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# OAR Box 1126 Prepped byOllie Stewart



## Document

Number: 

# 169)11-1-382 Docket Number: 

# A-83-2 2

Printed 4/18/2008 9:58:29 AM

Sheet 169 of 182P. 2p. ;



### Fina l Repor t A NEXAMINATIO NO F AI R QUALIT Y DAT ACOMPLETENES S REQUIREMENT S

SYSAPP-84/07 6 . 2 9 May198 4

Prepare d fo r Monitorin g and Report s Branc h Offic e o f Ai r Qualit yPlannin g and Standard s U.S . Environmenta l Protectio nAgenc y Researc hTriangl e Park , N C 2771 1

Prepare d b

y A . D . Thral l J . L . Baptist a C . S . Burto n System s Applications , Inc , 10 1 Luca s Valle yRoa d Sa nRafael , C A9490 3

6830 6 e f 831t6 rP. 4 

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DISCLAIME R 

## O Thi s repor t ha s bee nreviewe db y the Offic e o f Ai r Qualit y Plannin g andStandards , U.S . Environmenta l Protectio nAgency , an dapprove dfo r publication . Approva l doe s no t signif y tha t th e content s necessaril y Qreflec t th e view s an dpolicie s o f th e U.S . Environmenta l Protectio n Agency , no r doe s mentio no f trad e name s o r commercia l product s constitut e endorsemen t o r recommendatio nfo r use .


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### ACKNOWLEDGMENT S

Th e author s ar e gratefu l t o Scot t Chapli nfo r hi s researc ho ncurren t dat a completenes s criteri a andt o Mik e Harper , Bell e Hudischewskyj , an dGary Lundber gfo r assistanc e incomputing . Th e author s als o than kBil l Hunt , Nei l Frank , an

dTom Curra no f th e U.S . Environmenta l Protectio nAgenc y fo r thei r thoughtfu l comments .

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CONTENT S



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O Acknow l edgment s ii i

Lis t o f Illustration s . , v i Lis t o f Table s x Notatio n xii i

1 INTRODUCTIO N1

Backgroun d 1 Methodolog yand Organizatio n o f Result s 3 2 STATISTICA L PROCEDURE S FO R DETERMININ G TH E AI R QUALIT YSTATU S O F ASIT E 6 Annua l o r Quarterl y(Long-Term ) Average s 6 Short-Ter mConcentrations . 1 0 Th e Observe d Numbe r o f Short-Ter mExceedance s 1 0 Th e Estimate d Numbe r o f Short-Ter mExceedance s 1 5 Curren t Practic e i n Determinin g th e Short-Ter m Attainmen t Statu s o f a Sit e 1 9 Limitin g th e Maximu mProbabilit yo f Typ e I Erro r 1 9 Summar yo f Result s and Alternativ e Approache s 2 7 3 EMPIRICA L ESTIMATIO NO F TH E PROBABILIT YO F MISCLASSIFYIN GATTAINMEN T STATU S 3 1 Long-Ter mAmbien t Standard s 3 1 Short-Ter mAmbien t Standard s 4 3

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# o STATISTICA L ESTIMATIO

NO F TH E STATU S AN

D TREND S I

NNATIONA

L AI R QUALIT

Y

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L ASSESSMEN

T O F TH E DAT

ACOMPLETENES S NEEDE D TO RELIABLY ESTIMAT E NATIONA L TRENDS. . Sulfu rDioxide
. Carbo n Monoxid e Nitroge n Dioxi d

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Appendi xASULFU

R DIOXID E DESCRIPTIV E STATISTIC S Appendi xB CARBO

NMONOXID E DESCRIPTIV E STATISTIC S Appendi xC NITROGE NDIOXID E DESCRIPTIV E STATISTIC S Appendi xD OZON

E DESCRIPTIV

E STATISTIC S Appendi xE LEA

D DESCRIPTIV

E STATISTIC S Appendi xF PARTICULAT E MATTE R DESCRIPTIV E STATISTIC S Appendi xGSUMMAR

Y O F CURREN

T DAT ACOMPLETENES S CRITERI A 5 5 5 5 5 6
5 8 5 8 5 8 6 5 6 5 7 2 7 2 7 2 8 0



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## o ILLUSTRATION S O 2- 1 Binomia l approximatio n t o a an d 3 i n th e one-exceedanc e case , r= l 2 1 Q 2- 2 Binomia l approximatio n t o a an d 3 i n th e three-exceedanc e case , r = 3 2 3 2- 3 Binomia l approximatio n t o a an d 3 fo r r = 1 an

d a specificatio n o f CX

Q = 0. 2 2 6

u2- 4 Binomia l approximatio n t o a an d 3 fo r r = 3 an

d a specificatio n o f a g = 0. 2 2 8 3- 1 Lead : the probabilityo f misjudging actua l attainmen t statu s a s determine d b

yth e mean , th e coefficien t o f variation , O an d the proportion o f dat a completenes s 3 6 3- 2 TSP , annua l geometri c mean : th e probabilit yo f misjudging actua l attainmen t statu s a s determine d b yth e natura l log o f the geometri c mean , th e coefficien t o f variation , an d O the proportion o f dat a completenes s 3 7

3- 3 TSP , annua l arithmeti c mean : th e probabilit yo f misjudging actua l attainmen t statu s a s determine d b yth e mean , th e coefficien t o f variation , an d th e proportio n o f dat a

_ . COffl U i ClCllcb b oooooooooooooooooooooooooooooooooooooooooooooooo o O O AA 3- 4 Estimate d probabilitie s a an d 3 o f misjudging attainmen t o f th e 24-hour sulfur dioxid e standard a s function s o f th e proport i on o f dat a comp l etenes s 4 6

AA O 3- 5 Estimated probabilitie s a an d 3 o f misjudging attainmen t o f th e one-hour carbon monoxid e standard a s function s o f the proportion o f dat a completeness.. . 4 7
AA 3- 6 Estimate d probabilitie s a an d 3 o fmisjudgin g th e 8-hou r O carbo n monoxid e standar d a s function s o fth e proportio n o f GuU u COITi p 1 GLGUGS S ooooooooooooooooooooooooooooooooooooooooooo o H O 83m6 r1 v i OP. 9 O

3- 7 Estimate d probabilitie s a an d 3 o fmisjudgin g attainmen t O o fth e maximu m dail yone-hou rozon e standar d as function s o fth e proportio n o fdat a completenes s 4 9
AA 3- 8 Estimate d probabilitie s a an d 3 o fmisjudgin g attainmen t o fth e 24-hou rTSP standar d as function s o fth e proportio n \^S O TQdl u COITi p I CtCllCb b oooooooooooooeoooooooooooooooooooooooooo o *) U

5- 1 Estimate d long-ter m sulfu rdioxid e ai rqualit yparameter s as function s o fth e require d dat a completeness.
. 6 0 Q 5- 2 Estimate d short-ter m sulfu rdioxid e ai rqualit yparameter s as function s o fth e require d dat a completenes s 6 2 5- 3 Estimate d one-hou rcarbo n monoxid e ai rqualit yparameter s as function s o fth e require d dat a completenes s 6 4 

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O 5- 4 Estimated 8-hou r carbon monoxid e ai r qualit yparameter s a s function s o f the required dat a completenes s 6 7 5- 5 Estimate d long-ter mnitroge n dioxid e ai r qualit yparameter s a s function s o f the required dat a completenes s 6 9 5- 6 Estimate d annua l ozon e ai r qualit yparameter s a s function s o f th e required dat a completenes s 7 1 5- 7 Estimate d long-ter mlea d ai r qualityparameter s a s function s O o f the required dat a completenes s 7 4

5- 8 Estimate d long-ter mTS P ai r qualit yparameter s a s function s o f the required dat a completeness. . 7 6 5- 9 Estimate d short-ter mTS P ai r qualit yparameter s a s function s o f th e required dat a completenes s 7 8 Appendi xA : Sulfur Dioxid e A- l Histogra

mo f th e percentag e o f dat a completenes s fo r O site s reportin g sulfur dioxid e concentration s in 198 1 A- 2 Scatte r plot s o f ambien t ai r qualit ystatistic s versu s th e percentag e o f tota l hour s recorded in 198 1 b ysite s reportin

g sulfur dioxid e concentration s A- 3 Histogra

mo f expected primar yexceedance s fo r site s reporting 24-hour sulfur dioxid e concentration s in 198 1

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A- 4 Scatte rplo to fexpecte d primaryexceedance s versu s th e

percentag e o ftota l day s recorde d i n 198 1 b ysite s O reportin g 24-hou rsulfu rdioxid e concentration s



## Appendi xB : Carbo nMonoxid e B- l Histogra m

o f th e percentag e o f dat a completenes s fo r O site s reportin g carbo nmonoxid e concentration s i n 198 1

B- 2 Histogra mo f expecte dprimar yexceedance s fo r site s reportin g one-hou r carbo nmonoxid e concentration s i n 198 1 Q B- 3 Scatte r plo t o f th e numbe r o f expecte dprimar yexceedance s

versu s th e percentag e o f tota l hour s recorde di n 198 1 b y site s reportin g one-hou r carbo nmonoxid e concentration s
O B- 4 Histogra mo f expecte dprimar yexceedance s fo r site s

reportin g 8-hou r carbo nmonoxid e concentration s i n 198 1 B- 5 Scatte r plo t o f th e numbe r o f expecte dprimar yexceedance s versu s th e percentag e o f tota l hour s recorde di n198 1 b y site s reportin g 8-hou r carbo nmonoxid e concentration s O Appendi xC : Nitroge nDioxid e

C- 1 Histogra mo f th e percentag e o f dat a completenes s fo r site s reportin g nitroge ndioxid e concentration s i n 198 1 Q C- 2 Scatte r plot s o f ambien t ai r qualit ystatistic s versu s th e

percentag e o f tota l hour s recorde di n198 1 b ysite s reportin g nitroge ndioxid e concentration s i n 198 1
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O Appendi xD : Ozon e

D- 1 Histogra mo f th e percentag e o f dat a completenes s fo r site s reportin g ozon e concentration s i n 198 1 D- 2 Histogra mo f th e numbe r o f expecte dprimar yexceedance s fo r site s reportin g ozon e concentration s i n 198 1 D- 3 Scatte r plo t o f th e numbe r o f expecte dprimar yexceedance s versu s th e percentag e o f dat a completenes s fo r site s reportin g ozon e concentration s i n198 1

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### Appendi xE : Lea d E- 1 Histogra m

o f th e percentag e o f dat a completenes s fo r site s reportin g lea d concentration s i n198 1 E- 2 Scatte r plot s o f ambien t ai r qualit ystatistic s versu s th e percentag e o f dat a completenes s fo r site s reportin g lea d concentration s i n198 1 Appendi xF : Tota l Suspende d Particulat e F- 1 Histogra mo f th e percentag e o f dat a completenes s fo r site s reportin g TS P concentration s i n198 1 F- 2 Scatte r plot s o f ambien t ai r qualit ystatistic s versu s th e percentag e o f dat a completenes s fo r site s reportin g TS P concentration s i n198 1 F- 3 Histogra mo f th e numbe r o f expecte d primar yexceedance s fo r site s reportin g TS P concentration s i n198 1 F- 4 Scatte r plo t o f th e numbe r o f expecte d primar yexceedance s versu s th e percentag e o f dat a completenes s fo r site s reportin g TS P concentration s i n198 1

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o 2- 1 Th e require d proportio no f dat a completenes s a s a functio n o f th e tota l numbe r o f possibl e measurements , th e coefficien t o f variation , and th e prescribe d maximumrelativ e erro r occurrin g wit h9 5 percen t probabilit y8 2- 2 Relativ e erro r fo r dat a completenes s proportion s p ^ = 0.5 0 and P i = 0.7 5 9 2- 3 Th e proportio no f dat a completenes s require d t o limi t th e ris k t o 3 o f no t detectin g r + 1 exceedance s 1 4 2- 4 Th e maximumprobabilit yo f a Typ e I erro r and th e binomia l approximatio nt o th e probability , a s function s o f th e pro portio no f dat a completeness... . 1 8 2- 5 Binomia l approximation s t o probabilitie s a and 3 i n th e

O i l G ""GXCGGQ O MC C vQbt . ) P " ~ Xoo000000«09000000000000«000*0««*>00 0 C U 

### 2- 6 Binomia l approximation s t o probabilitie s a an d 3 i n th e three-exceedanc e case , r = 3 . 2 2 2- 7 Attainmen t statu s a s a functio no f observe d exceedance s and th e proportio no f dat a completenes s 2 5 2- 8 Attainmen t statu s fo r th e one-exceedanc e formo f th e

SX » a MQc i l U\ \ *"* " iyooooo«©o»oooooo©ooo*oo©ooo©ooooooo»>oooooos»s»o o CO 3- 1 Estimate d probabilit ytha ta site' s attainmen tstatu s fo r long-ter m standard s i s misclassifie d a s a functio n o f minimu m dat a completenes s proportio n 34 3- 2 Estimate d probabilit ytha ta site' s attainmen tstatu s fo r short-ter m standard s i s misclassifie d as a functio n o f minimu m dat a completenes s proportion...
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5- 7 Estimate d composit e annua l averag e o f one-hou r sulfu r dioxid e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a comp l etenes s Estimate d mea nannua l rat e o f 24-hou r sulfu r dioxid e exceedanc e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a completenes s Estimate d mea nannua l rat e o f one-hou r carbo nmonoxid e exceedanc e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a completenes s Estimate d mea nannua l rat e o f 8-hou r carbo nmonoxid e exceedanc e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a completenes s Estimate d composit e annua l averag e o f one-hou r nitroge n dioxid e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a completenes s Estimate d mea nannua l rat e o f maximumdail yone-hou r ozon e exceedanc e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a completenes s Estimate d composit e averag e o f maximu mquarterl ylea d and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a completenes s 

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5- 9 Estimate d composit e averag e o f 24-hou r TS P and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a
COIli p I GUGllG j J OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO i 

### Estimate d mea nannua l rat e o f 24-hou r TS P exceedanc e and it s estimate d varianc e a s function s o f th e require d percentag e o f dat a comp l etenes s 75

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O Appendi xA : Sulfu rDioxid e

A- l
A- 2 Numbe ro fsite s recordin g one-hou rsulfu rdioxid e durin g a t leas t7 5 percen to fth e tota l possibl e hour s i n 198 1 Numbe ro fsite s recordin g one-hou rsulfu rdioxid e durin g a t leas t5 0 percen to fth e tota l possibl e hour s i n 198 1

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A- 3 Frequenc ytabl e o f th e percentag e o f tota l day s recorde d i n

198 1 versu s expecte d primar yexceedance s fo r site s reportin g ^ 24-hou r sulfu r dioxid e average s

Appendi xB : Carbo nMonoxid e B- l Numbe r o f site s recordin g carbo nmonoxid e durin g a t leas t O 7 5 percen t o f th e tota l possibl e hour s i n 198 1

B- 2 Numbe r o f site s recordin g carbo nmonoxid e durin g a t leas t 5 0 percen t o f th e tota l possibl e hour s i n 198 1 O B- 3 Frequenc ytabl e o f th e percentag e o f tota l day s recorde d i n 198 1 versu s expecte d primar yexceedance s fo r site s reportin g one-hou r carbo nmonoxid e average s


## O B- 4 Frequenc ytabl e o f th e percentag e o f dat a completenes s i n 198 1 versu s expecte d primar yexceedance s fo r site s reportin g 8-hou r carbo nmonoxid e average s Appendi xD : Ozon e D- 1 Frequenc ytabl e o f th e percentag e o f dat a completenes s i n 0 198 1 versu s expecte d primar yexceedance s fo r site s reportin g

maximu mdail yozon e concentration s Appendi xF : Tota l Suspende d Particulat e O F- 1 Numbe r o f site s recordin g 24-hou r TS P durin g a t leas t 7 5 percen t o f th e schedule d monitorin g day s i n 198 1 F- 2 Numbe r o f site s recordin g 24-hou r TS P durin g a t leas t 5 0 percen t o f th e schedule d monitorin g day s i n 198 1 F- 3 Frequenc ytabl e o f th e percentag e o f tota l day s recorde d i n 198 1 versu s expecte d primar yexceedance s fo r site s reportin g 24-hou r TS P average s O

O Appendi xG : Curren tDat a Completenes s Criteri a

G- l Nationa l Aerometri cDat a Bank' s criteri a fo rvalidit y o fdat a G- 2 Californi a Ai rResource s Board' s criteri a fo rrepresenta O tivenes s o fai rqualit ymeasurement s an d statistic s

G- 3 Indian a Ai rPollutio n Contro l Division' s criteri a fo r completenes s o fdat a
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### NOTATIO N ft Fixe do r controlle dparameter s N = numbe r o f possibl e measurement s ina yea r P Q= require ddat a completenes s proportio no r percentag e e = specifie dtoleranc e fo r estimatin ga site-specifi c long-term averag e concentratio n

' • r = th e maximu m numbe r o f time s short-term concentration s at a sit e ma y excee da referenc e concentratio nwithou t violatin g a give nshort-term

ai r qualit y

standar d a = probabilit y

tha t th e attainmen t statu s o f a sit e wil l b e > incorrectl y determine da s nonattainmen t 3 = probabilit y

tha t a site' s failur e t o attai na nai r qualit y standar dwil l g o undetecte d ASite-specifi c quantitie s ( i = sit e index ) p n 

### - = proportio no f possibl e measurement s actuall y recorde ddurin g the yea r

A 

### Ui = averag e o f th e p^ N concentration s recorde ddurin gth e yea r
^ i = averag e o f al l N

concentration s tha t coul dhave bee n recorde ddurin gth e yea r o . = standar ddeviatio no f th e p^ N concentration s recorde ddurin g • th e yea r O i = standar ddeviatio no f al l N concentration s tha t coul dhav e bee nrecorde ddurin gth e yea r 0 , k i = th e numbe r o f time s a sit e i s reporte dt o have exceede da short-term

referenc e concentratio n
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### X . = th e estimate dnumbe r o f short-term exceedance s A . = th e actua l numbe r o f short-term exceedance s (equa l t o k i whe nPi = 1 ) Sampl e an

dpopulatio nquantitie s /J r = se t o f indice s i o f site s comprisin gth e sampl e V(PQ ) = numbe r o f siite s inth e sampl e whos e dat a completenes s proportio nequal s o r exceed s p g

AA 

### U(PQ ) = sampl e averag e o f P i acros s site s wit hp . > p Q 

### P(PQ ) = populatio nmea no f p i acros s site s wit hp . > P Q P = populatio nmea no f p i "2 "2 

### a (p n 

### ) = sampl e averag e o f varianc e estimate s o* acros s site s wit hp . >

p Q 

### 2 2 a (p Q 

### ) = populatio nmea no f variance s O i acros s site s wit hp . * » p ^ 2 2 a = populatio nmea no f variance s a^ AA 

### x(p Q 

### ) = sampl e averag e o f estimate dsite-specifi c exceedance s (A.. )

fo r thos e site s wit hp . > p Q 

### A(P 0 

### ) = populatio nmea no f site-specifi c exceedance s (Ai ) fo r thos e

site s wit hp . >

p Q 

### A = populatio nmea no f site-specifi c exceedance s

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EXECUTIV E SUMMAR Y

PURPOS E AND SCOP E O F TH E STUD Y
Th e U.S . Environmenta l Protectio n Agenc y(EPA ) store s ambien t ai r qualit y data , obtaine d fro ma nationwid e networ k o f monitorin g stations , i n th e Nationa l Aerometri c Dat a Ban k (NADB) . Statistic s summarizin g th e ai r qualit ya t eac hmonitorin g statio n ar e als o store d i n th e NADB . Thes e summar ystatistic s ar e mad e availabl e t o th e government-an d publi c provide d tha t certai n dat a validit ycriteri a ar e met , chie f amon g thes e bein g requirement s fo r dat a completenes s (give n i n Appendi xG) . Thi s dat a screenin g polic yhelp s t o ensur e tha t NAD B summar ystatistic s ar e reliable . Moreover , th e polic yo f usin g on e se t o f dat a validit y criteri a regardles s o f th e intende d us e o f th e dat a i s necessar ysinc e th e EPAmus t respon d quickl yt o numerou s request s fo r NAD B data . I t i s possible , however , tha t som e informatio n ma yb e unnecessaril ylos t t o th e genera l NAD B use r becaus e o f th e stringenc yo f th e criteri a fo r dat a validity . Nevertheless , stringen t criteri a ma yb e neede d fo r som e purposes , notabl yfo r determinin g whethe r Nationa l Ambien t Ai r Qualit y Standard s (NAAQS ) hav e bee n attained . Th e purpos e o f thi s repor t i s t o examin e dat a reliabilit ya s a functio n o f dat a completenes s i n orde r t o assis t th e EP Ai n it s revie wo f th e adequac y and appropriatenes s o f th e curren t NAD B dat a validit ycriteria .
W e conside r tw o importan t case s a t opposit e end s o f th e spectrumo f dat a usage : (1 ) th e determinatio n o f NAAQ S attainmen t a t a site , whic hi s essentia l t o th e implementatio n o f th e Clea n Ai r Ac t and whic hdepend s heavil yo n complet e data , an d (2 ) th e estimatio n o f th e statu s of , an d
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trend s in , ai r qualit ynationwide , fo r whic hmuc hles s complet e dat a ca n b e tolerate d sinc e dat a ar e poole d fro ma larg e numbe r o f sites .

