f t h e h_»,fpothet.ir.a1 c o a l - f l r e d power p l a n t s

desr . r 1 Ded 1n Se c two n 2 . 2 . To b e g m 1-|r|T.h, we w i l l c o n s m e r o n l y 2 4 - h o u r

a ve r a g e 1mDac ts a s s o m a t e d m t h th e 40 0 Mk. p i a n t . B o th 3 - h o u r a ve r a g e s

an d i mp a c ts a s s o m a t e d w t h t h e sc r u b b e d a m un s c r u b b e d IUOU MH powe

p1 an 1s a r e dws nu s se o 1m C h a p te r 1 .

1 STANDART3 Exim; METHOD

C051-fwred power p1Bnt5 ermt vamable amounts of SUE aue to the

va-1ab1!1ty rn the su1fur content o f tne coal 1 t s e l f . A Monte Carlo

mmulauon method (known as the ExEx method), wh|C.|\ ls cleswgnec! to

m c o r p o r a t e Lhe known va r 1 a D | l 1 t y o f c o a i s u l f u r c o n te n t I n t o t h e a w

q u a h t y 1mp ac t as s e s s me n t o f c o a h f i r e d po we r p l a n t s , na s be en de ve 1 o p e c

for UAOPS/EPA by Systems Apphcamo ns, inc . TnrS method has been

extens1ve1y described e isenmere {H111yer and Bur ton, 1980; H1H_yer

N o r d m , an d B u r t o n , 1 9 8 1 ; Bu r t o n , S t o e c k e n i u s , an d h u r d m , 1 9 8 2 ] an d we

M H r e f e r t o ' i t 1n th u s re p o r t as t h e " s t a n d a r d " EJLEJ: me t h o d . By

" s t a n d a r d " we mean L h a t t h e d i s p e r s w o n me te o r o l o g y i s t r e a t e d

determ1nist1ce1\y ; one day fo i lous the ne x t in c hr onologma i or de r, as i t

1s c a lc uht e d f r a n c ns un, and only the ern1ss1on rate 15 chosen randomly .

Z51 T

Us e o f th e Ex£x me th o d r e q u i r e s t h a t t h e d 1 s t r 1 b u U o n o f c o a i s u l f u r

c o n t e n t be k n o wn . P r e v i o u s s t u d i e s h a ve shown t h a t a I o g n o r ma l d i s t r i b u -

t i o n may be us e d t o d e s c r i b e t h e c oa1 s u l f u r va r 1 a b i 1 1 t y f o r mo s t p l a n t s

( B u r t o n , Ha r d i n , an d S t o e c k e n i u s , 1 9 8 2 ) . S u l f u r d a ta f o r s e v e r a l n o r t h -

e a s t e r n po we r p 1 a n ts was e xa mi n e d an d t y p i c a i va 1 u e s o f t h e d i s t r | b u T. 1 o n a 1

p a r a me t e r s c h o se n ( s e e Tab 1e 5 - 1 ) . A g e o m e t r i c mean c o a I s u l f u r c o n te n t

was th e n c h o s e n ba s e d up on t h e c r 1 t e r i a t h a t a 1 0 p e r c e n t n e two r k p r o b a -D

Thusb1'tit_y of v'io1a1.ion would re suI t fo r t he 15-_year pemod 1966-1980

value turne d out to be 13.00 lb S02/MHBtu (see Table 5-2 ). In arr1v1ng at h i s r e s u l t , the Zh-hour NAAQS of 365 ugjm3 was used as a Standard and a

constant background concentrat lon of 60 ug!m3 was assumed. Although soon

nigh coal sul fur co nt ents are never observed, this mer e ly suggests that

the 2¢-hour NAAQS is not hmi t i n g f o r t h i s source. Smce we are only

interns ted i n t he intercomparison of Exba re s uhs here, the use of such a

nigh coal suTfur content should not concern us . Hhat is impor tant is tha

we are app1_ying the ExEx method to a si tuatwon 1n wmch app-ox1mate1y a

1 0 p e r c e n t NPOV i s c a l c u l a t e a

5.2 STOCHASTIC £xEx METHOD

I t i s re1at1ve1y s tra ight forwaru to inco rporate the \Tlo l\ thly ana

s e a s o n a l r e s a mp 1 i n g sc hemes d e s c r i b e d i n C h a p te r 3 i n t o t h e ExEx me th o d

S i n c e we a r e o n l y i n t e r e s t e d 1n 3 - and 2 4 - h o u r a v e r a g e s , i t 15 n o t

n e c e s s a r y t o r e a p p l y th e a tm o s p h e r i c d w s p e r s w n modeT t o ea c h sa mp i e

R a t h e r , t h e m s p e r s i o n c a l c u h t w o n s Can be made on c e f o r ea c h dayYearof the base period and the resamphng performed upon the normahzec

Eacn of me resampded years ofc o nc en tr at 1 o n e s t i m a t e s th ef ns el ves

normalized concentrat ions thus generated can then be Lreateo as a regular

I n p r a c t i c e , 1 1 i s mo r e e xp e d ! e n L¢eteoro1og1ca1 .year in the Ex£x methudI

to c onf ine the resampiing and £x£x methods 1n1.0 one step 1n umch each

random samp1e of 365 days is as-socmted wi th a new random sample of

Tms process has been 1ncorporat.ea 1ntLemission rates (see Figure 5-1)

a computer program called SYO.£XEX (f o r Stochastvc £xEx) (Stoeckemus ann

STU.EXEX incorporates both the seasonal and montnhNordin, 1983)

resamp'| ing schemes

26a a o u u

x HL'¢ Da

m p , d<¢ ' N ..>e_; , r ; : < LAL m a e

L

O a r a g m g tu n e 24 ur5

OH: 502Geornetrwc s t a n d a f s d e w a t r o r

ocorre1at1on c O J ;|

3P" Of Ge IC . 5 " f G 3 " C

4I

N E :O& : \ L ~ " C u Yr :

T=¥\P>-E 5 - L . S t f md a r d f x h mod el r e s u | t 5 f o r t h e 400 ""r\

Pr1;1ac1eT;>"\1a 0 . e r p " m t ,

1 e,- ~ao1ea'"5 mo'JeeC

13 UQ 10 5U2,'|~\.*~Br.uL:E'0m9t1'1L »» wau f af" CO"

0 . 4lxfmu11 exper t exc -:ance

12k pr o b a m| 1 r . » , 0

ula §.

2 ug /m: t e a n a t* i x t m u m =

nc | L r ~ 1

uo n dv

N

|m

n:IL

27£ )17 3

I

EmissionsDi f fus io n

S t o c h a s t i cS t o c h a s t i cTreatmentTreatment§ Meteor-u'|ugy

Simu|ation

3

s t ic Exi x me thod (see Figure 5-IbFIGURE 5»1a. Eiements of the s tochafo r det a i ls o f t he s immat i on mo de1 )

za830 17

¢ 1 z

Lo __:c_f#_i

§ ____

I

\

E1:1

g==\, , -~-

_co

Yco_

c :OEE

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1 :; ~ '

T \=¢

~; z =

E E W5

.Ex I

/I

= \ /.=, _~- ' s

u -C'

/f

S Z E B

: EEES E

cu

/ \E

_ ;____:__ _:_____

_1 c_cC._

.Ci- I\

LD

___

___

E :

I

_`__ : _ g _ o _ _ S P_ :_______ ___

_ ___

83 01 ?29

5.3 conpmlson UF STANDARD IND 5,1(,Lhf\:*IC Exim was

I d e n v c a i Base P e r i o d s3

O: o f s h o r t - t e r m v e f s w ' 0 1 \ ; - t i f mBefore embarking 0| a com;ao Iresn:1ts, ' l t i s ins t ruc t we t o exar mne the ef fe c t s of resamr11m. or h h

n o r de r t o do t h u, both the s tandard am: st.o¢r|<a'=tz; 1̀1:O"1V11r e s u l t s

Exf ar. me th o d s we re a p p l i e d t o th e same on e - a n i f w e - y e a r ba s e p e f m o

l l k t n from the Ph1| |delph1a lneteorohngic f ! data f11e. R1-su|t§ fo

the five-_year periods are shoum i n F1g\;'¢ 5-2.