METHODOLOG Y
W e tak e th e vie wi n thi s repor t tha t summar ystatistic s base d o n incom

plet e dat a ar e estimate s o f th e summar ystatistic s tha t woul d hav e bee n obtaine d fro mcomplet e data . Moreover , w e trea t th e se t o f observation s a t a sit e a s a rando msampl e fro mth e entir e se t o f pollutan t concentra
tions , eve n i n th e cas e o f regula r bu t intermitten t samplin g (s o tha t a samplin g schedul e o f onc e ever ysi xday s produce s a t mos t 1 7 percen t completeness) .
Fro mthi s viewpoint , th e correc t NAAQ S attainmen t statu s o f a sit e depend s solel yo n th e complet e se t o f measure d pollutant , concentrations , s o tha t misclassificatio n i s possibl e onl yfo r thos e site s havin g incomplet e data . Similarly , th e accurac yo f estimate d trend s in ' nationa l ai r qualit y depend s on th e dat a completenes s a t eac hsite.a s wel l a s th e se t o f site s use d t o formth e estimates . W e hav e thu s se t asid e othe r importan t component s o f dat a reliability , i.e. , measuremen t erro r (du e t o a variet y o f inheren t limitations , suc ha s instrumen t calibratio n and maintenanc e o r recordin g and reportin g practices ) o r th e degre e o f spatia l representa
tivenes s o f measure d concentrations .
W e adop t tw o form s o f analysis : (1 ) w e analyz e hypothetica l "most
sensitive" scenario s (i n whic hsite s barel yattai n o r fai l t o attai n short-ter mai r qualit ystandards , o r wher e th e hypothetica l highvaria

bilit yo f pollutan t concentration s make s th e estimatio n o f long-ter m average s mor e difficult ) and (2 ) w e estimat e actua l erro r rate s base d o n 198 1 NAD B dat a (describe d i n Appendixe s Athroug hF) . Th e criterio n w e us e t o evaluat e th e effec t o f dat a completenes s require

ment s o n th e estimatio n o f nationa l ai r qualit ytrend s i s th e varianc e o f th e estimate d nationa l averag e i n a singl e year . W e sho wtha t stric t dat a
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o completenes s requirement s affec tth e varianc e i n two distinc tways . Tha t

i s , excludin g site s wit h les s complet e dat a has two effects : (1 ) a n increas e i n th e reliabilit yo fthos e site-specifi cestimate s include d i n th e nationa l estimat e an d (2 ) a reductio n i n th e numbe ro fsite s include d i n th e nationa l estimate
. Usin g 198 1 NAD B dat a w

e evaluat e thes e com petin g effect s o n th e varianc e o fth e estimate d nationa l average .

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O

G MAJO

R FINDING S I n general , reliabl e determinatio n o fth e short-ter m NAAQ S attainmen t statu s o fa sit e require s more complet e dat a tha n th e othe rdat a use s w e consider
. However , as severa l investigator s hav e noted , increasin g th e dat a completenes s proportio n (u p t o a point ) als o increase s th e chanc e o f misclassifyin g a sit e that , i n fact , has on e exceedance
. Thi s peculiarit y i s du e t o th e fac ttha tth e more complet e th e data , th e greate rth e chanc e o fincludin g th e exceedanc e i n th e sampl e an d thu s derivin g a n expecte d exceedanc e rat e greate rtha n unit ywhe n correctin g fo rth e incompletenes s o fth e dat a record
. Thi s scenari o ma ybe guarde d agains tb yrequirin g essentiall ycomplet e dat a (mor e tha n 95 percen tcompleteness) , o rby modifyin g th e procedur e fo rdeterminin g NAAQ S attainmen tstatus
. W e use d 198 1 dat a i n tw o ways t o analyz e dat a completenes s needs : (1 ) w e estimate d th e expecte d rat e o fmisclassificatio n fo rsite s tha tme t curren tan d alternativ e completenes s requirement s i n 1981 , an d (2 ) fo r long-ter m lea d an d particulat e standard s w e estimate d "critica l intervals " abou tth e standard s withi n whic h misclassificatio n probabilitie s excee d 1 0 percent , an d w

e sho who wthes e interval s narro was more complet e dat a ar e required
. (Critica l interval s ar e define d i n Sectio n 3 , an d shoul d no tbe confuse d wit h confidenc e intervals. )

O Eac h for m o fanalysi s serve s a differen tpurpose . Th e firs tindicate s

rate s o fmisclassificatio n unde rcurren tcompletenes s requirement s bu ti s les s usefu l fo restimatin g th e consequence s o ftightenin g o rrelaxin g thes e requirements
. Th e secon d for m o fanalysi s use s characteristic s o f

O 831<+6 r1 x v n

## G P.2 0



## G

G th e 198 1 dat a t o estimat e th e consequence s o f variou s dat a completenes s

requirement s o

nth e classificatio no f leado r particulat e monitorin gsite s whos e long-term

average s ar e nea r th e standard . Th e secondform thu s focuse s o

nthos e site s whos e long-term averag e concentration s ar e nea r th e standar dwithou t addressin gth e questio no f ho w many suc hsite s ther e ar e likel y t o b e (whic hcanno t be don e reliabl y inth e absenc e o f muc hmor e dat a o r stron gassumption s o f uncertai nvalidity) .

G

G

O Th e probabilit yo fmisclassifyin g a n attainmen tsit e unde rcurren tdat a

completenes s requirement s i s 1 percen tfo rth e 1-hou rC O standard , 2 percen tfo rth e 8-hou rCO , 24-hou rS0 2 , an d 24-hou rTSP standards , an d 8 percen tfo rth e dail ymaximu m ozon e standar d (se e Tabl e 3-2)
. Wheneve r reliabl e estimatio n wa s possible , w

e estimate d th e probabilit yo fmis classifyin g a nonattainmen tsite
. Fo rth e 24-hou rSO 2 standar d an d th e 1-hou rC

O standard , reliabl e estimatio n wa s no tpossibl e du e t o th e smal l numbe ro fnonattainmen tsite s (les s tha n 10)
. Th e probabilit yi s les s tha n 1 percen tfo rth e 8-hou rC O standar d an d th e dail ymaximu m ozon e standard , an d 6 percen tfo rth e 24-hou rTSP standard
.



## O

O



# o W

e attempte dt o us e th e firs t for m o f analysi s t o estimat e th e effect s o f alternativ e dat e completenes s requirement s onth e probabilit y o f misjudg in gth e attainmen t o f short-term standards . Thi s wa s don e b y restrictin g th e analysi s t o thos e site s meetin gth e alternativ e requirements . Fo r continuousl y

monitore dpollutants , a relaxatio no f th e 7 5 percen t require men t t o 5 0 percen t produce dn o appreciabl e differenc e i nth e probabilit y o f misclassification . It i s theoreticall y possible , bu t impractical , t o reduc e th e probabilit y o f a fals e determinatio no f nonattainmen t t o zer o b y requirin g9 5 percen t complet e data . Fo r th e curren t 24-hou r TS P stan dard , w e examine dsite s meetin gcompletenes s requirement s o f 5 , 12 , and 2 5 percent , i.e. , requirement s o f 5 , 11 , an d2 3 vali dsample s pe r quarter , respectively . Again , th e analysi s wa s insensitiv e t o difference s i ndat a completeness , althoug hth e estimat e fo r 5 an d2 5 percen t completenes s differe dslightly . 

## G

O 83m6 r - 

## xvmP.2 1 G

Fo rlong-ter m standards , th e 198 1 dat a indicat e tha tth e probabilit yo f Q misclassifyin g th e statu s o fa sit e tha thas actuall yattaine d a standar d

an d tha tmeet s curren tNAD B completenes s requirement s i s 2 percen tfo rTSP an d les s tha n 1 percen tfo rothe rpollutant s (se e Tabl e 3-1)
. Th e chanc e o fmisclassifyin g th e statu s o fa TSP monitorin g sit e tha thas no t Q attaine d th e annua l standar d i s estimate d t o be 9 percent
. Th e estimate d

chanc e o fmisclassificatio n i s greate rfo rTSP site s tha thav e no t attaine d th e standar d tha n fo rthos e tha thav e attaine d th e standar d becaus e th e nonattainmen tsite s ten d t o be onl yslightl yabov e th e O standard , wherea s th e attainmen tsite s ten d t o be wel l belo wth e stan dard
. Fo rothe rlong-ter m standards , ther e ar e to o fe wnonattainmen t site s t o reliabl yestimat e th e rat e o fmisclassifyin g suc h sites
. Thes e result s sugges ttha tmisciassification s ar e unlikel yunde rcurren tdat a G completenes s requirements
. Thi s i s tru e provide d tha tth e 198 1 dat a ar e

representativ e o fothe ryears , i.e. , s o tha tactua l long-ter m average s ar e wel l belo wth e standar d fo ral l bu ta smal l fractio n o fsites
. G A

s i n th e cas e o fshort-ter m standards , th e misclassificatio n rat e wa s approximatel yth e same fo rsite s meetin g variou s dat a completenes s requirements
. Th e exceptio n i s tha tth e estimate d rat e o fmisclassi ficatio n o fTSP site s tha thav e no tattaine d th e standar d drop s fro m 9 O percen tt o 3 percen twhe n 25 percen tcompletenes s i s required
.

Thus , direc testimatio n o fexpecte d rate s o fmisclassificatio n generall y require s more dat a o rstronge rassumption s (o funcertai n validity ) t o G distinguis h th e effect s o falternativ e dat a completenes s requirements
.

Usin g th e secon d for m o fanalysis , i n whic h w e estimate d "critica l intervals " abou ta give n standard , w e analyze d th e effec to fdifferen t O completenes s requirement s o n th e accurac yo fclassification s o fattainmen t

o fth e quarterl ylea d standar d an d th e annua l TSP standard
. W e gav e specia l attentio n t o thes e tw o pollutant s sinc e the yar e typicall ysample d onl yonc e ever ysi xdays
. Fo reac h pollutan tw e estimate d th e expecte d G tota l numbe ro fmisclassification s (tha tis , misclassification s o fbot h

83U6 ri xi x G

# o

o

o

o

o attainmen t an d nonattainment ) t o be les s than 5 percent ; th e estimate d percentag e fo r lea

d wa s les s than tha t fo r TS P (se e Figure s 3- 1 through 3-3) . Fo r lea

d (quarterl ystandard =1. 5 pg/nr) , th e estimate d critica l interva l whe n 1 2 sample s pe r quarte r ar e required i s -1 7 percen t t o +2 7 percent , i.e. , 1 7 percen t belowt o 2 7 percen t above th e standard . Fo r TS P (annua l standard = 7 5 pg/m 3 ) , the critica l interva l when five sample s pe r quarte r ar e required i s -1 1 percen t t o +1 3 percent . I f 1 2 TS P sample s pe r quarte r wer e required , th e interva l woul d narrowt o - 7 percen t t o + 8 percent .
I f our goa l wer e t o contai n thes e critica l interval s withi n ± 1 0 percen t o f the respective standards , then strengthene d requirement s shoul d b e considere d fo r lea

d an d possibl yfo r particulates . Indeed , judging fro m ou r analysi s o f TSP , thi s goa l woul d be achieve d unde r a recentl ypropose d revision t o standard s fo r particulat e matte r tha t include s a requiremen t o f 1 2 vali d observation s pe r quarte r (EPA , 1984 ; 4 9 F R 10434) . O

O Asimila rcritica l interva l analysi s o fshort-ter m standard s i s possible ,

althoug h thi s woul d requir e additiona l assumption s abou tth e frequenc y distributio n o fconcentration s a tindividua l sites
. I n th e interest s o f tim e an d projec tresource s w e di d no tconduc tthi s analysis , althoug h i t ma yb e usefu l t o d o s o i n th e future
.



### O

O

O For reliabl e estimation o f nationa l trends , th e benefit s o f relaxin g dat a completenes s requirements , i.e. , broadening th e bas e o f site s fro mwhic h t o for mth e nationa l averag e ove r successive years , outweig hth e dis

advantage s o f including th e site s tha t have les s complet e dat a an d therefor e les s reliabl e summar ystatistic s (se e Section 5) . Thi s i s becaus e the variabilityin ai r qualityamon g site s outweigh s the samplin g variabilit ya t individua l sites . Althoug hno optimu

mrequiremen t ca

n b e identifie d fro

mthe analysis , the curren t 5 0 percen t dat a completenes s requiremen t used fo r th e annua l repor t o n nationa l ai r qualitytrend s coul d be relaxed withou t increasin g calculate d variances . Thi s conclusio n i s based o

n th e distributio n o f th e percentage s o f dat a completenes s foun d



### O 831"+6 r 1 X X

### i nth e NADB record s fo r 1981 , andassume s tha t th e distributio nwoul dno t

chang e substantiall y

i nfutur e year s i f th e curren t requiremen t fo r estimatin gnationa l trend s wer e relaxed .

RELATE DISSUE S
W e hav e attempte dt o be thoroug hwithi nth e scop e o f thi s study , howeve r we mus t poin t ou t tha t dat a completenes s requirement s needt o be evaluate d i na broade r contex t tha t include s (1 ) overal l dat a quality ; (2 ) th e procedure s use dt o determin e th e attainmen t statu s o f a site , an d (3 ) th e ambien t standard s themselves . Som e alternative s t o th e curren t procedur e fo r determinin gshort-term attainmen t statu s us e a greate r numbe r o f th e highconcentration s recorde d a t a sit e (se e Sectio n2) . Althoug hthes e alternativ e procedure s ar e somewha t mor e complicated , they appea r t o b e les s sensitiv e t o incomplet e dat a an davoi dth e counter-intuitiv e result , note dabove , tha t th e chanc e o f misclassificatio nincrease s wit hincreasin gdat a completeness . Althoug hthi s repor t focuse s o ndat a completeness , ther e ar e othe r aspect s o f dat a reliability , e.g. , qualit y assuranc e procedures . I t i s importan t t o remembe r tha t requirin gmor e complet e data , e.g. , requirin gmor e frequen t intermitten t sampling , i s no t th e onl y way t o increas e dat a reliability , andno t necessaril y th e mos t cost-effectiv e way . Thu s al l aspect s mus t b e considere dtogethe r i f enhance ddat a reliabilit y i s th e objective . Similarly , th e questio no f dat a reliabilit y belong s t o a large r cirel e o f issue s concernin geffectiv e ai r qualit y management . I f increase ddat a
831"46 r i XX I

### reliabilit y reduce s th e chanc e o f misclassification , the nth e marginal cost s o f improve ddat a reliabilit y shoul db e weighe dagains t th e economi c an dpubli c healt hbenefit s o f fewe r misclassifications . I f we reduc e th e chanc e tha t anattainmen t sit e wil l b e misclassifie da s nonattainment , the nunnecessar y

administrativ e an

dcontro l cost s wil l als o be reduced . Likewise , i f w e reduc e th e chanc e tha t a nonattainmen t sit e wil l b e misclassifie da s attainment , the npresumabl y publi c healt hi s bette r maintained . I

nevaluatin gth e latte r benefit , however , on e shoul dbea r i n min dtha t a margi no f safet y i s incorporate dint o ambien t standard s s o tha t actua l pollutan t concentration s a t a nonattainmen t sit e may ye t b e below level s causin gadvers e healt heffects . Moreover , i t i s possibl e tha t wit hsufficien t effort devote dt o dat a reliability , ou r certaint y abou t actua l ai r qualit y coul dexcee dou r certaint y abou t ai r qualit y heait heffects . I nshort , monitorin grequirement s (dat a completeness , qualit y assurance , number s o f monitors , frequenc y o f sampling , etc. ) andothe r regulator y issues , suc ha s th e margi no f safet y embodie di nambien t standards , ar e interdependent . Fo r example , th e smalle r th e margi no f safet y use di n derivin ganai r qualit y standard , th e les s w e ca naffor dt o misjudg e th e attainmen t statu s o f a site , andth e greate r th e nee dfo r highl y reliabl e data .

RECOMMENDATION S
On e us e o f th e NADB dat a tha t we conside r i s th e estimatio no f th e statu s o f an dtrend s i nai r qualit y nationwide . Tightenin gth e dat a requirement s ha s tw o competin geffects : (1 ) th e site s meetin gth e stricte r require ment s (an

dtherefor e include di nth e nationa l average ) hav e mor e reliabl e ai r qualit y

summary statistics , bu t (2 ) th e exclusio no f site s wit hles s reliabl e statistic s reduce s th e sampl e siz e use dt o for m th e nationa l average . Ou r conclusio ni s tha t th e curren t 5 0 percen t dat a completenes s requiremen t fo r determinin gnationa l trends , whic hi s a relaxatio no f th e 7 5 percen t NADB requirement , shoul dbe furthe r relaxe dbecaus e th e 83me r l xxi i

# o

o advantag e o f a larg e sampl e siz e outweigh s th e advantag e o f reliabl e

statistic s a t individua l sites . Unfortunately , th e optimumrequiremen t canno t b e identifie d fro mou r analysis , s o tha t an yspecifi c recommenda

tio n wil l requir e furthe r consideration .