V

o r b o t h th e o n e - a m f w e - y e e r p e r 1 u r > the m6x' mU1" exp e f t e o

exceedance (HU re s uhs are comglarab'e between the two mEt'.<1GS. Thu

\ . l t nSeems r e a s o n a b f = f r o m an E n t u m w e S 1 a \ GL : " 1 I Iof sarnp1e years, each day of the base permci M11 have been chosen

a p p r o m m a t e l y an e n u m numD¢' o f 1111125 a n ; th e ' f 3 ' 0 r e an a v e n u e Ove ' e

sa mp le _years H111 proGur .e a p g f u x wm a t vl y t h e Sarre Pu"1bEV C4 e xi e e d f w_ e s

ha d ea c h day been c h o se n e x a c i l , onc e f o r ea h san. e v e a ' . UT l.>LVE\:

t h i s Es o r e m s e l y wh a t hap pe ns 1n : r w stafwc fwa F x l x mmh o d ana we m . i

a

Shui .~, m e s a w Tuf b o t h mexno c ae r e f o r e e xp e n t t h e MSE rL"> .. 7t

uc h a l u x e o f t h o u g " : :mes n o t dD{1E'af a p , " u ; f 1 a L e f o r t h e c a s e Q*r

t h e n e tw o r k p r o b a b i 1 1 t y 01 v w o l a t t o n s

one c o u i d a r g u e t h a t , s1 nc e t h e r e 1s a

c o u i d be c h o s e n mo re th a n onc e i n i n e

o f f i n d a n g tw o o r mo re exc e e da n c e s ' n

g r e a t e r i n t h e s t o c h a s t i c

Ho we ve r , t h e ma g n t tu d e o f

o f t h e HPU¥ r e s u l t s sho wn

c l o s e t o one a n o t h e r . l n

ExEx me th o d

t h i s e f f e c t

i n F i g u r e 5-

f a c t , ba s e d

{ h i c \ } r e s u i t s , h o w e ve r . l n f a c t ,

n o f f e r o p r r f a r mlmty t h a t ea c h d a ,

s t o c n a s t wc me t h o d , t n e p r o b a b ' 1 1 t 3

a f ; g1 ve n s a m; . e y e a r s h o u ld be

th a n i n t h e s t a n d a r d me th o d .

may be q u i t e sma11 An exa m1 n a t1 o f

2 r e ve a 1 s t h a t t h e va tu e s a r e q u 1 te

upon th e ma g n i t u d e o f t h e samp11ng

s i g n i f i c a n te r r o r s d e te r m i n e d i n S e c t i o n 6 . 1 , t h e r e a p p e a r s t o be n o

d i f f e r e n c e 1 n th e NPUV r e s u 1 t s b e twe e n th e s e tw o me t h o d s , a t l e a s t f o r

|

a p t e r 7 , d i f f e r e n c e s we re fouV1Gt h i s par ticu1ar s i t e . As dzscussed in Eh

to be much la r ge r a t another loc at i on (St Loans)

83 0 1 ? 1. 30

-w

\

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Q O o

U K1 l l

v m

mir v d a i t * ¢

f x { I f n

| ¥ Y | L H F "

! f x

_ - . - - » -

N .

1 .

m g .

\ f

' - - a - _ "`1

i; I11

L I L

£ aI

K.I

J

s

i1

~;

- . . . . . . - - - . f - - - . . _ . . . ' . . . . . . - F . . . - . .

N

FaAN 2| Qdx Ba

F r

FIGRE 5-2. Comparison of resu1ts of t he s tandard and s t och a s f

£>E» metwcds applied to f ive-year base per:ods (400 Mn power i a n t . P'~1`lade1phia meteorc1ogy'.

I

E L

31

c o mp a r i s o nue

to be no s ign i f ica nt d1 f f ere nc es

c o n s 1 5 te n ta r e c o n c e r n e dHPUV stat ist ics

subsequentC h a p te r

Stochastic

a p p 1 y i n g s t o c h a s t wrwe p r e s e n t t h e r e s u h s o fI n t h i s s e c t i o

displays the MEE and NPOv values obtained by app\_»1rFigure 5-4r from 1966-19B A large amount of year-Lu-

botn s tat1s t1cs . In f act, o f i y o ne out of thes t o c h a s t 1 c Ex£x to e a c h

v a r i a b i l i t y

method seems to promde st a t i s uc s NDN a r e u & " g r e u f f estochast ic £xEx

I fwe -ye ar long base permcis (seep r e s e n t r e s u i t s ba s e d

v a m a b w h t g

wsecond-highest concentratwn results (Table 5-3andba s e p e r 1 o d Lo th e n e x t . I n f a c t , f ov a r i a t 1 o n f r o m

f o r b o t h t h e o n e - anos t o c h a s t i c ExEx me th o d s

p e r m d s , a l ? o f t h e s h o r t - t e r m va l u e s o f t h e s e s t a t i s u c s .f ive-yearn Table 5-Z. Tms1ong-term va1ues

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TABLE 5 - 3 . Maximum e x p e c te d h i g h e s t and se c o nd h i g h e s t c o n c e n t r a t i o n s

a s c a l c u i a t e d by th e s t a n d a r d and s t o c h a s t i c ( m o n th l y ) E n i x me th o d s

( 4 0 0 nw power p i a n t , P h i l a d e l p h i a r r e t e o r o i o g y ) .

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2nd H1ghest(ug/m3;

£xpecte<1Hi gI\e5{cw/m3>

ExpectedZnd Highest

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e a

281

252

242

224

243

266

2311

332289285259283315281

2255.11321

282

274

245

273

308

269

1966

1g5?

1968

248

238218239261232ZH2082?8280273

1969

1970

1971

1972

1973

1974

1975

1976

287

216

231

293

276

245

260

283

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341

314

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* S Q F V CG 1 0 ' a v a r 1 a n 1 ¢ e m l s s i g r f n i e b u ' C C 5 u . » + w T 1 " c I y a

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h 1 g h e r s e c o n d - h 1 g h e s t

h i g h e x i c on c 9 \ \ Ua T. ; ' " : . ~c 15 ; \ c "»~ ' i c t f a t \F\ ] l

some $ a m; 1 e - y e a r s \ t h 0> E 1n un _n th e : d y c t c f

i s c h o s e n mo re th a n onc e§ \ 1 ] \ ac c oa1 1y h a ve e

c o n c e n c r a t 1 o n th a n wo u i o oc c u r 1n t h e s t a n o a f n

£ x£ x r . n o d . Ho u e z e r , su c h s a n p 1 e - y e a r s a r e l e s s 11 xe1 y t o o c c u r t n .

t h o s e i n wh1c h c h e day o f th e h s g h e s t c o n c e n t r a i i o n 1 s c h o s e n o n : e o r

n o t a t a 1 1 . Th e r e f o r e , t h e e x p e c te d s e c o n d - h i g h e s t c o n c e n t r a t 1 o n a sc | 1 c u 1 a t e d by t h e s t o c h a s t 1 c me th o d H111 s t1 1 1 be 1 : 5 5 th a n t h a t

c a 1 c u 1 a te d by t h e s t a n d a r d me th o d .

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e x p e c te d Nth h t g h e s t c o n c e n t r a t i o n s . Th i s 15 t o s a y , f o r a g 1 v e n m e te o r o -

1og 1c a1 y e a r th e h t g h e s t ( o r Nth h i g h e s t ) c o n c e n t r a t i o n i n any on e samp1e~

y e a r te n d s t o oc c u r a t t h e same r e c e p t o r an d on t h e same day a s i n mo s t

o t h e r s a mp Te - y e a r s . I f t h 1 s i s t h e c a s e , t h e n th e ma xi mu m e xp e c te d Nth

h t g h e s t c o n c e n t r a t i o n as c a l c u l a t e d by t h e s t a n d a r d E x i x me th o d e1 11 b e a t

I e a s t a o p r o x t m a t e l y e q u a l t o t h e maximum Ntn h i g h e s t n o r m a l i z e d c o n c e n t r a -

t 1 o n Las c a 1 c u 1 a te d by th e d i s o e r s t o n mod e1) twmes t h e mean e m i s s i o n r a t e ,

and th e ran dow s e 1 e c t1 o n o f da y s e111 p l a y t h e d o mtn a n t r o l e i n t h e

d e t e r m 1 n a t1 o n o f th e maxtmum e x p e c t e d Nth n t g h e s t c o n c e n t r a t i o n 1n t h e

' A

Then, by the argument presented above for aExix methods to c h a s 1 1t o c n a s m c me th o dc o n s t a n t em1 ss1 on r a t e S o u r c e , we wo u lu e x p e c t t n a l . w e :.

wi ! p f o d u c e i o we r ¢;on c er~ traL rons th a n th e s t a n d a r d me th o d

As a way o f e v a \ u a t1 n g t h e va 1 1 d 1 t3 o f t n 1 S 11 ne o f r e a s o n wn g , we

ha ve maoe a c ompa r1s on of t h e max1mum Nth h 1 g h e s t n o r m a l i z e d c o n c e n t r a t i o n

twmes th e mean emws sxon r a t e (a s s e t f o r t h 1n Ta b l e 5 - 4 ) w i t h t h e c o r r e -

soo nowng max1mun e xp e c t e d Nth n 1 g n e s t c o n c e n t r a t 1 o n (a s c a1c oW a teo by t n e

s ta n Ga " d me th o d , see Ta b le 5 - 3 } f o r N = 1 and 2 . The r e s u l t s a r e shown un

F1 g o r e s 5 - 5 and 5 - 6 . E r r o r b a r s ha ve been 1n c 1 ud ed t o show t n e e f f e c t s o f

sa mp la n g e r r o r un t h e E x f x mod el on t h e mean em1 ss1 on r a t e c a 1 c u 1 a t 1 o n .

A l t h o u g h th e r e 1 a t1 o n s n 1 p be twe e n th e two q o a n t 1 t 1 t e s i s f ar f r o m p e r f e c t ,

some d e g r e e of c o r r e 1 a t 1 o n 15 e v 1 d e n t . Th 1s s u g g e s ts t h a t t h e r e a s o n s f o r

t h e o b s e r ve d d 1 f f e r e n c e s 1n th e ma11mun e xp e c t e d Ntn h xg h e s t c o n c e n t r a -

t 1 o n s be twe e n th e s t o c n a s t wc and s t a n d a r d E x i x me th o d s may b e i d e n tw c a l t o

th o s e de s c r 1 o e d aD0vE f o r t n e c o n s ta n t em1 ss1 on r a t e c a s e .

B o th H g u r e s 5 - 5 and 5 - 6 Show some b u s to w a r d m g h e r e x p e c te d va l u e s

as c ompar ed t o c o n c e m r a u a n s c a 1 c u 1 a te d u s m g th e a ve r a g e e r m s s m n

r a t e . A l t n o u g h th 1 5 w a s 15 n o d o u b t a r e s u l t o f t h e s e l e c t w e e f f e c t o f

t h e max1mu1" o p e r a t o r when a p p h e d t c a s e t o f s t o c h a s t w . v a r i a b l e s , we

know of no £ 0 n c ! u 5 1 ve way o f s h o w mg t h a t t h 1 S 1s ma e e a t h e c a s e .I

we fwnd that the re la t we magni t udes of t he Nthln conc lus ior

a l a a s 1 g n 1 f 1 c a n L r u l e i n d e t e r m 1 n -h 1 g h e s t no r ma 1 \ z e d c o n c e n t r a t1 o n s 0 p y

d c o na n1 g h e S t c o n c e n t r a t i o n s ,1ng th e max1mum e x p e c t e d h i g h e s t an s e

a E th o u g h th ws 15 c i e a r l y n o t i n e on1y f a c to r i n v o T v e d . Ne ve r t h e i e s s t n 1 s

3 1Q §{ ) j l

is

cn cu] atedx luesh ig h e s t v aMaximum5-4TABLE

PM 1 aae1 phi ap la nt ,un s c r u b b e dnu(CRSTER) for the 400mode!dispersion)l b 502/mmme 1322emss ion r a t e( I ln e t e o r o lo g v

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f h l f 1m umbe n a vwo f dun seem t o sup por t o u r a r g u me n ts an Lu L n : l t u a u u a . - - m-

e xp e c t e c Mtn n 1 g h e s t c o n L e n t r a t1 o n s a s c a i c u i a t e d by s t a n d a r d £xEx a r e

e n e r a \ 1 y I a r g e f t h a n th o s e c a l c u l a t e d by s t o c h a 5 t 1 c E x i x .

An o th e r i n t e r e s t w n g f e a t u r e o f Ta o i e 5 - 3 1s t h e d e g r e e o f va r 1 a b i 1 * t y

w th e ma\ \mum e xp e c t e d Mtn h 1 g h e s t c o n c e n t r a t1 o n s f r o m one y e a r t o th e

n e x t . Tne se c o n c e r t r a t t o n s e xn 1 b 1 t l e s s va r 1 a b 1 1 1 t5 th a n d o t h e NPOM anc

ME? r e s u l t s p r e s e f t e d e a r 1 1 e . I n f a c t , a l l g f t h e va l u e s i n ea c h c o lu mn

0 a n te 5 - 3 f al we l l » 1 th 1 n 1 2 0 1 0 * t h e " r e s p e c t 1 v e mean v a i u e s .

Ho s e ve r , t h i s 1s n o t t o S63 t o a t mdxtmum e x p e c t e d Nth h i g h e s t c o n c e n t r a -

t 1 o n s a r e n e c e s s e r t l y s u p e r i o r Hn dwc e so fs c t a 1 r a u a i t t y i m p a c t . when

c o n5 1 Qe r 1n g t n e s t a o 1 1 1 t y of q u a n t 1 t 1 t e s Suc h as NP U. , u s a . an d max1mum

e xp e c t e d NLP h1 g he s 1 c o f c & " tF a t 1 o n 3 , i t 15 o e r n a o s mo s t me a n tn g f u l t o

examwne to e s t a o 1 1 1 t ; 0* em1 ss1 0n t t m t t s ba se d on ea c h o f th e s e q u a n t i t t e s

Stnc e 11 1s th e em1 ss1 of 11m1t uhmc h i s d 1 r e c t 1 ; 1 n v o lv e c tn th e r e g u 1 a -

t o r ; p r o c e s s . As né w11 Show tn Cn a Dte * 6 , t n e p r o c e s s by wh c n em1s S1w

=1m1ts Do>€G on HPU\ va ues a r e o c ta a n e d r e s a l t s t o a s t g n w f t c a n t i f 1owe

aa ' = a o ~ 1 1 t3 mn e ts s wo c 11 mwts tn a r ws e " | o 1 t e c Q. th e u n d e c ly tn g NDUV

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t \ me no suA'znougr~ at the presefwna.->n=. un em ss 1o r H m m sv u . . . . ~ _ _g e s L 1 o n s h a v e b e e r p u t f o r t h a s t o h o n t h e m a x w m u m e x o e c t e . N t r n 1 g h e s t

L o n c e m r a t w o r " m w g n t De u s e d t c c \ e L e fm 1 : > c a r e m 1 s s 1 o n 1 1 m t , i t n e v e " t r l e -

l e s s S t r : 1 5 ¢»as f | ¢ ; W e t u e x p e c l t h a t m e r e s o o n s e o f t h e m a x i m u m e x o e w e o

Nth h| gr .»¢st c ~»=. \~nUet1- ,ws t o c h an ge s 1n t h e g e o m e t r u meav ewwsswon F a te

w l l ne a p p r c f m a t e i y } " . » ¢ f . I n t s c a s e , t h e r e ' a : 1 v e v a ' 1 a b 1 i \ t y o f

t h e <1:|1SS10n h m w t |1111 me Lhe same a s t h a t ~ th e me n mu m e xp e c t e d Nth

n i g h e s t c .onr .enLr at1o| on wm c h 1 1 15 b a s e d . Tn e r e ' o ' ~ e , i n pr a C t1 C a

te rms. , t h e maximuw e m e c t r c N w r r g n e s f . : o n e n 1 . r a t \ n = > may n o t be § n 1 f 1

L a n U y mo re s t a b ' € Tron ow- . w a f t o th e n e f i t h a n any o t h e r me a s u r e .

418 3

6 [FFLCTS OF METEUROLOGICALON EMISSION LIMIT DETERMXNATIUNS

Strong var1aD111tyIn Chapter 5 we presented resu1ts which suggest

a i r qua 1 i t y impact assessments\ th1s variab111£y on act.ua1 1im1ts wmcrexa mi ne the e f f ec i . o fc h a p t e r we

upon emiss ion ra tes due to these impact assessmentsmight be imposed

ear.amp1e, a p la nt em1ss1on5L0o p e r a t o r mi g h t be

a n e m i s s i o n l i m i t d e te r m i n e dmuch wi llme L e o r o 1 o g i c apa rt icu' lar year years

quest ions are taken up 1n theus ing the stochast ic £xEx method? These

METHODOLOGY

1\m1tsfor determ1ning

representat

1the coa\ su1 fur d i s t r i but io nac o n j u n c t i o npercentTab'|e 5-1. Thi s v a lue, known as the compliant

be ca1cu|ated f a i r ly eas13y by apply ing the £x£xparameters listed

\ gganetrici te rat ive f ash1on, adjus t ing the geometr ic mean during eacn

o p t i m i z e d

s tochast ic ExEx me th o d ha s been

M1 N1 . £ x£ x ( S t o e c k e n m s andknownincorporatea

Hhen c o mp a r i n g c a n p h a n t g e o m e t r i c mean e m i s s i o n r a t e s , i t i s

imp or ta n t t o ke ep i n mi n d t h e e f f e c t s o f sa mp| ' i n g e r r o r s on th e va 1 u e

o b t a i n e d . S a mp i i n g e r r o r s a r i s e as a r e s u l t . o f t h e f i n i t e samp1e s i z e

{ 1 . e . , number o f sa mp 1 e - y e a r s ) us ed i n th e ExEx me th o d . L a r g e r sa mpI e

s i z e s r e s u l t i n S ma i l e r s a m p h n g e r r o r s a l o n g w i t h i n c r e a s e d u s e o f

1c o mp u t i n g r e s o u r c e s . Th e r e f o r e , t h e o p t i mu m s a mp le s i z e i s t h a t wh i c h

r e s u l t s i n th e maximum a c c e p t a b l e s a mp l i n g e r r o r . To d e t e r m i n e t h e

ma g n i t u d e o f th e s e e r r o r s , c a l c u l a t i o n s we re made f o r b o t h t h e s t a n d a r d

an d s t o c h a s t i c me th o d s i n wh i c h r e p e a t e d d e t e r m i n a t i o n s o f t h e c o m p l i a n t

g e o m e t r i c mean we re c a r r i e d o u t u s i n g i n d e p e n d e n t s e t s o f r a n d o mly dr a wn

e m i s s i o n r a t e s . The r e s u i t i n g v a r i a t i o n s i n t h e c o m p i i a n t g e o m e t r i c mean

e m i s s i o n r a t e s a r e a me a su r e o f t h e s a m p i i n g e r r o r . Ta b le 6 - 1 p r e s e n t s

1|

It h e r e s u l t s o f t h e s e e x p e r l m e n t s . I t s h o u l d be n o t e d t h a t , s t m c t l y

s p e a k i n g , t h e s e r e s u l t s o n l y h o l d f o r t h e p a r t . 1 c u la r l o c a t i o n , po we r

p l a n t , and c o a l s u l f u r c o n te n t r a n g e m d i c a t e o i n Ta b l e 6 - 1 . He ve r th e

l e s s , l t seems r e a s o n a b le t o assume t h a t t h e n o r m a l i z e d s t a n d a r d e r r o r Iremain f a1r1y cons tant for a given samp1e s izeu i i w

mssxou Llnrrs BASED Oh SNURT-TERM ns1£onoLos1cAL UITA SETS6.2

F i ve - Y e a r Base P e r i o d s6.2.1

Compliant geometric mean emiss ion rates were c a lcula ted by both the

standard and Stochastic (monthly ) ExEx methods us ing the five-year base

periods 1966~19?U, 1911-levs , 1976-1980. Figur e 6 -1 pf csent the re sult s

of these ca lcu la t i ons . Di f ferences between the stochastic and standard

methods appea r to be qui te small when compared to the sampli ng er ror s .