### G

O

G

O

©

G >



### G

G Th e EP Astaf f responsibl e fo r th e estimatio n and reportin g o f nationa l ai r

qualit ytrend s hav e direc t acces s t o NAD B data . Thi s i s an exampl e o f a specia l group o f NAD B user s wh o ca n appl ydat a completenes s requirement s accordin g t o thei r particula r needs . I n considerin g th e releas e o f NAD B dat a t o th e genera l user , however , i t appear s wis e t o continu e th e polic y o f usin g on e se t o f dat a completenes s requirements . Specia l user s wit h direc t acces s t o NAD B data , suc ha s thos e responsibl e fo r th e estimatio n o f nationa l ai r qualit ytrends , shoul d continu e t o determin e th e degre e o f dat a completenes s neede d fo r thei r particula r application .
Becaus e o f th e practicalit yo f usin g on e se t o f requirements , th e require

ment s shoul d b e base d o n th e commo n applicatio n havin g th e greates t nee d fo r complet e data . On thi s basis , w e hav e focuse d o n th e issu e o f whethe r curren t NAD B criteri a provid e sufficien t protectio n agains t misclassifyin g th e attainmen t statu s o f a sit e wit hrespec t t o short-ter mo r long-ter m standards . Certainly , accurat e estimate s o f nationa l trend s requir e les s complet e dat a tha n d o accurat e classification s o f individua l site s (compar e Figure s 5- 1 throug h5- 9 wit hTable s 3- 1 an d 3-2) . O f course , w e canno t compar e thes e dat a need s quantitativel yunti l w e prescrib e th e accuracie s accept
abl e i n eac hcase , bu t th e evidenc e supportin g th e statemen t i s clea r nevertheless . I t i s als o clea r tha t ther e ar e othe r possibl e dat a uses , no t examine d i n thi s report , tha t depen d eve n mor e heavil yo n complet e dat a tha n doe s th e determinatio n o f attainmen t status , e.g. , inferrin g th e maximu m10-minut e concentratio n fro mhourl ydata . But , fo r th e purpos e o f establishin g appropriat e NAD B requirement s fo r complet e data , th e determinatio n o f attainmen t statu s seem s t o b e th e mos t exactin g us e o f ai r qualit ydat a tha t i s commo n t o al l th e pollutant s fo r whic hw e hav e nationa l ambien t ai r qualit ystandards . 83U6 T 1 XXI1 1 

### G

# o

o

o Direc t estimate s o f th e expecte d misclassificatio nrat e fo r continuousl y

monitore d pollutant s d o no t chang e appreciabl ywhe nth e curren t NAD B requiremen t o f 7 5 percen t dat a completenes s i s relaxe d t o 5 0 percent . Analyse s o f th e mos t sensitiv e scenario s (whic hcoul d becom e mor e commo n tha nthe ywer e i n1981 ) war nagains t thi s relaxation , however . In particular , i f th e procedure s fo r determinin g th e attainmen t o f short-ter m standard s remai nunchanged , i t seem s bes t fo r th e tim e bein g t o als o maintai ncurren t dat a completenes s requirement s fo r continuousl ymonitore d pollutants .



## O

O

O Similarly , i nth e cas e o f intermitten t sampling , e.g. , fo r lea d and

particulat e matter , direc t estimate s o f misclassificatio nrate s barel y distinguis hbetwee nth e alternativ e dat a completenes s requirement s w e consider . I

ngeneral , th e NAD B dat a validit ycriteri a requir e onl yfiv e sample s pe r quarter , and thu s onl y2 0 sample s pe r year . Fo r lead , however , 1 2 sample s pe r quarte r ar e require d fo r attainmen t determination s (EPA , 1979 ; 4 3 FR46266) . Ineithe r case , i t i s muc hmor e difficul t t o ensur e th e correc t classificatio no f ai r qualit ystatu s unde r a ninter

mitten t sampling . Critica l interva l analyse s (Figur e 3- 1 throug h3-3 ) demonstrat e th e advantage s o f strengthenin g dat a completenes s requirement s fo r lea d and particulates . I t i s therefor e advisabl e t o adop t th e recentl ypropose d requiremen t o f 1 2 particulat e sample s pe r quarte r (EPA , 1984 ; 4 9 FR10434 ) and t o conside r eve nmor e frequen t samplin g o f lead . 

## O Concernin g th e issue s relate d t o dat a completeness--les s centra l t o th e

scop e o f thi s studybu t n o les s importan t fo r effectiv e ai r qualit y management--w e recommen d consideratio no f tw o change s i nprocedures . 

## O (1 ) Agreate r numbe r o f th e hig hconcentration s recorde d a t a sit e shoul d b e use d i norde r t o provid e mor e robus t short-ter m attainmen t inferences . 

## O

O 83146 T l XX I vP.2 7



### (2 ) Dat a completenes s consideration s shoul db e incorporate di nth e review , revision , andinterpretatio no f ai r qualit y standards , alon gwit hsuc hrelate dissue s a s th e cos t o f mor e complet e data , othe r limitation s o ndat a reliability , th e cos t o f misclassifyin gattainmen t status , an dth e existin gmargin s o f safet y use dt o se t threshold s fo r ambien t concentrations .

831t6 r 1 

## xx vINTRODUCTIO N

The U.S . Environmenta l Protectio nAgenc y (EPA ) store s ambien t ai r qualit y data , obtaine dfro

m a nationwid e networ ko f monitorin gstations , inth e Nationa l Aerometri c Dat a Bank(NADB) . Statistic s summarizin gth e ai r qualit y a t eac hmonitorin gstatio nar e als o store dinth e NADB . Thes e summary statistic s ar e mad e availabl e t o th e governmen t an dpubli c provide dtha t certai ndat a validit y criteri a ar e met , chie f amon gthes e bein grequirement s fo r dat a completenes s (give ninAppendi xG) . Thi s dat a screenin gpolic y help s t o ensur e tha t NADB summary statistic s ar e reliable . Moreover , th e polic y o f usin gon e se t o f dat a validit y criteri a regardles s o f th e intende dus e o f th e dat a i s necessar y sinc e th e EPA mus t respondquickl y t o numerou s request s fo r NADB data . I t i s possible , however , tha t some informatio nmay b e unnecessaril y

los t t o th e genera l NAD B use r becaus e o f th e stringenc y o f th e dat a validit y criteria . Nevertheless , a stringen t criteri a may b e neede dfo r some purposes , notably , fo r determinin gwhethe r Nationa l Ambien t Ai r Qualit y Standard s (NAAQS ) hav e bee nattained . The purpos e o f thi s repor t i s t o examin e dat a reliabilit y a s a functio no f dat a completenes s inorde r t o assis t th e EP A init s review

o f th e adequac y an dappropriatenes s o f th e curren t NADB dat a validit y criteria .

BACKGROUN D Ai r qualit y

dat a ar e provide dt o th e Nationa l Aerometri c Dat a Bank(NADB ) primaril y

b y stat e andloca l agencies . Include di nth e NADB recor do f ai r qualit y summary

statistic s fo r a monitorin gstatio ni s a "criteri a flag "
83146 r 2indicatin gwhethe r NADB dat a validit y criteri a ar e met . Thes e (an dother ) dat a validit y

criteri a ar e presente dinAppendi xG , bu t they may b e roughl y summarize da s a 7 5 percen t dat a completenes s requirement . (Not e tha t th e monitorin gschedul e fo r leadan dparticulat e matte r i s onc e ever y si xdays . Inthes e cases o f intermitten t samplin go f 24-hou r concentra tions , NADB criteri a requir e fiv e sample s pe r quarte r an dthu s 2 0 sample s pe r year .
I nrespondin gt o typica l request s fo r NADB data , th e recor do f a sit e failingt o mee t th e criteri a may be writte nwit hquestio nmarks t o indicat e questionabl e dat a reliability , o r th e recor dmay no t b e writte n a t all . Thus , wherea s authorize dusers o f NADB dat a hav e acces s t o al l records , th e record s indicatin gtha t NAD B criteri a hav e bee nme t consti tut e a commonsubse t o f NADB dat a tha t i s reliabl e an dwidel y

available .
I nthi s repor t we conside r th e effec t o f excludin gai r qualit y dat a fro

m site s tha t fai l t o mee t certai ndat a completenes s requirements . Mor e specifically , w e conside r whethe r curren t NAD B requirement s appea r t o b e satisfactor y

o r nee dt o b e changed , and , i nth e latte r case , whethe r dat a completenes s requirement s shoul dvary wit hdat a usag e andtyp e o f monitor in g(intermitten t o r continuous) .
We conside r tw

o importan t cases at opposit e end s o f th e spectru m o f dat a usage : (1 ) th e determinatio no f NAAQ S attainmen t at a site , whic hi s essentia l t o th e implementatio no f th e Clea nAi r Ac t an dwhic hmake s a heav y deman dfo r dat a completeness , an d(2 ) th e estimatio no f th e statu s o f an dtrend s i nai r qualit y nationwide , fo r whic hmuc hles s complet e dat a canbe tolerate d(sinc e dat a ar e poole dfro m a larg e numbe r o f sites) .
Fo r eac ho f thes e two dat a use s we conside r summary statistic s relevan t t o short-term

an dlong-term

ai r qualit y

standards . Tha t is , we conside r th e numbe r o f exceedance s o f th e short-term standard s (havinganaveragin g time o f 2 4 hours or'less) , an dth e annua l o r maximum quarterl y

average . Again , b

y treatin gbot hpea kvalu e summary statistic s (wher e th e effec t o f

831<+ 6 2incomplet e dat a i s pronounced ) an dlong-term

average s (wher e dat a com pletenes s need s ar e minimal) , we hop e t o provid e usefu l benchmark s fo r othe r dat a uses . Currently , th e attainmen t o f mos t nationa l ambien t ai r qualit y standard s i s determine dseparatel y fo r eac hyea r o f data . However , a three-yea r attainmen t perio di s use dinth e cas e o f ozone , an dmulti-yea r period s ar e bein gconsidere dfo r othe r short-term standards . We therefor e addres s th e dat a completenes s neede dfo r bot hsingle-yea r an dmulti-yea r attainmen t standards .

METHODOLOG YANDORGANIZATIO N OF RESULT S
W e tak e th e view

i nthi s repor t tha t summary statistic s base do nincom plet e dat a ar e estimate s o f th e summar y statistic s tha t woul dhav e bee n obtaine dfro

m complet e data . Moreoever , we trea t th e se t o f observation s a t a sit e a s a random sampl e from

th e entir e se t o f pollutan t concentra tions , eve ni

nth e cas e o f regula r but intermitten t samplin g(s o tha t a samplin g schedul e o f onc e e^/ery si xday s produce s a t mos t 1 7 percen t completeness) .
From thi s viewpoint. , th e correc t NAAQ S attainmen t statu s o f a sit e depend s solel y o nth e complet e se t o f measure dpollutan t concentrations , s o tha t misclassificatio ni s possibl e onl y fo r thos e site s havin g incomplet e data . Similarly , th e accurac y o f estimate dtrend s innationa l ai r qualit y depend s o

nth e dat a completenes s at eac hsit e a s wel l a s th e sampl e o f site s use dt o form

th e estimates . We hav e thu s se t asid e othe r importan t component s o f dat a reliability , i.e. , measuremen t erro r (due t o a variet y o f inheren t limitations , suc ha s instrumen t calibratio nan dmaintenanc e o r recordin gan

dreportin gpractices ) o r th e degre e o f spatia l representa tivenes s o f measure dconcentrations .
We adop t tw

o form s o f analysis . I nSectio n2 we analyz e hypothetica l "most-sensitive " scenario s (inwhic hsite s barel y attai no r fai l t o attai n 83m 6 2 3P.3 1 

### O



# 0

o

o short-ter mai r qualit ystandards , o r i n whic hth e hypothetica l high

variabilit yo f pollutan t concentration s make s th e estimatio n o f long-ter m average s mor e difficult) . In Sectio n 3 w e asses s th e likel yerro r rate s base d o n 198 1 NAD B dat a (describe d i n Appendixe s Athroug hF) .
I n ou r treatmen t o f short-ter mNAAQS , th e assigne d statu s o f a sit e i s base d o n a quantit yknown a s th e "expecte d numbe r o f exceedances, " tha t is , attainmen t statu s i s determine d assumin g tha t th e rati o o f observe d exceedance s t o tota l observation s i s maintaine d fo r th e complet e dat a set . Th e criterio n w e us e t o judg e th e degre e o f dat a completenes s require d t o accuratel ydetermin e NAAQ S attainmen t i s th e chanc e o f misclassifyin g th e statu s o f a site . Th e chanc e i s zer o fo r site s havin g 10 0 percen t
^ complet e dat a o r fo r site s havin g n o exceedances . Otherwis e th e chanc e o f

misclassificatio n depend s on bot hth e degre e o f dat a completenes s and th e actua l numbe r o f exceedances . Q In Sectio n 2 w e conside r th e effec t o f dat a completenes s o n th e chanc e o f

erroneousl yclassifyin g th e statu s o f a sit e a s nonattainmen t whe n i n fac t th e referenc e concentratio n ha s bee n exceede d exactl yonc e i n th e cours e o f th e year . W e als o conside r th e chanc e o f erroneousl yclassifyin g th e Q statu s a s attainmen t whe n th e sit e ha s exactl ytw o exceedances . Thi s

analysi s i s als o carrie d ou t fo r ai r qualit ystandard s allowin g n o mor e tha n thre e exceedance s i n thre e years . Q In Sectio n 3 w e us e 198 1 NAD B dat a t o estimat e th e actua l (bu t unknown )

rate s o f misclassification . W e firs t estimat e th e frequenc ydistributio n amon g site s o f th e actua l numbe r o f exceedances . W e the n us e thi s distributio n t o estimat e th e probabilit yo f misclassifyin g site s meetin g Q variou s dat a completenes s requirements .

Fo r long-ter m(annua l o r quarterly ) ambien t standards , th e chanc e o f misclassifyin g a sit e depend s no t onl yo n th e degre e o f dat a completenes s O a t th e sit e bu t als o o n th e empirica l frequenc ydistributio n o f th e entir e

yea r o f pollutan t concentration s a t th e site . In Sectio n 2 w e asses s dat a
831<+ 6 2 

### O

### completenes s requirement s b y assumin gtha t th e actua l averag e concentra tio nat th e sit e i s 1 0 percen t abov e o r below th e standard , an

dtha t th e standar ddeviatio no f th e yea r o f concentration s at th e sit e i s twic e the average . I

nSectio n3 we empiricall y estimat e probabilitie s o f misclassi ficatio nusin g198 1 data . I nSectio n4 we introduc e a criterio nfo r evaluatin gthe effec t o f dat a completenes s requirement s o nth e estimatio no f nationa l ai r qualit y trends , namel y

th e varianc e o f th e estimate dnationa l averag e ina singl e year . Excludin gsite s wit hles s complet e dat a ha s two effects : (1 ) th e reliabilit y

o f th e site-specifi c estimate s include dinth e nationa l estimat e i s increased , an d(2 ) th e numbe r o f site s include dinth e nationa l estimat e i s reduced . I nSectio n5 , using198 1 NADB data , we evaluat e thes e competin geffect s o nth e varianc e o f th e estimate dnationa l average .

8311+ 6 2

### STATISTICAL PROCEDURE S FORDETERMINING TH E AI RQUALIT YSTATU S O F A SIT E

ANNUAL O RQUARTERL Y(LONG-TERM ) AVERAGE S Suppos e we wis ht o kno w (u pt o measuremen t error ) the annua l averag e concentratio npi o f a pollutan t a t a particula r site , wit hinde xi , base d ona complet e se t o f N measurements , bu t tha t onl y n i vali dmeasurement s wer e recorded , th e remainin gm i = N - ni bein geithe r invali do r missing . Lettin gPi denot e th e proportion , ^-/N , o f dat a completeness , i t canbe A 

### show n(Cochran , 1963 ) tha t th e sampl e averag e p . ha s expecte dvalu e p , an d varianc e ( 1 - p i 

### )/pi 

### ,(o|/N) :

E u .


## Va r P i a.



### Moreover , annua l ai r qualit y measurement s usuall y entai l larg e number s o f bot hmissin gan

dobserve dvalue s (m i an dnM ) wit hrelativel y few extreme values . Unde r thes e conditions , formulate dmor e precisel y b y Cochra n A 

### (1963) , wh o cite s Hajek(I960) , th e samplin gdistributio no f P i i s approximatel y

normal . 2 Thu s [( 1 - p^)/p^Do./ N i s a natura l measur e o f th e erro r i nestimatin gth e annua l averag e (pi ) o f al l N measurement s b

y th e averag e o f a proportio n (Pi ) o f th e N

measurements .

831H6 r 3P.3 4

W e may us e thes e results—th e expecte dvalue , variance , an dapproximat e A normalit y

o f Pi~t o determin e th e minimu m acceptabl e proportio no f measurements , pg , provide dtha t (1 ) w e specif y a relativ e erro r tolerance , e , suc htha t error s o f large r magnitud e have , say , onl y a 5 percen t o f occurring , an

d(2 ) we hav e some ide a o f th e coefficien t o f variation , aJ\i,. Specificall y w e have |Mi " Mi l P r l— ' —

> E ) = P r I" 1 " u i ep .

(Varp\) 1 / 2 (Var^) 1 ' 2

* 2 EM .

.(Var Ui ) 

### 1/

2
$ e W i (Np., ) i/2\ n

' i l ' > .
wher e * i s th e standar dnorma l cumulativ e distributio nfunction . Th e abov e expressio nmay b e use dt o calculat e eithe r p g fro m a prescribe d probabilit y

(e.g. , 5 percent) , o r a confidenc e boun do f a prescribe dleve l A (e.g. , 9 5 percent ) o nth e absolut e relative erro r (|p . - p.|/p. ) giventhe proportio no f dat a completenes s (Pi ) an dthe coefficien t o f variatio n(oi/p. ) at a particula r site . Tabl e 2- 1 show s th e minimu m proportio np

g correspondin g t o severa l combination s o f e , a^/\x^, an dN . Tabl e 2- 2 show s E a s a functio no f N , oJvi, an

dp. . Not e tha t th e 7 5 percen t criterio nusedb y th e SAROAD system implie s tha t partia l annua l average s ar e no t likel y t o diffe r b

y mor e thanappprbximatel y on e percen t fro

m complet e annua l average s i f th e coefficien t o f variatio nequal s unit y (10 0 percent) . Th e correspondin g erro r fo r th e 5 0 percen t completenes s criterio ncommonl y usedi

nreportin g trend s i

nannua l average s i s approximatel y tw o percen t (for a

nindividua l site) .

8314 6 3TABL E 2-1 . Th e require d dat a completenes s proportio n (pg ) a s a functio n o f

th e tota l numbe r o f possibl e measurement s (N) , th e coefficien t o f varia

tio n (oi/pi) , and th e prescribe d maximumrelativ e erro r (E ) occurrin g wit h9 5 percen t probability .

N= 876 0 (hrs/yr )

N= 292 0 ( 3 hrs/yr )

N= 109 5 ( 8 hrs/yr )

N= 36 5 (days/yr )

N= 9 1 (days/qtr )

N= 3 0 (days/mo ) °i /y i

0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0 .00 1 0.9909 6 0.9977 2 0.9994 3
0.9969 7 0.9992 4 0.9998 1
0.9988 6 0.9997 2 0.9999 3
0.9996 2 0.9999 1 0.9999 8
0.9999 1 0.9999 8 0.9999 9
0.9999 7 0.9999 9 1.0000 0 

### .0

1 0.5229 7 0.8143 1 0.9460 7
0.7668 4 0.9293 6 0.9813 5
0.8976 5 0.9722 9 0.9929 2
0.9633 9 0.9905 9 0.9976 3
0.9906 1 0.9976 4 0.9994 1
0.9968 9 0.9992 2 0.9998 0 

### e .0 5

0.0420 1 0.1492 3 0.4123 3
0.1162 6 0.3447 9 0.6779 3
0.2597 1 0.5839 0 0.8487 8
0.5127 8 0.8080 5 0.9439 4
0.8084 8 0.9440 9 0.9854 1
0.9275 6 0.9808 5 0.9951 4 

### .1 0

0.0108 4 0.0420 1 0.1492 3
0.0318 4 0.1162 6 0.3447 9
0.0806 3 0.2597 1 0.5839 0
0.2083 1 0.5127 8 0.8080 5
0.5134 6 0.8084 8 0.9440 9
0.7619 7 0.9275 6 0.9808 5 1.0 0

0.0001 1 0.0004 4 0.0017 5
0.0003 3 0.0013 1 0.0052 3
0.0008 8 0.0035 0 0.0138 4
0.0026 2 0.0104 1 0.0404 0
0.0104 4 0.0405 0 0.1444 6
0.0310 2 0.1135 1 0.3387 1

8314 6 8313 2

### TABL E 2-2 . Relativ e erro r (E ) fo r dat a completenes s proportion s p . = 0.5 0 and p . = 0.75 . P.3 6

N= 876 0 (hrs/yr )

N= 292 0 ( 3 hrs/yr )

N= 109 5 ( 8 hrs/yr )

N= 36 5 (days/yr )

N= 9 1 (days/qtr )

N= 3 0 (days/mo ) a • / u •

r M i 0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0
0. 5 1. 0 2. 0 

### .5 0

0.0104 7 0.0209 4 0.0418 8
0.0181 4 0.0362 7 0.0725 4
0.0296 1 0.0592 3 0.1184 6
0.0512 9 0.1025 9 0.2051 8
0.1027 3 0.2054 6 0.4109 2
0.1789 2 0.3578 4 0.7156 8 

### .75

0.0060 5 0.0120 9 0.0241 8
0.0104 7 0.0209 4 0.0418 8
0.0171 0 0.0342 0 0.0683 9
0.0296 1 0.0592 3 0.1184 6
0.0593 1 0.1186 2 0.2372 4
0.1033 0 0.2066 0 0.4132 0

8311+ 6 8313 2P.3 7 

## O

O



# o I

ninterpretin gth e minimu m proportion s give ninTabl e 2-1 , not e tha t a give nmaximu

m relativ e erro r Emay see m eithe r excessivel y

stringen t o r to o lenien t dependin go nth e particula r application . Fo r example , 1 0 percen t relativ e erro r may be to o larg e i f w e nee dt o determin e th e attainmen t statu s o f a sit e whos e annua l averag e i s typicall y withi n1 0 percen t o f th e annua l averag e ambien t standar dwherea s fo r a sit e whos e annua l averag e i s typicall y les s tha nhal f th e standar d, a 1 0 percen t relativ e erro r specificatio nmay b e unnecessaril y

stringent .
O SHORT-TERM CONCENTRATION S Th e Observe dNumbe r o f Short-Term Exceedance s O Curren t nationa l ambien t ai r qualit y standard s (NAAQS ) fo r pollutan t concentration s average dove r 2 4 hour s o r les s influenc e th e presentatio n an danalysi s o f highshort-term concentrations . The short-term standard s

~ fo r mos t pollutant s stipulat e a nambien t concentratio ntha t shoul dno t be exceede dmor e tha nonc e pe r year , whic himplie s tha t th e secondhighes t short-term

concentratio nrecorde dat a sit e determine s whethe r th e sit e i s i nattainmen t o f th e standard . O It i s possibl e t o trea t th e secondhighes t valu e ina year' s partia l

sampl e o f short-term

concentration s a s anestimat e o f th e secondhighes t concentratio nina complet e sample , jus t a s we treate dlong-term Qaverages . Thi s turn s ou t t o be a difficul t approac hfro m a statistica l viewpoint , however , becaus e o f th e grea t variabilit y o f th e secondhighes t concentratio nan

dth e influenc e o f th e unknow ntai l distributio no f short term concentration s o

nth e samplin gbehavio r o f th e secondhighes t value . O Another , mor e workabl e approach , at leas t fro m a statistica l perspective , i s t o examin e th e sequenc e o f short-term concentration s at a sit e ove r a one-yea r perio dan

dt o simpl y

coun t th e numbe r o f time s th e ambien t Qconcentratio nexceed s th e standard . I f th e coun t i s n o mor e tha none , th e

short-term

standar di s attained ; otherwis e i t i s not . 8311+ 6 3 1 0 

## OP.3 8 

## O



# o

G

O

O

O

O Inthi s approac hth e sequenc e o f short-term concentration s i s converte dt o a 0- 1 value dsequence , inwhic h1 indicate s tha t the concentratio nexceed s th e standar dan

d0 indicate s otherwise . The.ke y questio nregardin gth e effec t o f dat a completenes s o ndeterminin gattainmen t statu s i s whethe r a n exceedanc e ha s bee noverlooked . Mor e specifically , we wis ht oknow th e probabilit y

tha t a sit e ha s twoo r mor e exceedance s bu t tha t nomor e tha n on e exceedanc e i s observe dinou r partia l sample . We may formulat e thi s a s th e followin gconditiona l probability : Pr (k . < 1 | x i 

## = 2 ) wher e ki = th e numbe r o f exceedance s inth e observe dsampl e o f siz e n i X i = th e unknow

ntota l numbe r o f exceedance s tha t occurre ddurin gth e year . Th e reasonfo r focusin go nth e cas e X . = 2 i s tha t thi s i s th e mos t challengin gproblem

fo r a fixe dpartia l sampl e size , ni ; we woul ddowel l t oprescrib e th e chance , sa y 3 , we ar e willin gt otak e tha t we fai l t o observ e th e twoexceedances , sinc e fo r large r value s o f X i ou r chanc e o f detectin ga violatio nonl y improves . Mor e generally , fo r a standar d allowin gnomor e tha nr exceedance s we woul dwan t t ocalculat e the Q probabilit y tha t r or fewe r exceedance s ar e observe dinth e partia l sampl e whe nther e ar e r + 1 exceedance s inth e complet e sample . Thi s conditiona l probabilit y i s give nb

y th e hypergeometri c distribution :

OFo r futur e referenc e we not e tha t
E (k i 

### | x. , p. ) = p i 

### x i


### O 83m 6 3 1 1P.3 9



### an d N - X i 

# va r(k i i x. , P 

# . ) =-**pn: p 

# i ( 1 

# " p 

# i } x

# i

* Pi U- Pi ) X n . (see , fo r example , Johnso nan dKotz , 1969) . Returnin gt o th e chanc e tha t no t all • r + 1 exceedance s ar e detected , w e hav e



### o r

Notin gtha t B*--Pr-(k. < r | x . = r + 1 )

1 - B = P r (k i = r + 1 | X i = r + 1 )

' N - r - 1 \ // N

n i n i - 1 n T ' r N N - 1 " • N

- r



## i " j



## _" T / N

\ _J_

- j N

\H - j / " N

-

N 

### vN 

### - j ; N

- j

= 

### P i -TH-J^-PI )

8314 6 3 1 2P.4 0



### w e see tha t 

## i - e - Pl 

## [ P 

## , - jj-i-j - d - P,) ] .. . [p f

## - ^ d - P,) ]

1 

# P i h -i^-p,-) ] -- - [P I -•&< ! - PI> ]

_r+ 1 / r+ 1 \

1 „ r, , . . 

## " P i 

## " I 2 J N P 

## i ( 1 

## " Pi ' 

## * " •

+ 

### (-l) r 

### r!(l) r 

### p j ( 

### l - P i 

### ) r



# - pr 1 

# * 1 ^ + l ) 

# (i) j

# pr j+ l 

# a - Pi> j



### wher e th e S^ i ar e Stirlin gnumber s o f th e firs t kin d(Abramowit z an

d Stegun , 1964) . Henc e 0 = 1 

## r+ 1

= 1 fo r r = 1 .

Tabl e 2- 3 give s th e dat a completenes s proportion , p 0 

### , require dt o reduc e th e ris ko f failin gt o detec t two exceedance s t o a specifie dlevel , 3 . Fo r th e 7 5 percen t completenes s criterion , ther e i s a napproximat e 4 4 percen t chanc e tha t a t leas t on e o f th e two exceedance s wil l no t be detected . Fo r th e 5 0 percen t completenes s criterio nth e ris ki s 7 5 percent . I t woul dseem the ntha t th e determinatio no f short-term attain men t statu s require s eithe r nearl y (e.g. , 9 5 percent ) complet e data , o r els e som e metho do f inferenc e othe r tha nmerel y countin gth e numbe r o f

8311+ 6 3 

## 1 3P.4 1



### TABL E 2-3 . Th e proportion , pg , o f dat a completenes s require d t o limi t th e ris kt o 3 o f no t detectin gr+ 1 exceedances .



## a 0.0 1 0.0 2 0.0 5 0.1 0 0.2 0 0.4 4 0.7 5 r= 1

0.99 5 0.99 0 0.97 5 0.94 9 0.89 4 0.74 8 0.50 0 P

O r= 3 0.99 7 0.99 5 0.98 7 0.97 4 0.94 6 0.86 5 0.70 7

8311+ 6 8 

## 1 4P.4 2



### exceedance s inth e partia l sampl e (se e EPA , 1979 ; Pac e an dFrank , 1982 ; Thral l an

dBurton , 1983) . Tabl e 2- 3 als o show s th e require ddat a completenes s fo r a three-exceedanc e standard , a topi c t o whic hwe no w turn .

Th e Estimate dNumbe r o f Short-Term Exceedance s
A nalternativ e procedur e fo r determinin gwhethe r short-term ai r qualit y standard s have bee nattaine dat a sit e i s t o extrapolat e fro m th e observe d exceedances , ki , t o th e tota l numbe r o f exceedances , X- , i.e. , t o estimat e Xi b

y

^ - k 1 

### /p 1 

### . Fro m the conditiona l moment s derive dfo r ki , we hav e

E (x\ | X. , Pi 

### ) = X i

. X

### " Pi Va r (x i 

### | X. , p. ) =~J— X i i



### s o tha t x i 

### i s a

nunbiase destimat e whos e varianc e approache s zer o a s P i approache s unity . Fo r a nr-exceedance short-term standard , we migh t judge a sit e t o be in attainmen t o f the standar donl y i f

^ < r+ | . Thi s procedur e reduce s the ris ko f failin gt o detec t nonattainmen t (x . > r + 1) , sinc e th e estimat e Xi i s a nextrapolatio no f th e observe d numbe r o f exceedance s (k^ ) among^ observe dconcentration s t o th e tota l numbe r o f exceedance s (x. ) inN concentrations . Bu t we have als o intro duce dth e ris ktha t X i migh t be overestimated . 831<+ 6 3 1 5P.4 3



### Thi s procedur e fo r determinin gwhethe r a short-term ai r qualit y

standar d ha s bee nattaine da t a sit e ca nb e cas t a s a statistica l tes t o f a hypothesis . A

sit e i s presume dt o b e i nattainmen t o f th e standar d(i.e. , 1 th e nul l hypothesi s i s that X i < r ) unles s X i * > r + - ^ , inwhic hcas e i t i s judge dt o hav e faile dt o attai nth e standard , i.e. , w e infe r that th e alternativ e hypotheis , X - * » r + 1 , holds . A "Typ e I " erro r occur s whe nth e sit e ha s actuall y attaine dth e standar d bu t we incorrectl y

infe r tha t i t ha s not . Previously , whe nwe determine d attainmen t solel y

onth e basi s o f th e observe dnumbe r o f exceedances , ki , thi s wa s impossible , sinc e k i canneve r be greate r tha nth e actua l numbe r o f exceedances , Xi . Now , however , th e probabilit y o f a Typ e I erro r i s a , wher e

a = P r (X i > r + j | Xi < r j . Whateve r th e proportio no f dat a completeness , Pi , th e probabilit y o f a Typ e I erro r wil l b e greates t whe nth e sit e i s jus t barel y inattainmen t o f th e standard , i ,e. , whe nx , = r , i nwhic hcas e
P r 

# \ V r + 

# 1 

# I x 

# i = r 

# ) * No wi fP i > 2r/(2 r+ 1 ) i ti s impossibl e fo rX i t o equa l o rexcee d r+ j sinc e 

# w

< 

### (2r)/(2 r+ 1 )

" r+ 

### 2
s o tha t
a = 0 i fp i 

### > 2r/(2 r+ 1 )
. 83m 6 3 

### 16P.4 4



### 1 I f 2( r - l)/(2 r +1 ) < p . < 2r/(2 r + 1) , X i wil l equa l o r excee dr + j onl y i f k - = r . Ingeneral , a s P i become s smaller , fewe r observe d exceedance s (k^ ) ar e require dt o produc e a nestimat e (x H 

### ) equalin g 1 or exceedin gr + j

, an dth e probabilit y

(a ) o f a Typ e I erro r increases , a s show ninTabl e 2-4 . O f course , whe nth e sampl e siz e (ni ) fall s below r , th e observe dnumbe r o f exceedance s (ki ) may be no mor e tha nn

i an dth e ris ko f a Typ e I erro r i s reduced . (W e assume throughou t thi s discussio n tha t N > (r+1 ) ( r + | ) s o tha t ( r + 1)/ N < 2/(2 r + 1). ) Th e binomia l approximatio ngive ninTabl e 2- 4 i s accurat e s o longa s N i s larg e relativ e t o r . Thus , basin ga

nattainmen t determinatio nonX i rathe r tha nk i introduce s some probabilit y

(a ) o f a Typ e I error , bu t th e maximu m probabilit y

(3 ) o f a Typ e I I erro r i s substantiall y reduce dfo r smal l value s o f Pi . We hav e

= P r(^ i < r+ | | x i 

### = r+ l )


# •I (r 

# : 

# T n 

# ; :. 

# K )

f o r

### 2( J ~ 1 ) < p 

### < 2j
_ r o r

### 2 r+ 1 p 

### i * 2 r+ 1

an d fo rj = 1 , 2 , 3 , ... , r+ 1
t 1 

### (r + 1 \ k n n 

### xr+1 - 

## S i l k ) p 

## i (1



## - p 

## i }



### O f specia l interes t ar e th e case s r = 1 , th e one-exceedanc e form o f short-term

standards , an

dr = 3 , a three-year , three-exceedanc e form o f

831»+ 6 3 1 7o

o •

TABLE 2-4
. Th e function s o fth e P i Interva l


### 7TTT < P i < l

2 r+ 1 K i

r- D 2 N p i 2 r+ 1
1 <„ " i < r N p i " N N #

n a ximu m propor t

2 j 2 r+ 1 •

probabil i io n p i o f

,

, j = 2 , t y , a

dat a

* 3 j ••t •

o fa Typ e I completenes s

, r P r

r 

# £ k= j r 

# £ k= l n . l 

# £ k= l •

erro r< » (x
. > r 

# (W; (0(n N 

# : 

# (0(S ( •

in d th e binomia l 

# 4lV r 

# > 0


### -)/(", ) -)/(»i ) 

# -V(-i ) • -

approximatio n •

t o th e , •

probabi l •

ity , a s
Binomia l Approximatio n

k= j 

# £ ( •

k= l V l 0
;)Pi< i 

# :) A

# * * ; )A

# < * -»i> r
- k -Pi) r " k -Pi) r " k

83H+ 6th e standards . Table s 2- 5 and2- 6 sho w th e binomia l approximation s t o a an d3 fo r r = 1 an

dr = 3 , respectively . Th e correspondin g plot s ar e show ninFigure s 2- 1 and2-2 .

Curren t Practic e inDeterminin g th e Short-Term

Attainmen t Statu s o f a Sit e
I nth e previous.sectio nwe calculate da an d3 , th e probabilitie s o f misclassifyin g attainmen t or nonattainmen t sites , respectively , i f th e estimate dnumbe r o f exceedance s (x ^ i s rounde dt o th e neares t intege r an d the ncompare dt o th e allowe dnumbe r o f exceedance s (r) . Thi s procedur e generate dth e regularl y space ddat a completenes s cutpoint s 2j/(2 r + 1 ) o r j/( r + 0.5 ) o f Tabl e 2-4 .
I nfact , th e curren t EPA polic y i s t o roundX i t o th e neares t tent han d the ncompar e th e rounde dvalu e t o r . Tha t is , th e statu s o f a sit e i s classifie da s nonattainmen t onl y i f x. , rounde dt o th e neares t tenth , exceed s r . Thi s procedur e generate s th e dat a completenes s cutpoint s j/( r + .05 ) whic har e greate r tha nth e correspondin g cutpoint s j/( r + 0.5 ) o f Tabl e 2-4 .
Fo r a sit e wit hdat a completenes s proportio nbetwee nj/( r + 0.5 ) an d j/( r + .05) , roundin g to.th e neares t tent hrathe r tha nt o th e neares t intege r thu s increase s th e chanc e o f misclassifyin g th e statu s o f th e sit e a s nonattainmen t i f i nfac t th e tota l numbe r o f exceedance s i s r . O nth e othe r hand , roundin g t o th e neares t tent hdecrease s th e chanc e o f mis classifyin g th e statu s a s attainmen t i f th e tota l numbe r o f exceedance s i s actuall y

r+1 .

Limitin g th e Maximu m Probabilit y

o f a Typ e I Erro r
Th e effec t o f determinin g attainmen t statu s b y comparin g x - t o th e fixe d 1 ' valu e r + -p

- i s t o creat e th e regularl y space ddat a completenes s cutpoint s 2j/(2 r + 1 ) o f Tabl e 2-4 . I f P i = 2r/(2 r + 1) , th e maximu m probabilit y

c t

8314 6 3 

### 1 9

### TABL E 2-5 . Binomia l approximation s t o probabilitie s a and3 i nth e one-exceedanc e case , r = 1 .
P i interva l Binomia l Approximatio n a 3 2/ 3 < p . < 1 0 < P i < 2/ 3 0 P i 1-P i

( 1 - Pi) 1

831i+ 6 8 2 01. 0

0.6 r
0. 6 I I sz CL 0, 4

(a ) a versu s p . 1. 0

0. 3

0. 6

0. 4

0.?

-

o.o 1 ' L 1 . 0

(b ) 3 versu s Pi

8311+ 6 FIGURE . 2-1 . Binomia l approximatio nt o a an dg in the one-exceedanc e case , r = 1 .



### 2 1TABL E 2-6 . Binomia l approximation s t o probabilitie s a and3 inth e three-exceedanc e case , r = 3 .

P i Interva l Binomia l Approximatio n



### 6/7 < P i

### 1 1 - P <

P- 0 4/ 7 < p . < 6/ 7 6 Pi 2 ( 1 - Pi) 2 + 4 p . ( 1 - Pi ) 3+ ( 1 - Pi ) 4
2/ 7 < p . < 4/ 7 p. 3 + 3 Pi 2 ( 1 - Pi ) 4 P i ( 1 - Pi) 3+ ( 1 - Pi) 4
3/ N < p . < 2/ 7 1 - ( 1 - p.) " ( 1 - Pi )
P i = 2/ N 3 Pi 2 ( 1 - Pi ) + 3 P i ( 1 - Pi ) 2 ( 1 - Pi )
P i = 1/ N 3 P j ( 1 - Pj) ' ( 1 - Pj )

8 3 11+ 61. 0

o.6 r

0. 6

0. 4

0. 2

1. 0



### o. e

0.6 L 1 3

•*- >

. o 0 . 4

0. 2 (a ) a versu s p- j

0. 0 0. 0 p ,

(b ) 6 versus P

i

FIGUR E 2-2 . Binomia l approximation s t o a an d6 i n th e three-exceedanc e case , r = 3 . 8311+ 6 

### 23P.5 1



### o f a Typ e I erro r wil l be betwee n0.6 0 an d0.67 , dependin gonr . Th e poin t i s tha t b

y usin gthi s metho do f determinin gth e short-term attain men t statu s o f a sit e w e ru na hig hris ktha t th e statu s migh t be errone ousl y determine da s nonattainment . It i s possibl e t o modif y th e metho ds o tha t th e probabilit y o f a Typ e I erro r neve r exceed s a prescribe dlevel , ag , a t th e cos t o f increasin gth e probabilit y

o f a Typ e I I erro r (i nwhic ha site' s failur e t o attai nth e short-term

standar dgoe s undetected) . Th e modificatio ni s t o simpl y shif t th e dat a completenes s cutpoint s t o smalle r values , TT, , IT^ , ••• » it . whic h ar e obtaine dfrom

ag . The procedur e i s depicte dinTabl e 2-7 .
2-4 , wit h2j/(2 r + 1 ) replace db y IT. , fo r j J 

### Th e resultin gmaximum

probabilit y

o f a Typ e I erro r i s tha t give ni nTabl e

1 , 2 , ... , r . Th e maximum probability , 3 , o f a Typ e I I erro r i s als o obtaine dinthi s way from previou s expressions . Below w e demonstrat e th e derivatio no f TT Jfrom a prescribe dleve l o f risk , ag , fo r th e case s r = 1 an dr = 3 . Th e procedur e fo r th e curren t one-exceedanc e form o f a standar d( r = 1 ) i s depicte dinTabl e 2-8 . W e se e tha t a Typ e I erro r canonl y occu r i f ki = 1 , Pi < ITJ , an

dX i = 1 . Th e probabilit y o f a Typ e I erro r i s thu s zer o i f

P i > ffl . 