This is to be expected i n view o i the f a i r ly small di f f ere nce in the NPUV

re sult s shown in Fi gure 5-2. Di f ferences i n t h e r e s ul t f rom one f ive-year

base pe ri od t o t he nex t are such that a l i of the values f a ll wi t h in s 5

percent of the average fo r t he standard method whi le 6? percent f a ll

wi t hin t h i s range fo r t he stochastic method ise e Table 6-2 ). For both

methods, 6? percent of the values f a ll w i t h i n 1 5 percent of the compl ia nt

geometric mean fo r the 15-year record 1966-1980 (as determined by the

451 7

I1

0

I5118-4 Q Q

1 n c F F F GQ » " 1 [

/ 1n w

I

/

St nnoa f c S t n c h a n x r

E: =-< £v

F

|¢J

l .1 IIrP

LJ

Icc

;I

1* i

1 I

i

s5 4 QMm i l

w p 1

U1 I

q g

r4

LULUl

(, gg1Ba

I1

F1355 E 1 Co|'1;.:111son of cor1p1iant geanetfi; meafer ss : f 1 r a zus de r we d f r o r the s tandard ExEx and sC* : s t u his me thods for 24-hour ave rages (400 nw;-n»e» ma nn, Phi lldeTpr. : l meteoro1ogy} and a base

ne mo : 1en; : r o f Hw e t y e a r s .

+ E"

45830 1?

I

o

TAB1£ 6-2. S\.l111Ilary of <.om;.T\ant geometrin mean resuhs

o f P e r H d s F a ' 1 F

H i t h 1 n 1 5 1 g f t h e

A ve r a g e Ove r A HBase Pe r 1 o d s °

1 of Per"io:1s Va Iin.,H11'.| l1n g 51. g f t h e

1 5 - Y e a ' Com: \ '1ar tGe n r w t f i g Me an t

No . 0 *

Ba s e D r i e d ;

f r Rf ; o " CIBase Pe'*od Lew! *1

5 1o n35 years

3 yearsI y e r

S ta n d a r d

Ht t h o j»

QR

111 :

F »

" P61So

3S t o c h a s t i c 5 y e a r s

Me th o d 3 y e a r s

1 y e ar '

55a4 0

1a

The nllhberi 1n th1s coTu' m were ca|»;a etrd by f i rs f comput ing the avef ags nfcompl1ant geometr ia mea' values *ounz fo ' e ac h bas e pe "' od an: then de ze -- -1the nunber o f ba se pe riods \ rh:n har: va 'ues u1 t | '€r 1 51 of the aver age. "number was ' l| : : \ "l expressed ls I perce"1age of the tnta` number of bas? ,.J(""I=S

the 1 5-yea r rec ord.The 15-year cor»;\` !1ant geometrw mean 15 |p: \*ox1mate'y 13 Ib S;= *M~!i1. asdetermined by the s tandard inf : method (ser Table E-PE. `

m e

I1 n

I

I

6o n

ve-yea com;~ 'an: V HI HMB L U. NME* o f *rn * 1

15 rrJ'rP th a n 8 . 8 3 |D SU2fHMbnethod of 1.%.Gl

t awav f r m f n~»» 1r~ H g u f e

n g - L ~ 1 Pe S u ' 1

Tn ».v ~ an . :1

a r E m w m g p1 : ] . E § 0 L P ; e I v e T . h f E 9 - y e a V b a : r

,t h e t h " e e - w a ' ha s

B"€19t o one a n v r h e r , t h e 1 9 i 5

r ¢ V \ O G § D r e |LJrT!p 15 wah#w l t e f y w a s n n : ' f E 1 n w u n s 1=f==:ern. N t h o u q r. i t m a y b e

p e I 0C Gm

na lQ { j \ 5 r P C I G V G T.h a p v r 1 0 G B 5 ci v

L i

pre fe= u.e g f su c r r ar 'oma1ous Lhree-_y ear ; J : . f 1 u: wh i c h pr1n tf~ t o t h e

re*\»frf.f1 we assumuwov Lhal a 'long-term re£ 0c 1sda wg e f s ¢» s 0; 1 a1 +

a b i e 6 - 2 , a g r e aii h r r l - y n" Q w e s t Led

m a n n ~¢ - e s fe| ` e w1 th 1 n 1he Lh r 9 - \ r d f 5p

r T."r Ca>E Tjm the fwe-yea basepef aevi 0* r w 15-~*

o for 1 e eip '"@~i1c meva howew{ \ p r 1 f \ r * & T h \ S S T T . . a 6 I | 0 r 1 5 7

I

HC J . ; U|

4 n Q im e e - 3 ; e : = : r \ 1 5 n f e r e g 1 1 5 L ' W * g Q r ; p 1 1 B i r ng mea

I m e Wa"Due tcern|s5\ur f ates ca|cu'a1ed on ore-_year base per wcs2 s u e .'§J) was »~= rww v o l v e d , a sr-1a'Wer sam

(1t l T\ |!.E\nu|Tr ' ' ' A n h t h e s a m ' l i n g e r r o rI f H stof.h»=~.t1c |n\ -.mar c1e=.e m1 n a . i o n . ut. o u g P

Hr qe rs a n mle s i r e 0* 50 '| s rw? know \ 11 i s c e r t a i n1B vd is

vPn 1n T n t ' e 6 - 1 . As c o m; f r m! t o 51L;LHB§ 6 - t and fa-2r m T ' e

va r 1 a D 1 l 1 l y um Jwe Dd5P1eP1uC t o t h e n€>{ Show" 1m Tab v 6 - 3 i s qu LP

f .F1

l a r g v as th e f 1 g u r e s 1| i d i v 6

va ue5 J r * e r m1 n e d by e ' t n e r mezw

U e S t ln f a c t , l e s s th a n h a i f m Q

Od f a l l u1 L h1 n 1 5 ve r c e n t * LHP a» P f 5 v

I

41b i n

/

FIGURE 6-2 Comparison of a n t QBOn1Etr1c omf 1 E

fror' Sianivedr a t e s der dard an amean e w i s s i o n

y(monih 24-hourstochasucA p1ant Phi\ade1phvMuOO pm - re raveragesmeteohnlogj |̀ le ngt '

\

l' A B I T E 3 . C o m p a v i s m o f c o m v H l n r g e o me t r i c m e a n s d e r i v e d f ron-

t \ - ' \ E l f . : me th o d s f o r 1 - y e a r b a s e pe" io£1Ss te f \ a a ' f ! n j s t o c h a s t i c [mon . y .

HC n a . , U" i ` a d e 1 p * : £ . 1 me te o r o 1 o g y } ,

mrT1a"t Geomet'1: ; 1b 502/MMB1J"

H " _ " _Stochast1c MethodA Nefh°j {monthTv\ 'R Q@

I :dQ . f

11.f=2.191~ 5

1 ~.1

1 - s a

1 3 . 0 3

1 3 , 4 4

1 4 . 2 1

, Q11

1:

1r.*!139

l1 .70

12i: M13.9"

11.v5

15.31

1213

22511

12T'5>10.25H

12

76 |63

1 713119

U3w e7012.59»~

e s 1z » ~ o f1 Computed using a

|

a~J

I

z m n s m (DT R£$L'U§ TO OTHER AVERAGINQma i s s o u m TURB, ANU LOCATIONS

7

J

lA l l o f t h e r e s u l t s p r e s e n te d th u s f ar a r e f o r an a ve r a , 1 r . g t i m e o f