### I f Pi < IT . the nP r 

### (k . = l | X i 

### = 1 ) 

# V s o th e absolut e maximum (i.e. , acros s al l sites ) occur s a t Pi = TTJ . We may therefor e limi t th e ris ko f a Typ e I erro r t o a gsimpl y b y settin gI

T j
= ag . Figur e 2- 3 depict s a an d3 a s function s o f Pi whe nth e prescribe d absolut e maximum

probabilit y

o f a Typ e I erro r i s a g= 0.20 . Inth e cas e r

- 3 , k i wil l be take na t fac e valu e i f Pi > v^* i.e. , w e wil l onl y

declar e th e statu s t o be nonattinamen t i f w e observ e k ^ > 4

8311+ 6 3 

### 2 4P.5 2



### TABL E 2-7 . Attainmen t statu s a s a functio no f observe dexceedance s (ki ) an d th e proportio n(pi ) o f dat a completeness .
* 

### 0 1 1 2 2 

### o< P i

### <1

0< P i< TT

j IT j < P i< 1 0< P i< TT

2 TT o< PA < 1 Assigne d k n - P i Interva l Statu s A N A N A

r0 < p n - < ir rN rir p < P i < 1 A > r+ l 0 < p i < 1 N
A= attainment , N = nonattainmen t

TABL E 2-8
. Attainmen tstatu s fo rth e one-exceedanc e for m o fth e standar d ( r= 1 )

k iCVJOIHiHA P i Interva l

o < P i < 1 0 < P i < TT-

j Tt j < P i < 1 o < P i < 1 Assigne d Statu s A N A N

* 

### A = attainment , N

= nonattainmen t



## 2 5 8314 6 81. 0

0. 6 - i | r " i r n 1 r

0. 6 sz a 0. 4

0. 2

0 . 8 T o0. 20. 4 0. 6 0. 5 i P i (a ) a versu s p .

0 . 0 0. 2 0. 4 0. 6 P i 1 . u

0 . B

0. 6

0. 4

0. 2

n r , 

# \ i" \ 

# A ! \i

- '

-

iii i i'i '

-
\

\
\

-

i I- I i \ (b ) 3 versu s p .



### FIGUR E 2-3 . Binomia l approximatio nt o a an dB fo r r = 1 an

da specificatio no f a Q

### = 0.2 .
8311+ 6 

## 2 6P.5 4



## exceedances . Henc e ther e i s nochanc e o f a Typ e I error . I f * £ < P i < 113 , thre e observe dexceedance s ar e require dfo r a nonattainmen t determina tion , an dth e maximu

m probabilit y

o f a nincorrec t nonattainmen t determina tioni s approximatel y

p*j . Continuing , we obtai na modifie dTabl e 2- 6 wit h cutpoint s 2j/ 7 replace db y TT Jfo r j = 1 , 2 , 3 . Clos e approximation s t o th e require dn. j ar e obtaine db y solvin g

a 

### 0 -I T 3



### _2 a Q- TT 2 +3TT 2 ( 1 T T 2 ) 

## a „ = 1 - a •i) ' 

## Fo r a 0 

## = 0.20 , we obtai n ir 3 

## = 0.58 5 TT 2 

## = 0.28 7 TT J= 0.07 2 Figur e 2- 4 show s th e resultin ga and3 ,
Summary o f Result s an

dAlternativ e Approache s Indiscussin gattainment o f ai r qualit y standard s a t a

nindividua l sit e durin ga specifie dyea r (or othe r attainment period) , we have adopte dth e view tha t a complet e se t o f measure dambien t concentration s at th e sit e for th e yea r woul dunambiguousl y defin e the statu s o f th e sit e t ob e eithe r tha t o f attainmen t o r nonattainment . We have als oadopte dth e view that , howeve r incomplet e the dat a may be , w e mus t com

e t oa decisio n regardin gwhether , onth e basi s o f a partia l se t o f observations , th e statu s appear s t obe eithe r tha t o f attainmen t o r nonattainment , i.e. , w e hav e exclude da

n"indeterminate " status . Rathe r tha nprescribin ga dat a
8311+ 6 3 

## 2 71. 0

0. B

0. 5

D J 0 . 4

0 . 2 (a ) a versu s p .

0 . n1 1 1 1 1 . " <

(b ) 3 versu s p .

FIGURE 2-4 . Binomia l approximatio n t o a an d 3 fo r r = 3 an

d a specificatio n o f a n= 0.2 . 8311+ 6 

### 2 8

# o P.5 6



## 0



# o completenes s threshhold , pg , abov e whic hwe may reliabl y

asssig nattain men t status , we hav e addresse dth e chanc e o f comin gt o a nerroneou s decisio na s a functio no f th e dat a completenes s proportion , Pi , whateve r i t may be . Moreover , we have focuse do nsituation s i

nwhic hth e tota l numbe r o f exceedance s (x. ) i s jus t withi nor jus t abov e tha t prescribe db y th e standard , i.e. , situation s i nwhic hth e chanc e o f misjudgin gth e attainmen t statu s i s greatest .



## O

O

0 Withi nthi s context , we examine dthre e procedure s fo r judgin gattainmen t

status : (1 ) base dsolel y o nth e observe dnumbe r o f exceedances , k ^ (2 ) base dsolel y

o nth e estimate dnumbe r o f exceedances , X i = k./p. ; an d(3 ) base do nbot hk

i andth e dat a completenes s proportion , Pi . I nth e firs t procedur e ther e i s no possibilit y o f a Typ e I error , i nwhic hth e statu s i s erroneousl y

determine dt o be tha t o f nonattainment . I nth e second procedur e th e maximu

m probability , a , o f a Typ e I erro r i s greate r tha n 0.6 , bu t th e probability , 3 , o f a Typ e I I error , i nwhic hth e statu s i s erroneousl y

determine dt o be tha t o f attainment , i s reduce dfo r moderat e dat a completenes s porportions . I nth e thir dprocedur e a i s limite dt o a preassigne dleve l a ga t th e cos t o f increasin g3 .



## O

G The Typ e I/Typ e I I erro r analysi s doe s no t giv e a definitiv e answe r

regardin gwhic ho f th e thre e procedure s i s preferable , becaus e thi s depend s o

nth e prioritie s o f th e decisionmaker . Fo r example , i f a Typ e I erro r i s t o b e completel y avoided , th e firs t procedur e i s preferable . It i s hope dtha t th e analysi s wil l nevertheles s b e usefu l inconsiderin gth e interpla y

betwee nth e proportio no f dat a completenes s an dth e likelihoo d o f a nerroneou s attainmen t determination .



## G

® Frankan dCurra n(1982 ) presen t a simila r analysi s inth e cas e o f particu lat e matter , whic hi s typicall y sample donc e ever y

si xdays . Thei r result s correspon dt o thos e w e hav e obtaine d(althoughthe y explicitl y trea t a five-exceedances-per-year , three-yea r standard , whic hwe trea t onl y implicitl y

inTabl e 2-4 , settin gr = 15) . Moreover , th e theoretica l probabilitie s the y

calculat e correspon dt o thos e the y obtaine dempiricall y



## C D 8311+ 6 3 

## 2 9fro m a subse t o f site s havin gnearl y complet e data . Thei r stud y empha size s a compariso no f th e firs t two procedures , base do nk i an d Xi , respectively . The y show tha t whe nth e numbe r o f exceedance s i s wel l abov e th e numbe r (r ) allowe dinth e standard , ou r enhance dabilit y t o detec t nonattainmen t usin gth e secondprocedur e i s eve ngreate r tha ntha t show nb y th e presen t worst-cas e analysi s (i nwhic hX i = r + 1) .
A differen t for

m o f theoretica l analysi s i s presente db y Davidso nan

d Hopk e (1983) . Th e author s construc t a probabilit y distributio no f pollutan t concentration s at a give nsit e havin ga characteristi c concen tration , c , tha t i s exceede do naverag e onc e pe r year . The y defin e th e statu s o f a sit e a s "attainment " i f c i s a t o r below th e standard ; otherwis e i t i s "nonattainment. "
It shoul dbe note dtha t theoretica l analysi s o f th e mos t sensitiv e scenario s i s no t th e onl y possibl e way

t o view

th e interpla y

betwee ndat a completenes s andprocedure s fo r inferrin gattainmen t status . A nalterna tiv e i s t o empiricall y estimat e th e probabilit y o f misclassifyin ga sit e wit ha give nproportio no f dat a completeness . Thi s approac hi s discusse d inSectio n3 . Ther e ar e othe r procedure s fo r determinin gattainment . Breiman , Gins , an d Ston e (1978 ) substantiall y ameliorat e th e effect s o f incomplet e dat a usin g a differen t estimate , X i s o f th e actua l numbe r o f exceedances , \j. Thei r approac hi s t o fi t anexponentia l distributio nt o th e highes t 2 0 percen t observe dconcentration s an dt o us e thi s fitte dtai l exponentia l distribu tio nt o estimat e th e expecte dnumbe r o f exceedance s amon gth e missin g concentration s (als o se e Breima nan dStone , 1983) . I t migh t prov e worthwhil e t o includ e a procedur e base do nX i i nfutur e investigation s o f th e effect s o f incomplet e dat a onth e chanc e o f misclassification .

8311+ 6 3 3 0EMPIRICA L ESTIMATIO N OF TH E PROBABILIT YOF MISCLASSIFYIN GATTAINMEN T STATU S

LONG-TERM

AMBIEN T STANDARD S Usin gth e statistica l framewor kintroduce dinSectio n2 , we conside r th e ithsit e t o hav e attaine da long-term ambien t standar di f th e averag e o f a complet e se t o f concentrations , p i s doe s no t excee dth e referenc e concentration , C^^gg . Typically , a complet e se t o f concentration s i s no t recorded , i.e. , th e dat a completenes s proportio n(Pi ) i s les s tha nunity , s o tha t th e average«o f th e recorde dconcentration s (p. ) i s use dinstea do f P i t o classif y

th e sit e a s attainmen t o r nonattainment .
I f Pi i s les s tha nunit y an dth e sit e ha s infac t attaine dth e standard , ther e i s a chance , denote db y a* , tha t th e sit e wil l be misclassifie da s nonattainment . Similarly , i f th e sit e ha s i nfac t faile dt o attai nth e standard , ther e i s some chance , 3i , tha t th e sit e wil l be misclassifie da s attainment . Usin gth e approximat e normalit y o f \x- discusse dinSectio n2 , i f * i < C NAAQ S w e hav e

a i = P r(y i > C NAAQS}



### * 1 ' N P i 

### ,1/2 'NAAQ S M i

= * N p i \

^ i ' C

NAAQ S 

### 1 l

8311+ 6 1 0 

### 3 1

## an

di f u i > CNAAQ S w e hav e



## * 1 = P r 

## K K

C 

## NAAQS }

'l»MAAnC ~ \-

i



## Settin g 

# -[(A r

Np, - \ 1/ 2 

## in- C

NAAQ S M 

## i a. 

## NAAQ S

C 

## i = 

## \ 1 - P i 

## i "NAAQ S wher e a- i s th e standar ddeviatio no f th e recorde dconcentrations , we ma y estimat e O i and3 . a s

« i = $(? 

## i } i f y 

## i * SAAQ S

* i = 

## * ( _ 

## « 1 ) i f u 

## i > C 

## NAAQ S

W e the nestimat e a(p 0 

## ) and3(p Q 

## ) , th e probabilit y o f misclassifyin ga sit e whos e actua l statu s i s attainmen t an dnonattainment , respectively , a s
a(p Q 

## ) = averag e Oi , p^ > P Q

## and^ < C NAAQ S 3(p 0 

## ) = averag e i v 

## p . >.p Q

## andM 

## . > C NAAQ S

8311+ 6 1 0 

## 3 2P.6 0

The calculatio no f a(pg ) and3(p Q ) require s tha t eac hsit e b e tentativel y classifie da s attainmen t o r nonattainmen t base donu^ prio r t o th e calculatio no f a. : o r 3. . Thi s tentativ e classificatio nmay b e erroneou s fo r a give nsite , particularl y i f ^ i i s nea r C NAA Q S , bu t averagin gove r a larg e numbe r o f site s produce s estimate s a(p Q ) , 3(P 0 ) whos e reliabilit y i s muc hgreate r tha nth e correspondin gestimates , O i o r 3. , a t a give nsite . Tabl e 3- 1 summarize s th e result s o f thes e calculation s fo r sulfu r dioxide , nitroge ndioxide , lead , andtota l suspende dparticulat e matter . I nsom e case s no estimat e i s give nbecaus e th e numbe r o f site s i s insufficien t fo r reliabl e estimation . Inth e case s wher e reliabl e estimatio ni s possible , we se e tha t a(pg ) ande(po ) ar e les s tha non e percent . Fo r sulfu r dioxid e andnitroge ndioxide , dat a completenes s requirement s o f 50 , 75 , and9 5 percen t wer e examined . Fo r lea dandtota l suspende dparticulate , whic h ar e typicall y

monitore donc e pe r si xdays , w e examine ddat a completenes s requirement s o f 5 percen t (correspondin gt o th e curren t requiremen t o f fiv e recorde dconcentration s pe r quarter) , 1 2 percen t (whic hmay be interprete da s requirin ga 7 5 percen t dat a recover y fro m a onc e pe r si x day samplin gschedule) , an d2 5 percen t (7 5 percen t recovery fro m a onc e pe r 3 day

samplin gschedule) . Whe ninterpretin gTabl e 3- 1 i t i s importan t t o distinguis hbetwee nrate s o f misclassificatio ntha t ar e possibl e unde r variou s dat a completenes s requirement s an

drate s tha t ar e estimate dfro m 198 1 data . Th

e distinctio n i s especiall y

importan t fo r leadan dparticulat e matte r sinc e thei r once per-six-da y

samplin g schedule s limi t th e dat a completenes s proportio nt o one-sixth . Figure s 3- 1 throug h3- 3 illustrat e thi s poin t for , respectively , th e quarterl y

leadstandard , th e annua l TS P standar d(base donth e annua l geometri c mea nconcentration) , an da hypothetica l TS P standar dbase don th e annua l arithmeti c mea nconcentration . The las t figur e i s include d becaus e anannua l particulat e (P M 10 ) standar dbase do nanarithmeti c mea n i s currentl y

unde r consideration .
Eachfigur e consist s o f a se t o f curves , a se t o f plotte dpoints , anda ba r chart . Eachcurv e show s possibl e misclassificatio nprobabilitie s fo r
831i+6 r 1 0 

### 33P.6 1

TABL E 3-1 . Estimate dprobabilit y tha t a site' s attainmen t statu s fo r long term standard s i s misclassifie da s a functio no f minimu m dat a completenes s proportion , pg . The tabl e entrie s ar e th e estimate dpercentage s o f attain men t site s (A ) meetin ga give ndat a completenes s requirement , p 0 , likel y t o b e misjudge da s nonattainment , o r th e percentag e o f nonattainmen t site s (N ) likel y t o b e misjudge da s attainment . N o estimat e i s mad e i f th e numbe r o f site s i s insufficient . (Note : ther e ar e no know nspecifi c instance s o f misclassifie dsites--se e tex t fo r a discussio no f th e estimatio nprocedure. )
S0 2 (annual) : 89 1 site s

A (99%) c N (1% ) Assigne dStatu s Actua l p 0 = .5 0 (85% V Statu s A

N < 1% C p 0 = .7 5 (71% )

A N < 1 % p 0 = .95 D(8% )

A N < 1 %

N 0 2 (annual) : 32 4 site s

Actua l Statu s A(97% ) N (3% ) p 0 = .5 0 (78% )

AN < 1 % p 0 = .7 5 (54% ) p 0 = .9 5 (8% )

A N A N < 1 % < 1 %
Pb (maximu m quarterly) : 69 6 site s

Actua l p 0 = .0 5 (61% ) Statu s AN A(97% ) N (3% ) < 1 % p 0 = .1 2 (39% ) p 0 = .2 5 (1% ) A N AN ' < 1 %
TS P (annual) : 365 4 site s

Actua l p 0 = .0 5 (92%) e Statu s AN A(87% ) N (13% ) 2 % 9% 1 p 0 = .1 2 (77% ) p 0 = .2 5 (6% )

A . N A N 2 % 8 % < 1 %

3 % Note s o nnex t page .

831i+6 r 8 

### 3 4P.6 2

Note s fo r Tabl e 3- 1

Th e numbe r inparenthese s i s th e percentag e o f site s meetin gth e require d dat a completenes s proportion , pg . B y 0.9 5 th e valu e y^- = 0.952 4 i s meant . The numbe r inparenthese s i s th e estimate dpercentag e o f site s tha t hav e attaine dor faile dt o attai nth e standard . Estimate s ar e base do nreporte d long-term

averages . Thi s i s th e estimate da-probabilit y tha t a sit e inattainmen t an dmeetin g th e dat a completenes s proportio np 0 = 0. 5 woul dbe misjudge d a s nonattainment . Thi s entr y ca nals o b e interprete da s a nestimat e o f th e percentag e o f suc hsite s expecte dt o be misclassified . Not e tha t intermitten t monitorin ginitsel f result s inles s tha ncomplet e data . Th

e dat a completenes s requirement s o f 0.05 , 0.12 , an d0.2 5 correspon d approximatel y

t o fiv e recorde d24-hou r measurement s pe r quarter , an d7 5 percen t dat a recovery fro m once-per-six-da y

an donce-per-three-da y samplin g schedules , respectively . Thi s i s th e estimate d3-probabilit y tha t a sit e no t inattainmen t o f th e standar dan

dmeetin gdat a completenes s proportio np g = 0.0 5 woul db e misjudge da s attainment . Alternatively , we ca ninterpre t thi s entr y a s a n estimat e o f th e percentag e o f suc hsite s expecte dt o be misclassified .

831i+6 r 8 

### 3 5P.6 3

(A ) f n = 1/18 , N = 91 ; (1/18 ) < = p . < (1/12) , 5 0 site s

U . I B . E.5 : 5. A 

## s E 

## - 5 

## -

" S B.4 - U? c ] r - *. B.2 ; o

~ 0. 1 

# r E. E o £-e . e.- 3 o/ y= 0.3 6 (IO J tile ) J o/ y•0.5 9 (50 % tile ) ' o/. w« 0.9 3 (90 % tile )

: . ^

o E. 5

E. 4 E. S - E. 2 E . : e . 7 AH- : (B ) f n = 1/12 , N = 91 ; (1/12 ) < = p . < (1/8) , 8 6 sites
.

U IE . o/ y = 0.3 6 (10 % tile )
_ ' alx. = 0.5 9 (50 % tile ) \ o/ y = 0.9 3 (90 % tile ) ~



## J i 

# i

E. 3 i . 2 2 . 4 3 . 3 (C ) p Q = 1/8 , N

= 91 ; (1/8 ) < = p . < = (1/6) , 18 0 sites
. E
. E . 5
e . 4 : - o/ y= 0.3 6 (10 % tile ) - j o/ y= 0.5 9 (50 % tile ) ! o/ y= 0.9 3 (90 % tile ) - I

> > £ 0. 1

. 0 0. 0 -SSS T O ^•i , r. 0
. 0 1 . 2 Figur e 3-1 . Lead : th e probabilit y o f misjudgin g actua l attainmen t statu s a s determine db

y th e mea n(y) , th e coefficien t o f variatio n{o/v), an dth e proportio no f dat a completenes s (p) . Continuou s curve s show probabilitie s determine db

y fixe dcombination s o f pan do/\i, wherea s th e plotte dpoint s ar e determine db

y combination s obtaine dfro m 198 1 data . 

### 3 5(A ) p Q = 1/18 , N = 365 ; (1/18 ) < = p . < (1/12) , 19 9 sites
. %

g 0. 6 S B. 5

* 0
. 4 ms S 0. 3 %B. 2 Percen t06 s se . I

" S 0. 0 o 

## -••J . 30. 0 l n og/l n y g = 0.0 8 (10 % tile ) l n og/l n y g = 0.1 0 (50 % tile ) l n og/l n y g = 0.1 5 (90 % tile )

_ L 60. 0 90. 0 _ L 120. 0 150. 0 (B ) p Q = 1/12 , N = 365 ; (1/12 ) < = p i < (1/8) , 43 2 sites
. g 0- 6 Percen tDb s se . S 0. 5
mm « 0. 4 - t n a 0- 3

» - 0. 2 - o > > £ 0 . I o 0 . 0

° - -0
. 0 . 0 I 30. 0 mmH*m& I I n og/l n y g = 0.0 8 (10 % tile )

I n og/l n y g = 0.1 0 (50 % tile ) l n o g /ln'y g = 0.1 5 (90 % tile )

t,'":i<<"" K* MX X

_ L 60. 0 90. 0 120. 0 150. 0 "SPMt P

(C ) p n= 1/8 , N= 365 ; (1/8 ) < = p . < = (1/6) , 212 5 sites ,
c0- 6 o Percen tDDs 5B
. I n og/l n y g = 0.0 8 (10 % tile ) - l n og/l n y g = 0.1 0 (50 % tile)
_ I n og/l n y g = 0.1 5 (90 % tile )

•aKOs-^WB^seot;—

* ac t 120. 0 150. 0 

### Figur e 3-2 . TSP , annua l geometri c mean : th e probabilit y o f misjudgin g actua l attainmen t statu s a s determine db y th e natura l lo g o f th e geometri c mea n(y g 

### ) . th e coefficien t o f variatio n(l na g 

### /l ny g 

### ) , an dth e proportio n o f dat a completenes s (p) . Continuou s curve s show probabilitie s determine d b y fixe dcombination s o f pand(I nOg/l nyg) , wherea s th e plotte dpoint s ar e determine db

y combination s obtaine dTro m ly8 1 data . 3 7

### (A) p Q

### = 1/18 , N = 365 ; (1/18 ) < = p . < (1/12) , 19 9 site s Percen t 00 9 SE
.

30. 0 60. 0 90. 0 120. 0 150. 0 

### (B ) p Q

### = 1/12 , N= 365 ; (1/12 ) < = p i

### < (1/8) , 43 2 sites , g0- 6 | Percen t Obs 5B . 0.5

- < « 0.4

-

o 0 . 3

0 . 0 o ° - -0 . 0 . 0 30. 0 o/y= 0.3 2 (10 % tile ) o/y= 0.4 2 (50% tile ) o/ y= 0.6 1 (90

% tile )

60. 0 90. 0 xvx xw. jftfe&^MMfafe.—; c
120. 0 150. 0
(C ) pf 

# I B

# 6 S 0. 5 1/8 , N = 365 ; (1/8 ) < = P i < (1/6) , 212 5 sites , Percen t Ob s 5B .

;-<M . i ? 60. 0 90. 0 120. 0 150. 0 IBB . 1 I
il l 1 1 o/ y = 0.3 2 (10 % tile ) - o/ y = 0.4 2 (50 % tile ) o/ y - 0.6 1 (90 % tile ) 1 1

Figur e 3-3 . TSP , annua l arithmeti c mean : th e probabilit y o f misjudgin g actua l attainmen t statu s a s determine db y th e mea n(y) , th e coefficien t o f variatio n(o/y) , an dth e proportio no f dat a completenes s (p) . Continuou s curve s show

probabilitie s determine db y fixe dcombination s o f pan do/y , wherea s th e plotte dpoint s ar e determine db y combination s obtaine dfro m 198 1 data . 

### 38P.6 6

a rang e o f mea nconcentration s b y combinin ga give ndat a completenes s proportio n(1/18 , 1/12 , o r 1/8 ) wit ha give ncoefficien t o f variatio n (obtaine dfro

m th e 10th , 50th , o r 90t hpercentil e o f th e 198 1 distribu tion) . Th

e give ndat a completenes s proportion s approximatel y correspon d t o 5 , 8 , an

d1 2 sample s pe r quarter , respectively . The las t proportion , 1/8 , may

als o be interprete da s a 7 5 percen t dat a recovery rat e fro

m a once-per-six-da y

samplin g schedule . The plotte dpoint s ineac hfigur e represen t site s whos e dat a completenes s proportion s fal l wit ha specifie dinterval . Part s (A) , (B) , an d(C ) o f eac hfigur e represen t completenes s interval s o f 1/1 8 t o 1/12 , 1/1 2 t o 1/8 , an d1/ 8 t o 1/6 , respectively . Fo r eac hsit e th e estimate dmisclassifica tio nprobabilit y

(inpar t determine db y th e coefficien t o f variatio n reporte dfo r tha t site ) i s plotte dagains t th e reporte dmea nconcentra tion . Withi neac hdat a completenes s interva l th e ba r char t show s th e percentage s o f site s havin ga give nprobabilit y o f misclassification . The figure s sho

w tha t th e dat a completenes s requirement s b y themselve s d o no t limi t probabilitie s o f misclassification . It canbe seen , however , tha t fo r th e grea t majorit y o f 198 1 sites , reporte dmea nvalue s ar e sufficientl y

fa r abov e o r below th e standar dan

dcoefficient s o f variatio n ar e sufficientl y

smal l s o tha t th e estimate dprobabilitie s ar e effectivel y zero . Thus , misclassification s ar e no t rule dou t b y thes e dat a complete nes s requirement s bu t the y ar e unlikely , assumin gtha t th e mean s an d coefficient s o f variatio nreporte di n198 1 ar e representativ e o f othe r years .
We canals o us e th e figure s t o infe r th e benefit s o f requirin g1 2 rathe r tha n5 sample s pe r quarte r fro m intermitten t samplers . Inth e cas e o f lea dwe ar e assessin gth e benefit s o f curren t requirement s sinc e 1 2 sample s pe r quarte r ar e require dt o determin e attainmen t statu s (se e Tabl e G-l) . The ba r chart s o f part s (A ) and(C ) o f Figur e 3- 1 show tha t th e two group s o f site s hav e nearl y th e same lo

w susceptibilit y

t o misclassifica tion . The curve s distinguis hpart s (A ) and(C ) mor e clearly , however , and ar e probabl y

mor e indicativ e o f th e futur e consequence s o f strengthenin g
83146 r 1 0 3 9o r relaxin gdat a requirement s fo r al l sites . We ca nexpres s thi s differ enc e b y comparin g"critica l concentratio nintervals, " i.e. , b y notin gth e interva l o f maximum quarterl y

mea nconcentration s withi nwhic hth e probabilit y

o f misclassificatio nexceed s 0.1 0 fo r a sit e havin ga typica l (i.e. , median ) coefficien t o f variation . Thi s definitio no f a "critica l interval " bear s some explanation . We ar e intereste dincorrectl y classifyin gth e attainmen t statu s o f a sit e whos e actua l long-term

averag e concentration , y , i s estimate db y y base don incomplet e data . Fo r simplicity , we assum e th e coefficien t o f variation , o/v, t o b e th e media no f th e coefficient s o f variatio ncalculate dfo r ou r sampl e o f sites . I f y i s ver y

clos e t o th e referenc e concentration , ^NAAQS ' the nuwil l be abov e o r below C NAA Q 5 wit hnearl y equa l proba bility . Therefore , i f y i s onl y

slightl y

abov e o r below CN A A Q $ , th e ris k o f misclassificatio nwil l be clos e t o 5 0 percent . A s y move s away

from ^NAAQS » t ^ 1 e probabilit y o f misclassificatio ndecrease s until , a t some poin t abov e an

dbelow C^ A A Q5 , th e probabilit y drop s below

1 0 percent . Th e critica l interva l i s thu s th e se t o f y fo r whic hattainmen t determination s ar e subjec t t o erro r wit hnonnegligibl e probability .
Inmathematica l notatio nw e defin e th e critica l interva l a s th e unio no f interval s A

an dB wher e
1 M : p< C NAAQ S an dPr y ( p> C NAAQS ) > a*

B = { y : y > C NAAQ S an d Pr u ( y< C NAAQS ) > a j

s o tha tth e critica l interva l i s

A U B = { y: a < Pr^y " > C NAAQ$ ) < 1 - a }
.
I nth e framewor ko f testin gth e statistica l hypothesi s tha t y < ^N A A n s base dony , th e critica l interva l i s th e se t o f y fo r whic hth e powe r o f



### 83m6 r i o 

### 4 0

# o P.6 8



### O



# o

o

o th e test , i.e. , th e probabilit y tha t y

exceed s C NAA g $ , i s betwee n a and1 - a , i.e. , settin ga equa l t o 0.1 , betwee n1 0 an d9 0 percent .
W e may als o describ e th e critica l interva l a s th e interva l withi nwhic h th e probabilitie s o f apparen t attainmen t an dnonattainmen t (basedo na compariso no f y

an dCw A A ge ) ar e bot hbetwee n1 0 and9 0 percent . It i s thu s a ninterva l withi nwhic hth e determinatio no f attainmen t statu s i s unreliable . W

e may therefor e us e critica l interval s t o judg e the adequac y o f completenes s requirements--th e mor e stringen t th e requirement , th e narrowe r th e critica l interval . Th e critica l interva l fo r a sit e recordin gonl y fiv e vali dleadsample s pe r quarte r i s 1.1 3 t o 2.2 3 yg/ m (2 5 percen t below t o 4 9 percen t abov e th e standar do f 1. 5 yg/m 3 ) , wherea s th e interva l narrow s t o 1.2 4 t o 1.9 0 yg/ m (1 7 percen t below t o 2 7 percen t abov e th e standard ) fo r a sit e tha t record s 1 2 vali dsample s pe r quarter . 

### O

O

O

O

O Figure s 3- 1 and3- 2 suppor t simila r conclusion s regardin gTS P long-term

standards . Sinc e long-term averag e concentration s ar e wel l below th e standar da t mos t sites , th e benefit s o f 1 2 versu s fiv e sample s pe r quarte r ar e cleare r fro

m th e curve s depictin gpossibl e misclassificatio n probabilitie s tha nb y a direc t compariso no f site s wit hdifferen t propor tion s o f dat a completeness . W e conside r tw

o form s o f annua l TS P standard , bot hhavin ga referenc e concentratio no f 7 5 yg/ m , namely , th e curren t standar dbase donth e geometri c mea nanda hypothetica l standar dbase don anarithmeti c mea n(the latte r i s relevan t t o th e recentl y propose dPM-1 0 standard) . Fo r th e curren t standard , th e critica l interva l fo r th e cas e o f fiv e vali dsample s pe r quarte r i s 6 7 t o 8 5 yg/ m (1 1 percen t below t o 1 3 percen t abov e th e standard) , whic hnarrow s t o 7 0 t o 8 1 yg/n r ( 7 percen t below t o 8 percen t abov e th e standard ) fo r th e cas e o f 1 2 vali dsample s pe r quarter . Thes e result s ar e th e same (t o two-digi t accuracy ) fo r th e hypothetica l standar dconcentratio nrepresente dinFigur e 3-3 .
I t i s instructiv e t o compar e th e case s o f lea dan dTS P represente db y Figure s 3- 1 an

d3-2 , respectively . Th e probabilit y o f misclassificatio n i s determine dno t solel y b y th e proportio no f dat a completeness , bu t als o 

### O 831i+6 r i o 

### 4 1P.6 9 O
b

yth e numbe ro fvali d observation s t o be use d i n judgin g attainment
. Q Fo rexample , 5. 5 percen tcomplet e dat a yield s 2 0 observation s wit h

whic h t o judg e attainmen to fa n annua l standard , bu tonl yfiv e observation s fo rassessin g th e attainmen to fa quarterl ystandard
. Therefore , a give n numbe ro flea d sample s pe rquarte rwit h whic h t o judg e Q attainmen to fth e quarterl ylea d standar d lead s t o highe r

misclassificatio n probabilitie s tha n th e same numbe ro fTSP sample s pe r quarte r(i,e. , fou rtime s tha tnumbe rpe ryear ) wit h whic h t o judg e attainmen to fth e annua l TSP standard , othe rfactor s bein g equal
. Thus , Q th e critica l interva l correspondin g t o th e 1 2 lea d sample s pe rquarte r

require d fo rattainmen tdetermination s i s relativel ywide r(1 7 percen t belo wt o 2 6 percen tabov e th e quarterl ylea d standard ) tha n th e interva l correspondin g t o th e require d 5 TSP sample s pe rquarte r(1 0 percen tbelo w O t o 1 3 percen tabov e th e annua l TSP standard)
.

Therefore , i fou rgoa l wer e t o contai n th e 0.1 0 probabilit ycritica l interva l within , say , + 1 0 percen to fth e standard , the n th e requiremen t Q o ffiv e TSP sample s pe rquarte rnearl yachieve s th e goa l wherea s th e

requiremen to f1 2 lea d sample s pe rquarte rdoe s not
. Thi s suggest s tha t an ytightenin g o fcurren tdat a completenes s requirement s t o improv e attainmen tassessment s o flong-ter m standard s shoul d begi n wit h lead,
. O O

n th e othe rhand , i fou rgoa l wer e t o restric tth e fractio n o fsite s vulnerabl e t o misclassification , e,g. , site s fo rwhic h th e misclassifica tio n probabilit yexceed s 0,10 , i tappear s fro m th e 198 1 dat a tha tan y O tightenin g o fcompletenes s requirement s shoul d be directe d a tTSP rathe r

tha n lead , sinc e th e observe d fractio n o f"vulnerable " site s i s greate r fo rTSP tha n fo rlead
. Thi s differenc e betwee n TSP an d lea d ma ybe solel y a consequenc e o fth e smalle rsampl e o flea d sites , however , O Th e two goal s thu s lea d t o differen tconclusion s abou twhic h pollutant ,

lea d o rTSP , warrant s th e mos tconsideratio n fo rstrengthene d dat a completenes s requirements
. Sinc e th e "critica l interval " analysi s seem s O t o b e more reliabl e tha n th e "vulnerabl e sites " analysis , i tseem s tha t

requirement s fo rlea d warran tfirs tconsideration
. Thi s i s especiall ys o sinc e strengthe d requirement s fo rparticulate s hav e alread ybee n O 83ii+6 ri o 4 2

# o P.7 0



## O considered ; propose drevision s t o the particulat e NAAQ S includ e a

requiremen t o f 1 2 vali dobservation s pe r quarte r (EPA , 1984) .



## : o

O

G Th e recommendatio n tha tstrengthene d completenes s requirement s be con sidere d fo rlea d i s offere d onl yas a poin to fdeparture , however , sinc e realisti crecommendation s mus tinclud e man ypractica l consideration s outsid e th e scop e o fou ranalysis
. Fo rexample , w e hav e no tattempte d t o distinguis h i n genera l betwee n dat a completenes s proportion s resultin g fro m goo d dat a recover yfro m intermitten tsampling , o n th e on e hand , versu s poo rdat a recover yfro m continuou s samplin g o n th e other
. Th e latte rcas e ma

yb e indicativ e o fgenerall yunreliabl e data
. Pendin g a more comprehensiv e revie wo fdat a completenes s requirements , however , th e result s presente d i n Tabl e 3- 1 an d Figure s 3- 1 throug h 3- 3 shoul d b e usefu l becaus e the ysho wtha tcurren trequirement s ar e adequat e t o rende r reliabl e determination s o fth e attainmen to flong-ter m standard s a tal l bu ta smal l fractio n o fsites
. G SHORT-TER M AMBIEN

TSTANDARD

S

O

G

G

G Correctl yclassifyin g th e short-ter m attainmen tstatu s o fa sit e havin g a

certai n dat a completenes s proportio n i s muc h more difficul ttha n classify - in g th e long-ter m attainmen tstatus
. Tha tis , th e estimate d long-ter m averag e i s a more stabl e statisti ctha n th e observe d numbe ro fshort-ter m exceedance s o rth e estimate d tota l numbe ro fexceedances
. Becaus e o f this , i ti s no tpossibl e t o reliabl yestimat e th e chanc e o fmisclassifyin g th e statu s o fmos tsites
. W e can , however , estimat e th e averag e chanc e o f misclassifyin g site s whos e proportio n o fdat a completenes s meet s a require d proportion
. Thi s ca n be don e i fw e mak e th e reasonabl e assumptio n tha tth e actua l numbe ro fshort-ter m exceedance s (X. ) an d th e dat a completenes s proportio n (Pi ) ar e statisticall yindependent
. Tha tis , w e ma yus e a n estimat e o f th e tota l numbe ro fexceedance s a teac h sit e t o estimat e th e statistica l distributio n o fshort-ter m exceedance s acros s al l sites
. W e the n appl y 831<+6 ri o 4 3 GP.7 1



### thi s statistica l distributio nt o thos e site s havin gdat a completenes s proportions , Pi , nea r a give nproportion , p , an dthereby

estimat e th e fractio no f thes e site s havin ga give nnumbe r o f exceedance s ( x= 0 , 1 , 2 , ...) . Fo r a one-exceedanc e standar d(fo r whic hr = 1 in th e notatio no f Sectio n2) , we may therefor e estimat e th e probabilit y o f misclassifie dattainmen t an dnonattainmen t sites , respectively , a and3 , r r 

### associate d wit h a give n proportio n o fdat a completeness
. Th e estimate s o f a an d 3 ar e

a p 

### = Pr(x i 

### >

1.05 | p i 

### = p , X i = 1 ) Pr(x i 

### = 1 | X i < 1 )

= p-Pr(x i 

### = 1 | x i 

### < 1) , i fp <Y-^ -

° ' 1f 

### P > 

### T^5 '
an d X



### ma x 3 p 

### = E Pr 

### ( x 

### i < i- 0 5 

### I P i = P
. * i = 

### * ) Pr 

### U - j = X| X
. > 2 ) X - ^

^ X\ « ''1 

### = E d - P

) Pr(x
. = x| x . > 2) , i fp < T 

### ± E A ~ £- 

### ma x\ \ * 1
= E C U " P

) + 

### *P d " P

) ] p 

### ^(X i = x| x n 

### . > 2) , i fp >

y-i ^
W e the nestimat e a(p Q 

### ) an d3(p Q 

### ) a s AA 

### a(p 0 

### ) = averag e a p

### , ' p 1 

### > p Q

AA 

### 3(p 0 

### ) = averag e 3 p

### , Pi > P 0


### I nestimatin gth e statistica l distributio no f th e tota l numbe r o f exceed ances , instea do f usin gXi = k./p - we us e X- , obtaine db y fittin gan 83ii+6 r 1 0 