24 h o u r s and we re d e r i v e d f r o m n o r ma l i z e d c o n c e n t r a t i o n est1rnaT.es made f o

nw, umcfubbed, co.°1-burrwg; power Ma nt using meteef cnhngwcal data1

a a o

COHQCIPC at Phi ladelph ia . I n t h i s chapter we seek to determwne the

0U fm ww 5degree to whwch our re sult s new fo r o t he r s i t ua t io ns

focus our a t t r wmor on Exim modeling resuhs ana Eofr; HT g e o f t t f i c mf:

emus lon rates for each of tne f mlo ui n, c a s e s

|> 3-llOu" averages; 40? Hb. urwscrunbed power p' Iant ; Pn11a

df" ; mia meteu"o' o.,y

(me' r1=~f= ""?4-hour averagw 1L\ Hb. 5

1 F rvd l1e1ea1fL?L

mmf averagw IDO. m. |m»;"ut'Qvd p

St. L0. :15 Ilkieufuiogy

&§_HL\n 1 ":\1:NG

Comphant geometric mean emiss ion rates for thr ee-hour averages wend e te r m i n e d i n t h e same ma nn er a s d 1 s c u s s e d 1n C h a p te r 6 f o r t h e L n r e e

f i ve - _ : e a r ba s e p e r i o d s : 1 9 6 6 - 1 9 7 0 , 1 9 2 1 - 1 9 7 5 , a n d 1 9 % - 1 9 8 0 . As F1 9 ur e

7 - 1 s h o ws , 1 0 0 p e r c e n t o f t h e v a l u e s f a 1 u | t ! \ 1 n 1 5 p e r c e n t o f t h ea

a v e r a g e a s was t h e c a s e f o r t h e 2 4 - h o u r a ve r a g e s ( T a b l e 6 - 2 )

8501 ? 1.50

I

r QI

J

,/~ rm~ A

1 I¢

T L1 E

= 1

E i lz

E ;

M

l ~ 1 J I

vL . \ [ 1I

5loc

19?1~ I 9

Bas e " e f1

|\ »

n f l ge3r=E'1-fic mean emissiunsta»":¢-a Exim method forL* Hn mower- Mant. Phi`lade1phia

F E 7-1. Lff : f~ ~ f r

s:> A \

I 1»as

HH SCRUBBED POND? PLANT2 1

emission rates were calcula ted 1n a manne

p r e s e n te d e a r I 1 e r f o r t h e f w e - y e a r ba se p e r i o d s us 1 n g

£xEx me t h o d . The r e s m t s a r e sho wn nn F1 g u r e 7 - 2 . l n t h uthe standard

per io d, f a ll u i t h m 1 5 percent of thepercentcase,o No te t h a t t h e c o m p l m n t va l u e s a r e a M mL.:n sma1 1er f o r

average value5 15 :Jue t othe 4-no Hin unscrubbe: ur11t h i s po we r p 1 a n t th a n

muc h g r e a t e r buo y an c y

t i o n s p r e s e n te d h e r e

eo f th e u n s c r u b b e d | T a n t

£ 0ass ume t h a t a M o f t h e 5 u ! * . . ' i n t h e uve 1s o x

g s t a c k , t h e y a r e ar t 1 f 1c 1 ¢ 1 1 y lo w f o r a S-"1JDl'can d r d e a s e d f r o m

e m i s s i o n r a t e s c an b e f o u n d Dy s c a l i n g t h e r e s u l tun1t 1 Com;

|11w l w t to the scrub:er e f f11;1e

e f w a t t h ebi.ch.:>P such 5 sig Hug u

e ba s e D E " L C t o t h e we

t m t£ur;.:f S t c e » c " . ' , anc mf aAs par t a

11r ratES u r e n.¢z.1e * c r t h e p e - 1 n d E9 3 -1 % - ' T f

p : a n t u s i n g h u e y e a r s o f r n . L o d i s me t e d r o

Th1s d a t a S e t p r o v i d e d t h e o p p u r t u n l t y t c

o f a new s i t e u s 1 5 g t h e t o o l s d e ve lo p e d f o r

s t s t m c o a l su11'ur U1 5 lr 1 h . . ' l1 u r p d r a r P t a r s

r G i 1

f

o f s t a n d a r d an a s t o c h a s u c £xEn r e s u l t s f o r a l l f 1 vEA

Tms shoL.'d be compared to F|g\."e~|presentedI t s f o r P I 1 l a d e 1 ; * 1 | a . Une o f th e mo s t1090115 resuwhich presents

important chfferences at St . Louis ' is that use of the s to cha suc Extxf higher NPDV values tha n are cbtamed f rom the

Mthough we expect . the s tochasuc NPOVS to me

we know of no paf t1cu1ar reason why tms

much more pronounced at St . Louis . In ge ne ra l, ofdi f ference shouh: be'I ts depend upon the tempora l and spat ia l d i s t r i pumo r

52

I

I0

_J

I

;we

i 4

.1

- I

I|

III

§I LI

r 1;-L f ?4

Sees ' e

I

I

§ "3',¢1§ T~2 m w wa r pnv<<~¢.-'E' x 'I r a s d 9 " v e

f g f U 1 6 T S Q . u funn E LHP r ! rgaorD*"'a rn:d v € ' & £

I

53ga

TABLE ?-1. Parameters of the 1ognorma\ coa1 sulf ur c ont entdi s t r i but i o n us e d i n t he Exix model1ng of the unscrubbed 102 Mupower p1ant wi th St . Louis meteuro1og5.

<Averaging t ime

1 5 y u Ur \Geo metm f 5 tance P0 : levi ai 1

0.60A u tu 2 0 * r e 1 a t 1 o " c o e f f i c u f

3Number o f g e o me t r u : sta n da f c

d e v i a m o n s a b o ve th e mean o f

t h e l a r g e s t n1| owe< v a h e

I J D I 7 s 54

I

I

\ \ \. .

\ ~.. , ~

\ \ \ \ \ \ \ \ \ \ \\ \ \ \ \

\ \

:aaz

\ ~ \ .\ \ \ N

___ _ . . . . . .

. . \ \ \ \ `i ~ >

~ r

i i :H

>,U1C!

¢

_OLONQE WZO m @Em3 £Q_Wm$E WU KMK LMUCMM

Q\

fi IE=

\I

LU;DQ UDDILQQCS lxC® KXm U mM£UOw

\ . \ ` \E

WQ

& ¢

gaf f

S!;H` [

g g U __£ :E __Dm __n_ES

1 ;

Q1| I

..v

2'E1 - ., ; .k r . . .

CA I

_ f

Efs2

Q n_E _EE. 2 mE___E_

VE

E E E: a s

'0<" " . . \Pi , nd Svuvoaanxg ;o .1313IHHN3 l.|f"L. ur" Jr 1 su: ,PLCL* ua Ka. .wmv-Id 11-1009!-a l #

I

g ;

55

gi v e n s i t e . Figure 7 -3 a lsoof exceedancesre su1t s a re qui te s i mi la r for both methods, as we

Section 5. 3. 1) . Another fe atur e of F1gure 7- 3 is

ye ar t o the ne xt

Hgur e 7- 4 Ulus tr a t e s t he e f f e c t s of t h i s v a r i a b .yi nat 1 onsmean e m i s s i o n r a t e s . The se d e te r m

c o m p l i a n t

us 1 n g a samp1e s i z e of 50 in order to reduce comput ing

es dar ned f r om s t andard Ex lx f a |̀1 \

60 percent f m ui t f nn x 5 percent

mean va1ue (8.65 YD 502/NMBt\A)_ T

` percent , respecLive1_y, for the 400

valupercent o f

of the average

compl 'iantun s c r u o b e d

va i u e s

f igures seem to indica te tha t the amountp u n tcompliant geometric mean vahees from one year to

v b e k e p tat P hi hde lph i a . However, i t shou1dLouis thanSrf iv e yea rs to e ach o the r a t

he iarger number of years ofare comparing only

meteoro1ogica1at Phi1ade1 pvua. Te1ph1a means that ther e i s a gr

1ues that dev ia te s1gn1fican1.l_yavai1ab\e at Phi1ac

.year s to exhibi t vad af1ve years

_v of v i ew ing tms is t o s ay t ha twa

e p r e s e n t a " s p e c i a l c a s e " o f s o r t s f o r u h u z h t h e

on s a r e m i n i m a l . S m o e t h i s m e t e o r o l o g i c a l r ec of c 15v a r i a t i1nter

a d d i t x o n , weent 1r e1 y e \1 m| na te th is Doss ib ih ty

the sa mphng error s ass oc iate d vnu* the res ul ts preheshown i n Table fm-1 due t o t?-4 are lar ger than tho se

used. Mt ho ugh the ef fe c t s1 a te d w i t h a n ;neverthe1ess and to the uncer ta inty(unbiased),

i n t e r p r e t a t i o n s o f t h e s e r e s u l t s

in t er e s t i ng f e at ur e o f F1gure If-4ageanetric mean vahaes derwed by the stochastic method

|"|llgE)I»L.\obtained by the standara method

c method 1n thi s case fo'\1o~4s 1

The gr ene r s t

valuesrngher NPOVr o ms t o c h a s t i

predic t ed by r n; s toc has t ic met hod (see F1gure

56

_

|

9

31

Mr

i n ' d \ 1H!