### 4 4

### exponentia l distributio nt o th e uppe r 1 0 percen t o f th e distributio no f

concentration s a t a sit e (the exponentia l tai l i s fitte dusin gavailabl e statistics—th e 90t hpercentil e andth e maximum concentration) . Thi s i s A 

### don e t o avoi da certai nlumpines s i nth e distributio no f Xi (e.g. , th e minimu m positiv e estimat e obtaine dfro m a onc e pe r si xday

samplin g schedul e i s 6) , an

dresult s ina large r estimat e insevera l cases . Th e formul a fo r xi s

X= k+ ( N

- n+ 1)( 1 - Y ) 

### exp r/C

## NAAQ S " V l n ma x 1 - y
wher e we have suppresse dth e inde xi fo r eas e o f notatio nandwher e k= N = n= * Y=
x ^ = " Y <

### ma x n th e numbe r o f recorde dexceedance s th e numbe r o f observation s ina complet e dat a se t th e numbe r o f recorde dconcentration s 0.9 , correspondin gt o th e us e o f th e uppe r 1 0 percen t o f th e concentratio ndistributio n x 

### 0.9 » th e 

### ^ t h

### percentil e o f th e concentratio ndistributio n th e maximu

m recorde dconcentratio n n/( n+ 1 ) Provisio ni s mad e inth e calculatio no f Xfo r case s inwhic heithe r x> " Y C 

### NAAQ S o r x 

### ma x= x

### * I n

### thes e case s xwa s se t equa l t o x= k/p . It shoul dals o b e note dtha t xi s rounde dt o th e neares t intege r t o estimat e th e statistica l distributio no f th e tota l numbe r o f exceedance s amon gal l sites . Th e result s o f thes e calculation s ar e show ninFigure s 3- 4 throug h3- 8 an d A 

### i nTabl e 3-2 . The figure s indicat e th e chanc e a tha t a sit e randoml y selecte dfro

m a groupo f attainmen t site s havin gdat a completenes s A 

### proportio npwoul dbe misclassifie da s nonattainment , o r th e chanc e 3 tha t a nonattainmen t sit e woul dbe misclassified . I ncontras t t o th e mos t sensitiv e scenario s treate di nSectio n2 , Figure s 3- 4 throug h3- 8 indicat e 83146 T 1 0 

### 4 5

### (a ) a versu s p

0.0 6

0.06' r
CL 0.04|

-

0.02

-



## o.c
(b ) 3 versu s p

0.0 8

0.0 6 - i i 1 r

C D n 0.0 4

0.0 2


### 0 . O J

FIGUR E 3-4 . Estimate dprobabilitie s a an d3 o f misjudgin gattainmen t o f th e 24-hou r sulfu r dioxid e standar da s function s o f dat a completenes s proportion , p . 8311+ 6 

## 4 6

### (a ) a versu s p

O.O B -

0.06 r

0.0 4

0.02 u

0.0 0 0. 2 0. 4 0. 6 0. 8 1. 0

(b ) 3 versu s 0
1 1 r

0.06 -
0.0 6

X ) 0.0 4 -
0.0 2 1

-
0. 0 1 ; 0



### FIGUR E 3-5 . Estimate dprobabilitie s a an d3 o f misjudgin gattainmen t o f th e one-hou r carbo nmonoxid e standar da s function s o f dat a completenes s proportion , p .

8311+ 6 

## 4 7

# •

0.0 8

0.06 - 

### (a ) a versu s p

- 1 1 1 1——r1 n r

ti sz D 0.0 4

0.02 -



### (b ) B versu s p

0.0 8

0.0 6

Q J 0.0 4

0.02 L

0. 0 O. S 1. 0



### FIGUR E 3-6 . Estimate dprobabilitie s a an d3 o f misjudgin gth e 8-hou r carbo nmonoxid e standar da s function s o f th e dat a completnes s proportion , p .

8311+ 6 

## 4 8P.7 6

1. 0

0. 8

0. 6 - x : Q 0. 4 -
0. 2 

### (a ) a versu s p

- i 1 1 1 1 1 r



### FIGUR E 3-7 . Estimate dprobabilitie s a and3 o f misjudgin gattainmen t o f the maximu m dail y one-hou r ozon e standar da s function s o f th e dat a completenes s proportion , p .

8311+ 6 

## 4 9

### (a ) a versu s p

0.0 8

0.0 6 o SZ' a 0.0 4

0.0 2
0 . o t - i 1 1 r - i 1 r

0.0 6 -

0.0 6 -
o X ) 0.0 4 -

0.0 2 -

0. 0



### FIGUR E 3-8 . Estimate dprobabilitie s a an d3 o f misjudgin gattainmen t o f the 24-hou r TS P standar da s function s o f th e dat a completenes s proportion , p .

8311+ 6 

## 5 0P.7 8



### TABL E 3-2 . Estimate dprobabilit y tha t a site' s attainmen t statu s fo r short ter m standard s i s misclassifie da s a functio no f minimu m dat a completenes s pro portion , pg . Th

e tabl e entrie s ar e th e estimate dpercentage s o f attain men t site s (A ) meetin ga give ndat a completenes s requirement , p 0 

### , likel y t o b e misjudge da s nonattainment , o r th e percentag e o f nonattainmen t site s (N ) likel y t o be misjudge da s attainment . No estimat e i s mad e i f th e numbe r o f site s i s insufficient . (Note : Ther e ar e no know nspecifi c instance s o f misclassifie dsites—se e tex t fo r a discussio no f th e estimatio nprocedure. )
S0 2 (2 4 hours) : 89 1 site s Assigne d Statu s

Actua l p 0 = .5 0 (85%) ' Statu s AN A (98%) c N(1% ) 2% c p 0 = .7 5 (71% ) p 0 = .95 ° (8% )

A N A N 2 % 0

%
C O ( 1 hour) : 480 , site s

Actua l Statu s A (99% ) N(1% ) p 0 = .5 0 (79% )

AN < 1 % p 0 = .7 5 (65% ) p g = .9 5 (22% )

A N A N < 1 % 0 %
C O ( 8 hours) : 48 0 site s

Actua l Statu s A(57% ) N(43% ) p 0 = .5 0 (79% )

AN 2 % < l% e p 0 = .7 5 (65% ) AN 2 % < 1 % p 0 = .9 5 (26% ) AN 0 % < 1 % O 3 (Dail ymaximu m 1-hour) : 72 3 site s

Actua l Statu s A(63% ) N (37% ) p 0 = .5 0 (86% )

AN p 0 = .7 5 (70% ) p 0 = .9 5 (16% )

A N A N 8 % 8

% < 1 % < 1 % 0 % < 1 % Continue d

831H6 T8 b lP.7 9 O

O



## o

o

o

o TABL E 3-2
. (Concluded ) TS P (24-hours) : 366 7 site s Assigne dStatu s



### Actua l p 0 

### = ,0 5 (92%) f

### p Q 

### = ,1 2 (77%

) p 0 

### = ,2 5 (6%

) Statu s A N A N A N A (79% ) 2 % 2 % 3 % N(21% ) . . 6% 6% 4 %

aThe numbe r inparenthese s i s th e percentag e o f site s meetin g th e require d dat a completenes s proportion , pg . Unde r curren t procedure s fo r determinin g th e attainmen t o f short-term standards , thi s completenes s requiremen t rule s ou t th e possibilit y o f a fals e nonattainmen t determination . bB y 0.9 5 th e valu e -—^ = 0.952 4 i s meant .

c Th e numbe r inparenthese s i s th e estimate dpercentag e o f site s tha t hav e attaine do r faile dt o attai nth e standard . Thes e estimate dpercentage s ar e base donth e tail-exponentia l metho ddiscusse dinth e text .
^ Thi s i s th e estimate da-probabilit y tha t a sit e inattainmen t an dmeetin g th e dat a completenes s proportio np 0 = 0, 5 woul db e misjudge d a s nonattainment . Thi s entr y ca nals o b e interprete da s a nestimat e o f th e percentag e o f suc hsite s expecte dto b e misclassified .

e Thi s i s th e estimate d3-probabilit y tha t a sit e no t inattainmen t o f th e ^ standar dan dmeetin g dat a completenes s proportio np g = 0. 5 woul dbe misjudge da s attainment . Alternatively , we caninterpre t thi s entr y a s an estimat e o f th e percentag e o f suc hsite s expecte dt o b e misclassified . Not e tha t intermitten t monitorin g i nitsel f result s inles s tha ncomplet e Odata . Th e dat a completenes s requirement s o f 0.05 , 0,12 , an d0,2 5 correspon d approximatel y

t o five recorde d24-hou r measurement s pe r quarter , an d7 5 percen t dat a recovery fro m once-per-six-da y

an donce-per-three-da y samplin g schedules , respectively , O

831i+6 r 8 5 2 

### OP.8 0



### tha t a and3 ar e fo r th e mos t par t wel l below 1 0 percent . Thi s i s becaus e mos t site s ar e estimate dt o hav e n o exceedances , i nwhic hcas e ther e i s no chanc e o f misclassification , an dthos e site s estimate dt o hav e mor e tha non e exceedanc e frequentl y appea r t o hav e mor e tha ntwo exceed ances . I

nshort , th e mos t difficul t case s treate dinSectio n2 appea r t o b e rar e inactuality . It shoul dbe note dtha t th e dat a ar e fro m 1981 , s o that , fo r purpose s o f comparison , ozon e i s treate da s havin gth e same one yea r one-exceedanc e form o f standar da s th e othe r pollutants . Tabl e 3- 2 show s a

napproximat e 1 o r 2 percen t probabilit y o f misclassi fyin gsulfu r dioxid e andcarbo nmonoxid e sites . The a - an d3-probabi-litie s o f misclassificatio nar e estimate dt o be 8 percen t an dles s tha n1 percent , respectively , fo r ozon e sites . Fo r particulat e site s a an d3 ar e estimate dt o b e 2 an d6 percent , respectively .

SUMMAR Y The 198 1 dat a indicat e tha t unde r curren t dat a completenes s requirements , th e rat e o f misjudgin gth e attainmen t o f eithe r long-term o r short-term standard s i s unde r 1 0 percent , andi nsevera l instance s th e estimate d misclassificatio nrat e i s unde r on e percent . Th e curren t completenes s requirement s therefor e seem t o b e adequat e fo r generall y reliabl e attain men t determinations . Thi s conclusio nshoul dbe regarde da s tentative , however , pendin gdevelopmen t o f specifi c objective s fo r limitin grate s o f misclassification .
We hav e als o conducte dwha t mus t b e regarde da s a preliminar y analysi s o f th e benefit s o f strengthene drequirement s fo r dat a completeness . In general , direc t estimate s of th e expecte dpercentage s o f misclassifie d site s reveal s virtuall y no chang e resultin gfro m th e change s inrequire ment s tha t we consider . Takin ga les s direct approac hinth e cas e o f long-term

standards , however , we hav e estimate da critica l interva l abou t th e standard , withi nwhic hmisclassificatio nprobabilitie s excee d1 0 percent , an

dw e hav e show

nho w thes e critica l interval s narrow a s mor e

8311t6 

### r 1 0 

### 5 3P.8 1



### complet e dat a ar e required . The analysi s suggest s tha t strengthene d requirement s be considere dfo r leadan dpossibl y

fo r particulate s (the recentl y propose drevision s t o th e particulat e standard s includ e suc ha strengthene drequirement) . A simila r analysi s i s possibl e fo r short-term standards , althoughth e analysi s woul drequir e some assumption s abou t th e frequenc y

distributio no f concentration s at individua l sites . Inan y case , realisti c recommendation s fo r strengthene ddat a completenes s requirement s mus t addres s th e broade r issue s concernin gdat a reliabilit y an dcost-effectiv e ai r qualit y management . Fo r example , we shoul d probabl y conside r th e benefit s o f strengthene dqualit y assuranc e proce dure s alon gwit hstrengthene ddat a completenes s requirements . Similarl y we migh t conside r whethe r mor e accurat e attainmen t determination s migh t b e achieve dunde r curren t dat a completenes s requirement s b y changin gth e form o f curren t short-term standards . W

e hav e no t attempte dt o includ e suc h issue s i nth e presen t analysis , althoug hthes e issue s certainl y deserv e futur e consideration .

831i+6 r 1 0 

## 5 4P.8 2



### STATISTICA L ESTIMATIO N OF NATIONAL AI RQUALIT YSTATU S ANDTREND S
We no w conside r th e estimatio no f nationa l average s o f site-specifi c annua l averages , y. , an dsite-specifi c exceedanc e rates , x , . W e fac e th e choic e o f a minimum

dat a completenes s proportion , pg , suc htha t onl y thos e site s in-ou r sampl e wit hp . > p n

### wil l be used.t o estimat e th e nationa l average .

A QUESTIO N

OF BIA S
Le t 1 v( 

### Po }



### . p(Pg ) = vTpg TE W- j



### an d 1 v(p 

### o }



### . X(Pg ) = v(p Q 

### ) E X 

### i

AA 

### wher e y . andx . ar e estimate s o f th e site-specifi c long-term average , M^, an dexceedanc e rate , X-, respectively , andwher e th e summatio ni s ove r site s in.th e sampl e wit hp . > p Q 

### . I f we assume tha t from sit e t o sit e th e ai r qualit y

parameter s yi and\. ar e independen t o f th e proportio np n 

### - o f dat a completeness , andi f w e regar dth e se t St o f site s inou r sampl e a s havin gbee nrandoml y

draw nfrom th e populatio no f site s o f interest , the n AA 

### fo r eac hpg , y(p Q 

### ) andx(p Q 

### ) shoul dbe unbiased , i.e. , w e shoul dhav e

A 

### E y(p Q 

### ) = y

= E( U i 

### )

8311+ 6 i

t 5 5P.8 3



## an d
E x(p Q 

### ) = X= E (x.) .

AA 

### Thi s lac ko f bia s follow s from th e unbiasednes s o f y i an dx. ,

A E U 

### i = U 

### i E x i = X i
as discusse d i n Sectio n 2
.

AA 

### Unde r thes e assumptions , y(p Q 

### ) andx(p Q 

### ) ar e approximatel y normall y distribute dunbiase destimator s o f y andx , respectively . Thus , a natura l criterio nt o us e i nselectin gp gi s th e varianc e o f thes e estimators .

VARIANC E OF TH E ESTIMATOR S

AA 

### I nChapte r 2 we obtaine dexpression s fo r th e varianc e o f y , an dx. , conditiona l o

nth e choic e o f site , i , an dthu s conditiona l ony. , x• , andp . I I A

1 Extendin g th e conditiona l varianc e t o th e average s take n ove rth e se ttrf o fsite s i n ou rsample , w e hav e 

# Var(„(pn 

# ) | fi) «- i E -s- L 

# 4 V 2 

# (P„) ft p 

# i N

an d
1 V( ' o)l " P i

Va r(x(p 0 ) |^ ) --jr-L. - E -y" 1 x . v(p Q ) 1= 1 K i

8311+ 6 i

+ 5 6P.8 4

T o obtai n th e unconditiona l variance , w e mus tallo wfo rsite-to-sit e difference s i n y . an d X-
. Thu s (see , fo rexample , Brillinger , 1966 )

Va r(y(p Q ) ) = E {va rQ(p Q ) \ $ )} + Var{E(y(p 0 ) \ fr)} 

# W . 1 - P l 

# of V( P g ) 1 = 1 H l v(p 0 ) 

## MPg ) fax



## 1

whic h ma

ybe estimate d as

AA (Pg ) Va r(M(PQ) ) = ~2

" E 

### 1 - p . a

i " i , 1 v(p 0 

### )
v(p Q 

### ) i= l N +

### 2 v'(Pg ) 1= 1



### E (l ^ - u(Pg)) '
Similarly , w

e hav e X(p 0 ) 1 " P i v(Pg ) 

## Va rU( p ) = Ej-g-^ - E -5— L 

## ^ I ? + Var 

## ]7TF T£ x 

## i 0 

## l v(p 0 

## ) 1=

1 p 

## i M r [p 

## o> 1 = 1 1
whic h ma

ybe estimate d as

AA Va r(x(p Q ) = - £ 1 ^'-p ,



## - L



## —

## E —1— -



## ^ + v(Pg ) V(Pg ) i= l H l 

### i + 

# 7 ^ S u 

# i- i(p 

# o , v

Th e varianc e expression s ar e simila rfo ry(p Q ) an d x(p Q )
. I n bot h cases , th e secon d ter m ma

ybe expecte d t o be proportiona l t o l/v(p Q ) whil e th e firs tter m depend s o n th e distributio n o fP i (a s p 0 increase s t o unity , ( 1 - Pi)/P i approache s zer o bu tl/v(p Q ) increases)
.

8311+ 6 i

+ 

## 5 7

### A N EMPIRICAL ASSESSMEN T O F TH E DATA

COMPLETENES S NEEDE DT ORELIABL YESTIMAT E NATIONAL TREND S

SULFURDIOXID E Tabl e 5- 1 an

dFigur e 5- 1 show

y(p Q 

### ) , th e estimate dcomposit e annua l averag e sulfu r dioxid e (S0£ ) concentration , an dVa r (y(p n 

### )) , it s estimate d varianc e a s discusse dinSectio n4 , fo r severa l value s o f require ddat a completenes s proportio npg . Th e estimato r y(p Q 

### ) i s fairl y constan t wit h p 0 

### , bu t it s estimate dvarianc e increase s substantiall y fo r p Q

### > 8 0 per cent , consisten t wit hth e discussio ninSectio n4 . Similarly , Tabl e 5- 2 andFigur e 5- 2 sho w a substantia l increas e i nth e A 

### estimate dvarianc e o f x(p Q 

### ) fo r p Q

### > 8 0 percent . Inaddition , Figur e 5-2 a suggest s tha t increasin gth e require dpercentage , pg , may induc e a positiv e bia s inth e estimat e o f the nationa l averag e exceedanc e rate . Th e increas e inX(p Q 

### ) accelerate s fo r p g> 8 0 percent . I nsummary , i t appear s tha t no mor e tha na n8 0 percen t dat a completenes s requiremen t shoul dbe usedt o estimat e th e nationa l statu s an dtrendin SO 2 concentrations .