V ln

V11

1 /

/ /

_ : F

I"`l 1

L

c 1

1 1l i

U

¢ : C _ M J

I

E_ C_ 4 t

s4II

11L _ 1

.m f

Ba se

I

sSFEEL 7-4. C Dd"150r of cc C n e w E " " >

I i xE\gr! !C DF' S x 5 ' " ><u C ff a

\S( " ( Cw; n\U l

>I r 1

aa57

SUHMARV OF RESULTS. CONCLLSIDNS, AND Ri c a nMENDAT 1U?\\s

I

He h a ve un de r t a ke n an a n a l y s i s o f t h e te m p o r a l r e p r e s e n t a t i v e n e s s o f

s h o r t - t e r m m e t e o r o l o g i c a l d a t a s e t s us e d i n a i r q u a l i t y i mp a c t a s s e s s -

me n t s . As p a r t o f o u r a c t i v i t i e s we ha ve d e ve lo p e d a new te c h n i q u e ba s e d

up o n t h e r e p e a t e d ran dom s a mp l i n g o f a s h o r t - t e r m d a t a s e t as a means o*

g e n e r a t i n g ps e ud o lo n g - t e n m d a t a s e t s e x h i b i t i n g c h a r a c t e r i s t i c s s i m i l a r

t o th o s e f o u n d i n a c t u a l l o n g - t e r m m e t e o r o l o g i c a l d a t a r e c o r d s . I r

e x p l o r i n g t h e e f f e c t i v e n e s s o f t h i s " r e s a m p l i n g " te c h n i q u e we h a ve fo f as e d

o u r a t t e n t i o n on t h e S02 i m p a c t s a s s o c i a t e d w i t h i s o i a t e d c o a l - f i r e c

e l e c t r i c g e n e r a t i n g f a c i l i t i e s . The s n o r t - t e r m p r i m a r y an d se c o nd a r g

a mb i e n t s t a n d a r d s we r e c o n s i d e r e d . Bec au se c o a l - f i r e d power p l a n t s

e x h i b i t l a r g e v a r i a t i o n s i n e m i s s i o n r a t e s , du e i n p a r t t o th e va r y i n g

S u l f u r c o n t e n t o f t h e c o a l t h a t i s b u r n e d , we h a ve i n t e g r a t e d t h e r e s a n ,

l i n g te c h n i q u e i n t o th e p r e v i o u s l y d e ve lo p e d E x i x me t n o d . The r e s u l t , a

new p r o b a b i l i s t i c t e c h n i q u e t h a t t r e a t s b o t h e m i s s i o n s and d i s p e r s i o n

me te o r o l o g y a s s t o c h a s t i c ( r a n do m) q u a n t i t i e s i s kno wn as S t o c h a s t i c

£ x £ x . He h a ve p e r f o r me d c o mp a r i s o n s o f t h e p r e v i o u s l y d e v e l o p e d

{ " s t a n d a r d " ) £xEx me th o d w i t h t h e new s t o c h a s t i c [ x L x te c h n i q u e i n

a d d i t i o n t o a s s e s s i n g t h e a b i l i t y o f S t o c h a s t i c E x i x t o a d e c u a te l y a c c o u n t

f o r t h e lo n g - te mm v a r i a b i l i t y o f d i s p e r s i o n c o n d i t i o n s . The f o c u s o ' o f

e f f o r t s was t o a s s e s s wh e t h e r e m i s s i o n l i m i t s o b t a i n e d U§lW f i v e y e a r s c*

m e t e o r o l o g i c a l d a t a and p r o b a b i l i s t i c t e c h n i q u e s a r e r e p r e s e n t a t i v e o f t h e

e mi s s on l i m i t s o b t a i n e d w i t h a lo n g e r me t e o r o l o g i c a l r e c o r d , i n t h i s CBS;

II

I1?-years

a s m ? LnI58

SLMHAR~ U; R£ 5 uL 1 \8.1

A p ; - I ma t i o n o f Re s a m p l mg Te c h mq u e s t o

E 52 - :§@:n P1etgqro! 091 c al Da ta Set s8 . 1 1

OneTwo resar; lir \g techniques were aeve1oped f ur t h i s study I'mi 1s dE5ign€L1 to preserve the 5easonaT c_vc1es known toRea5ona1 sam;1

he L " e s e n t * n mar-_y meter1ro1<»u\c a1 va r i a b 1 e 5 ; t h i s i s a c h i e v e d by r e s t r 1 c t . -

: n g th e ran dom samg fwn a c t w w t y t o i n d 1 v i d u a \ se a so n s o f t h e b a s e

p e f i o d . Tne se c o nd me th o d {mun thTy samp11 ng) p r o wld e s . m e r te m p o r a i

r e s o l u t i o n by c d n s t r m n i n g th e ra nd r ln s a m p w n g t o i n d i v i d u a l mo n th s o f t h eI

Ad: !§ f p l

y a w: s e a s o n a l sc hemes we re a p p ' i e d t o o n e - , f i v eB o th t h e m

and s e . e n - y e a r s u b s e t s o f a 1? - y e a r me te o r o 1o g 1 c a 1 r e c o r d f r o m t h e

? ' 1 1 m e rma m e t r o n o h t a r a r e a . Mean and va r 1 a n c e s o f t h e f r e q u e n c i e s o f

o c c u r r e es o f s e v e r a l n n d s o f me 1 e o r o 1 e g i c a \ e v e n t s ( e . g . , st . a b i1 i t _ v A

C u ' | : i t 1 0 r S ) and c o n. 'c ~ na ti o" s o f m e t e o r u m g i c a l e v e n t s ( e . g . , o c c u r r e n c e (JT

t e s1sT.ent ur~1*eL e c o n v 1 t i 0 n s ' we re c a l c u l a t e d f r o m t h e 1 ? - y e a r r e c o r d .

mean and va ma n c é s o f th e o c c u r r e n c e s o f t h e(17-yeao r g - t ew e

€ \ P " i S a mi Ccrr1t". nat1on§. o f e v e n t s we re c o mp ar ed m t h th o s eF C v |

o b t a i r e d f r o m b o t h r e 5 a m ; | 1 1 " 5 s c h e m e s f o r t n e o n e - , f i v e - , a n d s e v e n - y e a r

Meteoro1og1ca1 events were 1dent1f1ec\ and defmed based uponSLE e r s

J u s q v n t s 6bouL t h P " 1 mp u " ta n c e 1n ! e a d 1 n g t o l a r g e i mp a c t 5 f r o m u s u la te c l

wnt s o m c e s HMV s t a n k s

uu xn u n th e samp11ng e r r o r s , no d 1 f f e r e n c e s i n th e Ob s e r ve d an d

c a u l a i e a f re q. 1e c i e s o f o c c u r r e n c e s f o r e | t h e r r e s a m p l i n g sc heme wa

n o te s ' o r aT1 e v e n t s ( e i t h e r i n d w v i o u a l o r i n c o mb 1 n a t i o n } an d a11 s u

5

b s e t s

uof the 17-year recvf a However, fo r e i t he r resamp|1ng aLnenw, u. . | e .¢ ". e ,in t he observed and ca ' ;u1ated frequenc1es were noted between comb1nat1ons

o f e v e '

e i t h e r

th e 1?

u n s t a b

t s an r i n a 1 v 1 d u a l e v e n t s . Th u s , f o r e x a m p le , r e s a m p l l n g ( u s i n g

sc h eme, f r o m a f 1 v e - y e a r s u b s e t p r o v i d e d c o mp ar ab 1e e s t i m a t e s o f

a- y e a r m e a n n u m b e r o f o c c u r r e n c e s p e r y e a r o f , s a y , p e r s i s t e n t "

e c o n H 1 t 1 ; " s , e . g . , two h o u r s o f A s t a b 1 l 1 t y c o n d 1 t i o n s o r f o u r

ho r s o f B s ta b 1 1 1 ty c o n d i t z o n s i n a 2 4 - h o u r p e r 1 o d . Resamp11ng f r o m a

9

B3D }?

59

p e r s u t e n to c c u r r e n c e s p g r _ye a rvariance 1n thereproducedresamplingCondi t 1 ons . Furthermore

o c c u r r e n c e s p e r y e a rmeanstab111t_y conaiuons)

d i f f e r e n c e s1Otc u r r e n c e s pe r y e a rthebetween the long-term variance

s i n o l e - h o u r

ns a mpi mg scheme. In a|1 cases Lne var1anc.e estimateden he r .v

of £ond\ t\0n5 foundfu| `ly reproduce the maeInfomation

9 r e s a mp h n g Scheme wh e r e i nc o n c e i v a b l e

r a t h e r tn a n f r o nth r o u g h o u t

greater variances 'in the occurrence of one-hour events . However s u c hi n

1c a1u n o e s x r a b l e

Sto c h a s z 1 c

t h em e t e o r o l o w

1 a t e odispersmn mode? to cn1cu1ate 24-hour average impacts assoc

b u r m g power p l a n twi t h a t y p i c n northeas iern 400 HH unscrubnen cod

s u b s e q u e n tre s u l t i ng no ma hze d d i s pe r s wn e s t ma t e s

s tochast ic Exix modeling

Compansons of results o f app1_yvng the two E xh t e c h m q u e s t o t h e

sets of nor~ma11ze: ! concentrat ions shuwed that e f fecuvel 1 d e n t1 a a

lc u la t e d by bo t h. Mt ho ugn qua i i t a t wee xc e e d a n c e r a t e s

c a k u l a t e d by t h e s t o c h a s u c Exim:that NPUV va\uesarguments

|

me th o d s h o u i d be g r e a t e r t h a n th o s e c a l c u l a t e d by t h e s t a n d a r d me t h o d , t h e

a c t u a l d i f f e r e n c e s

s i m i l a r c o mp a r i s o n

e s t i m a t e s o b t a i n e d

g r e a t e r t h a n th o s e

tu r n e d o u t t o be S ma l l f o r t h e Ph 1 1 ad e 1 ph i a s i t e . A

u s i n g S t . L o u i s metem-o1og_y sho wed t h a t t h e Npuv

f r a n th e s t o c h a s t r c ExEx me th o d we r e s u b s t a n t i a i i y

o b t a i n e d f r o m th e s t a n d a r d E x i x me th o d . S t o c h a s t i c

ExE= r e s u i t s f o ' b o t h th e mo n t h l y and s e a s o n a i r e s a m p i i n g sc hemes pr o d u c e d

n e a r i i d e n t i f a i Hr u v a~d e x p e c te d exc e e da n c e r a t e e s t i m a t e s .0

S t o r h a s t i c and S ta n d a r d £:r.Ex r e s u l t s f o r o n e - and f i v e - y e a r b a s e

p e r i o d s o f t h e Ph 1 1 ad e ? ph i a r e c o r d sho wed s u o s t a n t i a i v a r i a t i o n i n HEE and

Nf q v r e s u i t s f r o m one ba s e p e r i o d t o th e n e x t . Very f e w ( i e s s th a n 2U

pe f z er t o f t h e s e va l u e s we re u 1 t ' 1 ' n 1 20 p e r c e n t o f une vaTueS c a i c u l a t e d

'Di s t a n d a r d E x lx f o r t h e e n t i r e 1 5 - y e a r p e r i o d . V a r i a t i o n s f o r s t o c h a s t i c

|

as Targa as those for s tandard ExEx ILx we* 1LJ'>

A < " g r t y d i f f e r e n t b e h a vi o r was o b s e r ve d i n th e c a se o f maxi mum

e x ; e ; t e d h= g h e s t and ma .mum e x p e c t e d s e c o n d - h i g h e s t c o n c e n t r a t i o n s . For

b o t h o n e - an d f i v e - y e a r ba s e p e r i o d s o f t h e P n i i a d e l p h i a r e c o r d , a i l o f

t h e s e c o n c e n t r a t i o r s f e i i w1 th 1 n 1 90 p e r c e n t o f t h e l o n g - t e r m r e s u i t s .

Ho we ve r , doe t o th e man ner i n wh i c h e m i s s i o n l i m i t s may be d e te r m i n e d f r o m

s o c r m a = i w ~ e x p e c t e d Nth n i g h e s t c o n c e n t r a t i o n s , i t may w e l l be t h a t

er s= on 1 i n L5 ba se d on th e s e c o n c e n t r a t i o n s a r e no mo re s t a b l e th a n

I

I 'E$u I SOF MUP Nw Da;

Lalcu\aL1omsum J n: u l iL asseSS t h e wmpac ts o f t h e a b o ve - me n t1 o n e d va r 1 a b 1 l 1 t 1 e s i n E x i x

f e s , t a on th e r e g u f a to r p r o c e s s , e m1 s s i o n E i m i t d e t e r m 1 n a t1 o n s ( b a s e d on

an a5~Jmed c f x t e r i a o f a1 1o w1 ng no mo r e th a n a 10 p e r c e n t NPUV) we r e made

u s i " g b o t h th e s t a n d a r d an d s t o c h a s t i c ExEx me th o d s . The g e o m e t r i c m e a n

L o a l s o 1 f o r c o n t e " t wh i c h me e ts t h e 1 0 p e r c e n t HPUU c 1 L e r 1 a was us e d a s a

s1mp1e s ' " o g a t e f o r an a c t u a l e m1 s s i o r l i m i t .

|

e o m e t r i c mean c o a i s u i f u r c o n t e n t sA omoa r1 so n o f comp 1 a n t g

s t o c h a s t i c E x i x me th o d s on o n e - an nd e te r m' " e C us1 ng b o t h th e s t a n d a r d and

f 1 v e - y e a r s u b s e ts o f t h e Ph1 1ad e1p h1n d a t a s e t sho wed l e s s va r 1 a L i o n f r o m

c 1C5

61

c o mp a r i s o n

cons is tent our genera l experience

parameters governing ( e . g. , geometric mean, concentrat I o n

def1n1t.1ov\ s i ng ie a ddi t io na l exceedance occurr ing at any one of a0

s uf f i c i e nt C a u s e a

rec1ass if ied as be|n9 in v i o la t i o n. Thus, even minoryearc o n c e n t r a tmo n

s a t u r a t i o n " e f f e c t ml ! when operatmg c lose

a f f e c t e d much by f u r t h e r d e c r e a s e s

Fo r t h i s r e a s o n , we h a ve cle11berate1y choosen to explore the sens1t1v1t

regu\atory

r e s u 1 t se x p e c t 51gni f icant1

Péfnentj wouid q u a n t i t a t i v e

A Summar_y of the compar1son between comp!

found i n Table 6-2. These resu1ts inchc ate that lim1t deterr11nat1ons based on five-year base periods have a f a1r¥_y probabi11tybe ing wi th in 5 per cent o f a represe ntatwe 1H r m t s d e t e r m i n a t i o n s

s t ab1} i t v

As a wa y of t es t i ng t he robustness of the r es ult s discussed

Exix modeling and compliant geometr ic I s u l f ur d e te r m1 n a

tions were performed fo r t he fo11o\-ring s i tuat io ns

3_h0nf averagr con<entrat1on5

utmbes, c o a l - f " e d power p l a

JEDPG ;¢0uEr p ` a n t u51f1; f w e y e a r s o f

< meteufo loJ I

* o " § f o r ea c h o f th e s e s c e n a r i o s we r e n e c e s s a r 1 \ y o f a

th e F€ S L ` I $ we re g e n e r a l 1 y c o n s ~ s te n t w i t h th o s e d e s c r 1 b e d

calcu'w

1|".T.€C f a i

UL;\;v\t|ng the; cvf clus D \ reacnel* 0" the bas1s of 1;n1s HOV!/¥\

s ' t E S , a» = r a g f ; L1me5, ana po we rrv wt Tw E\»'" ' P d 1

a: VI f w i f w f 'a LLJaL1;:";,n.a".:"\ of f* s re s ul t1

2 TEN ATI \'E CONLLUSIUN

me d vw, we C1"aw UI: f o l lmvJ IJp|1 t"E f cSuT »

tentatwe c onduswons I

Th e 1s no v g m f 1 .=1nL d w f f e f e n n e be twe e n r e s u l t s o b ta me c i f r o m

th e f n t h l y M d soa =. ~~ 5arw,}1rm, sc h er r ea.

u r

resanpl P; tv=.nr11que. when ap;He s to data subsets f ive<22 ET¢=,»n~5 i n Ie nqtn, provae> comparable e§t1mates of the mean anc

v i r i a ncr o f ine nurbe r u f orccrfenrea per year 01 comb1=¢r1uns

of mefeurolog1ca1 evewzs oo>ervec in the lo ng- te r m (17-year)

Fei v f d. These combinat ions of events are he lreved to produce

I

|

. . .__ __ . _ \ . . . Sr e a t w i c ¢' ; L» la1 .eu £ 4 - n o f a ve r a g e 1mpa<.\.b 101 puwe: p l a l l u

1 i a 1 s t m m aes o<1..¢r a t an o b s e r v e d f r e q u e n c y o f a p p r e n -H 1

I f . a 1 . e , on _e pe r ye.- sf . Eur o n e - h o u r m e t e o r u l o g m a l e v e n t s a u t h

mean a n n u a l f r e q u e r u e s o ' o c c u r r e n c e muc n g r e a t e r t h a n o n e ,

n e 1 th e r r e s a r r p l i n g t e c h m q u e , when a p p h e u t o d a t a s e t s f r o m on e

t o sea en yEa ;. i n l e n t h , r e p r o d u e s th e va r 1 a n c e f o u n d i n t h e

| B3 D i } 1.6 3

underes t ilong- term rec ord; in a11 cases the

c o n c l u s i o n sna Led ; .Y

(Phi ladelphiacw le c te a

dependency

te c h n wq u e s(3) t h e s t o c h a s t i c1effectiv e1y 1ndenr1ca\ expected exceedance

conc ius ion a p p e a r

D a f f e r e n c e s

stochast tc

(P hi ladewhie )Compn rab1e

(Sm s t o c h a s t i c

var1ab1]1tyre1at1ve1.y high degreemeteoro logica l

regu1atoryindicat1ng

of d1spers1on data Conta1ns mgledec is ions

uncer ta1nty. ?h1 t o be t r u emgnStandard and stochastmc ExtTculat ions

s t o c h a s u c Ex1 t h e sta n ds r dmeteorologica

based f i v e - y e a r d a ta s e t sregu1a1.or_y

much Inner degr ee o f uncer ta in ty . Indeed, such fwe

r e p r e s e n t a t i v e o f t h o s e

Pni\ade1pni a)(forso!el_y lc uh tion s

k n o wl e d g e o f t h e d e g r e e t o w h i c h i tthere fore

I( c f . conc1us'ion

7

3 R§~l0HHENf»5T

Nlthough we behave the res ult s a nd co nc lusmns presented above

r e p r e s e n t an ad va n c e men t i n ou r c u r r e n t u n d e r s t a n d i n g o f t h e e f f e c t s

aT van-1at>111t_y has on the makmg of reguiat ory dec is io ns , theymeteo rol o n;

r . mu s t be c o n s i d e r e d t e n t a t i v e ; muc h work r e ma i n s t o be d o n e . Our f i n d i n g s

and t e n t a t i v e c c m d u s i o n s a r e ve r y s u g g e s t i v e and c a n be us e d t o g u i d e t h e

d i r e c t i o n o f fuI.I.H"£' a c t i v i t i e s . S p e c 1 f 1 r a 1 \ y , we wo u ld l i k e n o make t h eI

oi Ou "| fe onmendations I

e V a ' a r w m8 . 3 . 1 §~ e

51 tn e H w t e u sc mwe o f o n a n ; t w 1 t 1 e s and t h e a v a 1 l a b i 1 1 t \ ,B e l a u (

o n sof a 1 -_year metec0?:>g1ca1 data rer or d, most 01 tne ca hc ulau

descrmbed 1n 1*\1s repor t were made for one s i t e (PPi1ade1pn1a} TheI

t e mu s t be v1 eu ed m t h\1 mt ec r.a1L.1at1ons performed fo r t he St. Louis 51

some c.aut1on f1r the reasons dmscussed in Chapter 7 [1Jv|ousl_y, me

tra ns fe ra bw li lg of CSf1rh,§o"> from one s ' Le t o t he next is an 1n1portant

r s s a and we rerommend Una: add1t1ona1 ca!cu1aT.1;1ns [ ' i . e . , Cover1ng a

Io, , . c a ` r e c o f d ) be c .a r r1 ed o u t a t a number o f s i t e s r e p r eL N : e r m v i e l

t h e f u l l r a n g e o f c h m a t o l o g m c a l r e g r n e s . I n a c l m t i o n , a b r o a d eS9"'

an us o f po u e r p i a n t . §OurC¢ c h e f " . : t e r ' s t 1 c s an d t e r r a i n c o n f i g u r a t i o n s

gnc-u1d me re ; ' e 5 -= - : t e d ' i n f u l . " e r . a I ; \ . Ta t a 1 s .I

Qjrgsures of \ar1a:|11L_I

n me present reL:>"* we have fO(L.SEG on tnr e e d i f f e re nt {alt.hougn

re la te d) sets o f cr1te '1a for de t e r n " i n g t he sui tao111cy of resamp1ing

technwlues 1n the s1mo1at1on of iong-term meteoro1og1ca1 var1abi }zLy .

rus t d1rect method 1nvO'V&u che frequenc ies of occurrence of s ingle and

mot1-hocr meteoro1og1ca1 events . The next step in t n i s h i e r a rc hy o f

; r \ : e ' 1 a was an analys=' of var iabi11ty in dispersion mode] resu1ts (or

The

r the case of a var1abTe emussion rate source). F i n a i l y , wex r

~.I65

}

I

Q examned the ef fec ts o f |\e teoro1og1ca1 va ri ab i l i ty o n e mi ss io n m m s

which are set on the basis o f made1 (Ex£x) r~esu\ts.

.1

0bv1ous1y, the choice of whi ch of the a bove three se ts o f c r 1t e r i a l

a r e t o be us e d de p en d s up on t h e p a r t i c u l a r a p p 1 1 c a t i o n e n v i s i o n e d . For

exa rnp 1e, f r o m t h e m e t e o r o 1 o g i s t ' s v i e u p o m t , one may n o t b e i n t e r e s t e d 1r.

any one p a r t i c u l a r t y p e o f d i s p e r s n n modeT b u t r a t h e r i n t h e a b 1 1 1 ty o f

t h e r e s a mp 1 i n g me th o d t o r e p r o d u c e c e r t a i n u r e t e o r o m g i c a i e v e n t s . On t h e

o t h e r h a n d , f r o m t h e a i r qu a 1 1 t_ v ma n a g e r ' s v i e w p o i n t , t h e e f f e c t s o f

| n e te o r d ' l o g i c a 1 v a r i a b i l i t y on e m i s s i o n ' l i m i t s may b e o f p r i m a r y

Q

I

He belie ve t here is mer i t in e xp lo r i ng fur t her t he re1at1onsn;9 interesti t y o f resamplw Ib e twe e n th e s e an d o t h e r me th o d s o f a s s e s s i n g t h e s u i t a b

te c h n i q u e s . I f a r e s a mc i i n g te c h n i q u e we re f o u n d wh i c h a c c u r a t e i y

a c c o u n ts f o r t h e l o n g - t e r m v a r i a b i i i t y i n c o m p l i a n t e m i s s i o n r a t e s b u t

d o e s n o t a c c u r a t e i y r e p r o d u c e f r e q u e n c y d i s t r i b u t i o n s o f c e r t a i n me te o r o -

i o g z c a i e v e n t s , t h e n ju d g e me n ts a b o u t i t s s u i t a b i l i t y v i i i de p en d h e a v i l y

on th e p a r t i c u i a r c r i t e r i a e mp i o y e d . A l t h o u g h t h i s i s a p u r e l y h y p o -

t h e t i c a i c i r c u m s t a n c e , i t s e r ve s t o p o i n t o u t t h e imp or t an c e o f t h e c h o i c e

o f c r i t e r i a and t h e u n d e r s ta n d i n g o f t h e i m p l i c a t i o n s o f su c h a c h o i c e .

J

Sammi ing Errors3

In the pr ese nt report we have pres ent ed t he results of smne li rni teo

empir ica i determinations of the s amphng er rors assoc iated wi th Exlx (botr.

standard and stochast ic ) model r e s ul t s . These samp 1ng errors r e f le c t the

v a r i a b i l i t y i n f.I.Ex results which ar e t o be e xpe cte d due to the f i n i t e

sample s ize (number of sample»years) employed. Th1s 1s an 1m"or tant toptc

because tne sample size cannot be increased a r b i t r a r 1 ly (the pena lty ln

requi red comput ing resources can become suostant1al} and the s1ze of t he

sa mpl ing e rr o r c an be c r i t i ca l unen inter-comparing £x£x re sult s { e . g. ,

fo r d i f f e r e nt ba se pe r io ds ) . He recommend that addi t ional emp1r1cal

determina t ions of sampl ing err or be car r i ed o ut for a varie ty o f base

period le ngths , averaging t imes, source emiss1on rate d1str1but1ons and

0

s o u r c e Ioc at 1 ons

8 3 0 1 7 u66

I

.

3.4 `Peoret1La' Eé L

hUu: h we ms t 5 t r a g ' 1 t foruarc l\¢T.'10G of detemining §a|11p11ngA

r e p e a t th e h h c a l m ; a t <;m5 u w * 9 a Ya rg e number oEV N

ndep:2"de*t svts of rancof nuvmefs, U12 method involves a large number of

1 c e i c u i a t a o w s wh i c h m e s ; be r e p e a t e d f o r e a c h c a s e o f i n t e r e s t ( e . g

lv r r a g i ng t une , Ie r qt h o f ba s e pe f wd, e t c . 2 . At temgzs to c a lcu la te

sar':J1ir=;. err or s |nay t i ca 11 y ar e mnae re a by vio1at ions of the necessary

e lssurrat1-:VIS fHi I1.yer |nC B\.'"1.nn, 1953). I-Iourever, 11. should

: . = o hta " th¢ r~e : i c a r~o§|.1ts f ar r .Prt . l1n s impli f ied casesi v

\

f

1 r\ W e n e c e s s a r y a s s u mp t i o n s h o l d .

l. B1 | L ' "S , a h n o u g h n o t a n - e a u ; a p ? 1e . q . , a 5ing1e *f*;E'11<" fnr vu

e s u i t s ' s. . : h 1 m = r f f :t o Ln e s o r t s o f C'e1=lems G= 5c . s' . n d 1 ' t h i s r e p o r t , \ | 0 u`d n e ve r t n e 1 e s s b e

o f va ' I ue 1n 1 n c " e a s a n g o u r u n u e r s ta n d i n g o f t h e c o n t f c d l i n g i n n u e n c e s o n

e l" 3 ' ; + o ' v m p i u n g »=" ' r ur5. we twe e f u r e b e h a v e t h a t anang 9

.r §5r * §" | nQ P " L : " * ¢ " J Ud be ac c o mpa n ie d by SU IP J e i n r 1 f . f ~

| `*§ *'Y| c iI 1\ r : '

»1»;:11L1cf1.:1 topmcs w+1:LF|. coma hp exammed from a theoret1;a3 view

ea by s t a n d a r d an dm t i r c .=r1e th e : o f 1 ; a ' ' f , J n o f I&='3v r e s l t s a s c omp u t

0: suchwe F w 3 " ' e ' e m rE5\fstoche 115 [1 x. wer1ef=' have ber" u m a " P : ar turf : d i f ferent s1tes (S t . Lou|$ anQ C

Ithv pres.- 'mt t ime, we car n='i_y sper.u`|ate on the ex;Eana

dr-;waency . A ' tHe: :'et 'La1 |na y s 1 s o f Lhfs que s tmn,JP M

t m ' ' _ H115 51

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