CARBON MONOXID E Tabl e 5- 3 an

dFigur e 5- 3 sho

w th e estimate dexceedanc e rate , x(p n 

### ) , an d
AA*• * 

### it s estimate dvariance , Va r (x(p Q 

### )) , fo r hourl y average dcarbo nmonoxid e (CO ) concentrations . Interestingly , site s wit hmor e complet e dat a hav e n o AAA 

### observe dexceedances , s o tha t bot hx(p Q 

### ) an dVa r (x(p Q 

### ) ) ar e calculate d t o b e zer o fo r p

g> 9 4 percent . Fo r smalle r value s o f pg , however , bot h x(p 0 

### ) an dVa r (x(p Q 

### ) ) increas e wit hp Q 

### , wit ha fairl y shar pris e in 8311+ 6 9 

## 5 8C O o o a



## o oaverage1siteannualTABLE5-1.Estimatedcompo - oitsestimat

T 3 C r o n o C L < 3 - CVJ 

### R S 3 o

. c i c u c o 4 - o O l + J 1+^ o t/ 1 o +- > i_ > c : z s 4 - 1/ 1 ra

o C L <P - s - r a c > (I J ( J c r a s _ r a >teness.1requiredpercentage,pQ,ofdatacomple



## o o

Q - < 3 - $

_ r o < >

o Q . < P -

O Q . L D rl O i H o r o r o r o r o r o vo r - v o r - <x > ri C M r - C N r o o o r-t i n •« *

r H

OOOOO O OOOOO O m ^ r-i ^ <Tt m •>* o o r » a\ r - c n < * w » o oo • « cr > v o r ^ r - vo r - C N C N C N C M C S C N

O l <T l O O C l O 0\ 0\ O O CTV O CT> O^ l O O ^ O ffl o > O O O l o c o C N C N o r » i n lOffiuiHoxNinHoioiffioor^off i

r--oor--oooocovoCT>r-inr~CNoor-~cr> o r-voorocrioinoovorocMocNoinc H OOOCNrHiHVOOinrHOOmfOCNCOr-lf H CM<T>oor~voir»in^j , "^rcororororocor o rHOOOOOOOOOOOOOO O
OOOOOOOOOOOOOOO O OOOOOOOOOOOOOOO O HMOCNinoinooinvorTJ'ffi'j'criv o vorocMinr-rHCT>vor-OiHcnr~-crvroc N CNrHVO I -*CT>OOVOr~VOrOCMOOr-CNO O i~-r"~vovoininir>ir>ir)inir»'3''3'ir>ini n CMCNCNCNCNCMCNCNCNCNCNCNCMCMCMC N a\oOToo\oimoiooa\ffiooo o cnocnootoioioioooMnooo o o\ O 0NO^O>CTlCT»OO^CT(OOO O siocnooxnaioioocnoiooo o r~CNCNCNr~roi>-r-rHooooooooinoor o voin-<i , cOf-iooor-»incNOO'«j'or-i-icNror~cr>r-i'«j' o m m m m m o » o

o o o o o ooM^r^vowmi'fnNC N



## o o o o 0 0 

## o a i i n

I D J - r o c o



### 0(A ) y(p Q ) versu s pQ (B ) Var(y(p n ) ) versu s p r

- +

o c i O c u X J O J -(- > r O E l/ l co . + + + + + + + + + 4 + + + + V +

10 . 20 . 30 . 10 . 53 . 60 . 70 . 80 . 80 .

Require d Percen t 1C0
. rs i

m _VarianceEstimated10

i / i

.- u + +

i + + i + + + i +

+ + +
i i ; i 10 . 20 . 30 . 10 . 50 . 60 . 70 .

Require d Percen t 80 . 90
. 130
.

FIGUR E 5- 1
. Estimate d long-ter m SO ? ai rqualit yparameter s as function s o fth e require d dat a completeness , p„ .

R 1 1 ' i G

### 1 0 O O 0

O D
1— «

. r c n

CT > I—* 

### O O Q O

MU>uj.e».Lncy»CT\-~j^j--Jooooaocovovovovoiov o OjbHONlUHOWOU)00l0i^Nl00OK)UU10\v l towwMioiouioa)iti>iooH«5i-'vi*bomwiti>o o >JUl-slWUIOOOOiM- , vlOOIOWWa(l- , UHDit>.W O il>OOOvHD^|vlO«>HIOHHHN)vlHili(X)IOvlO O oooovovooooovovovovovooovovoovo o
OOOOVOVOOOOOVOVOVOVDVOOOVDVOOVD O

OOOOOOOOOOOOOOOOOOOOO O HHHHMHHHHHHIOIOWIOIOWIOMWIOO I |OMUIUi^U19ivlOOa)VOON)U)U1IX)OvlU}OaVOt O •JOOUimft.WIOWIOOlCTimMVOVOWtOOIOOOO A OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O

OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOOt O OOOOOOOOOOOOOOOh-'MI-'l-'tOLn O HHMHMHtOIOIOWWit»UimOOHWWa)vlH* > uw*uiviiotouiy>woouiitkvi*wo-Jowwoov i Hitk7j^>JOOfcfcOOmO>W|\J(MOibOOU100 H - T D o

>- > -a o

< > C U

- s

•>• > T D ocentage,pn,ofdatacompleteness. 

## o o

O f D —\ 0> X3 »

- j n o o

- —.C D 1 — >m > f D m C L T D o>

t n O 3 1 ^_ ^ o r o.Estimatedmeanannualrateof24-houre,x(pQ),anditsestimatedvariance,),asfunctionsoftherequiredper-

</

1 O r o 

## o' 0 0

U J t — < ! - F 1 CT1

! i : i i 1 i i

i i
i i i

• t i i i I

i! i
i i



### i O J

m

- h c 3 n <-t - mU.0SUO

- b rt- 3 " f Dreq c

- 5eddataco -

- n r— t c n c = P O m t n i r o
m i n r-t - 3 O Jted m 3 " ort-termSO 3 r oplet f D 3 f D V I t o V T D O Q J

_ olualityp Q Jrameters P O f DquiredPercent

P O f DquiredPercent sP- 010.20.30,

t n60.7
t s
C D C"3* "

ea '

r a - Q

sP0 0

(S3 -10.50.50.70.e0.93.I r h

rh V
¥
t- t - t f 4- +t

# X

f^ 3 2 9

Estimate d Exceedanc e Rat e 0 . 1 0. 2 0. 3 0. 1 0. 5 0. 6 0.7 ' 0. 8 0. 9 1. 0 t . l rI I tI I I I +

+ + + + + + + + + + + +

+ +

Estimate d Varianc e 0.0 5 0.1 0 0.1 5 0.2 0 0.2 5 0.3 0 0.3 5 0.1 0 0.1 5 0.5 0 i i i i i i I I i i

+ +(A) >> > T D O *- * < f Drsus T D O

0 0
< > Q J

- 5 > < > •a O < f D " 5 (/! c l/ l

• a o •'

•

•

•

•

•

•

•

•

•

• I•tr

CT )

t O K J O O C D U T u>£kO\cn^JoooocoaovovoK>vov0vov0V0v o L H t o I- J oo^HOiootooiouiMjTcriffivK s UUIOUOOOvllOIOOOOOUIv J OOOOOVOOOVOVOOVOVOV O OOOOOVOOOVDVOOVDVDV O OOOOOVOOOVOVOOVOVOV O OOOOOVOOOVOVOOVOVOV O OONNOOOSIT J OVOOOVOVOOV O OVOOOVOVOOV O OVOOOVOVOOV O OVOOOVOVOOV O

o o OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOO O O O OOOOOOOOCD O OMJiviuimmmvivisjoomuirnHHooooo o COOOHNIOWVIIOWOOUIIONIWIOWOOOOO O OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O

OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O H-'MMI-'MI-'l-'l-'tOtOWh-'tOtTOOOOOOOO O WWUIK)WUIvliDMO\OlOWIOHHOOOOO O oo\owwvi,i>*ioou\oui7j«)Oi«>a)Ooooo o T D O

>- > *— % • a O

. -

< > c u

- s ."— ^ 5- > > •"—' N T D O % * ' — O

o 3 T D

— - m tt <-tf D 3 f D i n i n • O

- h r + 3 " f D

- J f D J D C _ j .

- s f D C L T D f D

-s r > f D 3 rt O i U D f D * # T D O •* O -• > C X C U r-tO J r o i n rt mm. = ) a i c + f D C X < C U

- s mJ. Q l 3 o ( D * # < Q l

- 5 ^ ^ >- > ^- ^ T 3 O

. . , # C U i n - * i c 3ctions o 3 f D 1 3 - o c

- s O o n > X o < D f D a . O J 3 > O f D « » > >• > mmm^ T D O

w O J 3 CX - j * rt i n — 1 3 » 0 0 1 — m t n i o o • m i n c + mm. 3 Q Jrtf D C X 3 f D B J 3 a i 3 3 C C U

— *

- s C U rf f D O

- h

u
, o • 1;
1 i

t

i
1 i

i |

•i i 1 1 ! j > i , i ! 1 1 ! i i i

i
:

i
' \ ] 

### 1 1 1 t
|

,

1 i I 6 d C D

• P J l

Q J "T l i n i— t rn -h CZ C 73 3 m n rr- t n -> •i o O J 3 • i n o m

- h mrtrt- -> • 3 - 3 f D Q Jtedone-hourrequireddat Q J O o O O Q Jirquamplete 3 — ' f D -" • i n rt - t n < < m T D T D QJ O " 5

•Q J 3 ( D rt - f D

- 5 i n 17 9

Estimate d Exceedanc e Rat e _ 0
. 0000
. 0100.0200. 0 300.0100.0500.0600.0700.0800.09 0
• ^ t i i ti t
. i i i

<s -

C J "

^ -
. U J TO s ~ f D • J D — J * eg -

- J • f D C Xu i

" O ' f D

- 5 o i O s - f D 3 r t - - J C i "

• X " J "

L O i + + + 

### +

+ + + + + + 4 - .

c a

Estimat e Varianc e Jl. 0000.0000.0010.0010.0020.0020.0030.0030.0010.0010 S r i I l. l I I I I I I

s -

f D £ -

- Q • LZ

_ " ^

- 5 s H f D • Q . in ~0 C3 " f D60.rcent Q "

C D Q " T

+

+ + +

+ + + + +

+ + * 3 a

>m > T D OS M ^ < C D -% m c i n T D O

0 0 w . ^ < > 0 1

- J ^-m. V> ^ - N • a o
~ . .)ver i n C l/ l •a o •

•

•

•

•

•

•

•

•

•

•

iP.9 2

Va r (x(p 0 ) ) beginnin ga t p g = 6 0 percent . Th e result s sugges t tha t no mor e tha n6 5 percen t dat a completenes s i s neede dt o estimat e th e nationa l hourl y COexceedanc e rate . Tabl e 5- 4 an

dFigur e 5- 4 show

result s fo r 8-hou r COexceedances . Bot hth e A estimate dmea nexceedanc e rate , x(p n ) , an dit s estimate dvariance , AA^ Va r (x(p 0 ) ) sharpl y increas e fo r p

g > 9 0 percent , suggestin gtha t n o mor e tha na 9 0 percen t dat a completenes s requiremen t shoul db e use dt o estimat e th e nationa l 8-hou r C Oexceedanc e rate .

NITROGE N

DIOXID E

A Tabl e 5- 5 an

dFigur e 5- 5 sho

w u(p n ) , th e estimate dcomposit e annua l

*J AA averag e nitroge ndioxid e (N0 2 ) concentration , andVa r (u(p Q )) , it s estimate dvariance , fo r severa l value s o f th e require ddat a completenes s proportion , pg . Th e estimato r p(p Q ) i s fairl y constan t wit hpg , bu t it s estimate dvarianc e increase s substantiall y fo r p g > 9 0 percent . Thi s suggest s tha t no mor e tha na 9 0 percen t dat a completenes s requirement shoul dbe use dt o estimat e th e nationa l statu s an dtrendi nN0 £ concentrations .

OZON E
Tabl e 5- 6 an

dFigur e 5- 6 show

th e estimate dexceedanc e rate , x(p Q ) , an d it s estimate dvariance , Va r (x(p n )) , fo r dail y maximu m 1-hou r ozon e (Oo ) * W

rs ° concentrations . Bot hx(p Q ) an dVa r (x(p 0 ) ) increas e wit hpg , wit ha fairl y shar pris e inVa r (x(p n ) ) beginnin ga t p g = 8 5 percent . Th e result s sugges t tha t n bmor e tha na 9 0 percen t dat a completenes s requiremen t shoul db e use dt o estimat e th e nationa l dail y maximu m ozon e exceedanc e rate .

83m 6 9 

### 6 5

# o

o

o TABL E 5-4 . Estimate d mean annua l rat e o f 8-hour C

O exceedance , x(p n ) , an d it s estimate d variance , Var(x(p Q ) , a s function s o f th e require d percentage , PQ , o f dat a completeness . x(p Q ) Var(x(p Q ) ) 

### O

O

O

O 99.3039 9 98.7899 9 97.6140 0 96.9059 9 95.7759 9 95.0679 9 93.6530 0 92.4890 0 91.1759 9 90.1709 9 88.5499 9 86.9289 9 80.8790 0 74.1319 9 68.4019 9 61.3469 9 44.5890 0 35.2629 9 25.5820 0 20.0460 0 0.5140 0 0.2970 0 43.7550 0

47.9129 9 49.9620 0 43.6939 9 39.2820 0 34.0160 0 34.1540 0 33.2879 9 35.1700 0 33.6909 9 31.1620 0 31.3650 0 30.4450 0 29.9710 0 31.4230 0 30.3030 0 29.7540 0 30.5920 0 29.6850 0 33.5129 9 32.9310 0 32.8620 0 254.1313 5

183.8109 7 155.0844 1 92.2039 6 63.4661 0 45.1320 7 40.9376 3 35.9497 4 38.8421 4 33.2028 7 27.7175 0 25.1968 7 22.0512 7 20.3942 1 24.0619 6 21.2795 1 19.3550 6 18.6498 0 16.9545 5 26.1345 6 24.2347 4 24.1383 9


### O

O

O

O 831U 6 

### 6 6C

O O J V O l 

### Z 9

Q J m

- h c 3 O rt - ^ t <D 3 i n - n >- H o c z P O m t n i -e »

. o m

3 " f D

- 5 f D J D c mm.

-s f D 3 Q Jrtf D C X 0 0 1 3 " o O . C a . O J rt Q J O O 3 T D

- ^ f D r l f D 3 - 5 o o Q J .^ . -T " J D c Q J mmi mm. rt f D < < i n i n > . T D o

. T D O i

- J Q J 3 ( D rt f D

- s i n P O f D J D C J

- S CD Q
. T 3 f D

- 5 O f D 3 r + Estimate dExceedanc e Rat e

10
. 20
. 30
. 10
. 50
.

_ j 1 1_ ^ 1
.

+ + T D O < f D •% i n
T D O 

### t + 

## * ' x y

Estimate d Varianc e s P 50
. 150
. 250
. 300
.

P O C D J D C _ j . -m f D C L -o ( D

- i o f D 3 rt Q J S "

.£ > ea t / i K > -

ca -70.8
ca t o + +

+ + + + + + 0 3

O J

- 5
T D O < ( D i n c i n

• a o
+ 

## 4 + +P.9 5

TABL E 5-5 . Estimate d composit e annua l averag e o f one-hou r N0 2 , y(p Q ) , and it s estimate d variance , Var(p(p 0 )) , a s function s o f th e require d percentage , p Q , o f dat a completeness .

p 

# o 96.5000 0 95.0999 9 93.7999 9 92.3999 9 90.5000 0 88.2000 0 85.7000 0 82.0000 0 78.2000 0 75.2000 0 69.7000 0 65.5000 0 58.3999 9 51.3999 9 45.3000 0 37.1000 0 31.8000 0 26.9000 0 23.1000 0 17.5000 0 0.3000 0 0.3000 0 A

•v(P 0 ) 33.4409 9 34.7530 0 41.2150 0 44.6939 9 44.6000 0 44.8960 0 44.3609 9 44.7140 0 45.9279 9 45.6250 0 44.9470 0 44.6349 9 45.0140 0 44.4539 9 43.9920 0 44.3019 9 44.2339 9 43.6550 0 43.7759 9 43.5640 0 43.3670 0 43.2469 9 A/• .

Var(y(p 0 ) ) 14.5987 8 6.8154 4 11.6274 3 10.4651 9 6.8971 1 5.3276 3 4.3596 4 3.4197 4 3.3488 0 3.1954 6 2.9265 6 2.7485 3 2.5641 0 2.4239 3 2.2454 1 2.2214 6 2.0557 8 1.9291 1 1.7844 6 1.6498 2 1.5710 0 1.5757 5



## 6 8 6314 6(A ) P(P 0 ) versu s pQ (B ) Var(p(p Q ) ) versu s p Q

CT ) V O c

to
T D <V +- > r o E , + + + + + + + + + + + +++ +

+ +

10
. 20
. 30
. 10
. 50
. 60
. 70
. 80
. 90
. 100
. Require d Percen t in. C U - o c ro • i — S
_ r c T D ' O J

"b. + +

+ +

. + + + + + + + + + +

" l —1 1 1 1 1 2 0
. 30
. 10
. 50
. 60
. 70
. 80
. 90
. 100
. Require d Percen t

FIGURE 5-5
. Estimate d long-ter m N0 2 ai rqualit yparameter s a s function s o fth e require d dat a completeness , p Q .

8 3 1 l i C„P,9 7 

## O

0

O TABL E 5-6 . Estimate d mea n annua l rat e o f maximu mdail yone-hou r ozon e exceedance , x(p Q ) , and it s estimate d variance , Var(x(p n )) , a s function s o f th e require d percentage , P Q , o f dat a completeness . 

## O

O

O

O

O p 

## 0 98.8999 9 97.7999 9 96.3999 9 95.2999 9 93.8999 9 92.8999 9 91.5000 0 90.0999 9 88.2999 9 86.8999 9 85.0000 0 83.0000 0 80.2999 9 78.0000 0 73.7999 9 67.2000 0 61.2000 0 50.8999 9 40.0000 0 26.8000 0 3.7000 0 0.4000 0 

### x(P 0 

### )

12.8230 0 20.1000 0 19.9020 0 18.1840 0 15.0180 0 13.1060 0 12.8350 0 11.5830 0 10.6570 0 9.7190 0 9.1610 0 8.5340 0 8.1760 0 7.8380 0 7.4310 0 7.4520 0 7.3640 0 7.2000 0 7.7850 0 7.9380 0 7.9260 0 7.9150 0 AA.

Var(x(p Q ) ) 30.2039 9 22.9468 7 15.0890 7 10.6284 5 7.0156 8 5.0499 8 4.2744 2 3.3042 7 2.6744 9 2.1821 9 1.8207 0 1.5377 7 1.3261 4 1.1613 7 1.0147 5 1.0081 5 0.8977 9 0.8283 4 0.9316 9 0.9596 3 0.9664 6 0.9639 4



# o

o

8314 6 

# o 7 0

B B ES D

### I Z

Estimate d Exceedanc e Rat e

Q ) -T | i ni— i CT

- h C ZRE5unct-6.ions o r n

- h i n 

## £ .

JD C
, -B f D *-

—t n3.60Perc f D • 3 r t
- - j

rrs
CD Q J

- 5 f D J D C - J ,

- 5 f D Q . Q . Q l rt Q j r > O 3 T D m-1 f D f D a . QJ 3 3 C QJ

— j O M o 3 f D OJ _ j
.

- 5 rt - J D f D 3 f D i n i n * T D O C QJ

— '

— , . rl - < < T D QJ

- 5 QJ 3 f D rt f D

- s i n 20 . 30 .

+ + + + + . • a o < a > m c m

• O O

" ^



### «?,
- Estimate d Varianc e

10 . 20 . 30 .

P O f D c

- s f D C L T D f D

- 5 n f D 3 rt c r10.20.3
s -

j ^ S "

c n

^ j e a - C D IS "
U D s " . T +

+

+ + + + + + +

^ . •

+ + *

* r ' wr* i

+ + 10 .

0 3

a t

TD O < f D m


### oP.9 9

LEAD
Tabl e 5- 7 an

dFigur e 5- 7 sho

w u(p n ) , th e estimate dcomposit e maximu m V AA quarterl y

lead(pb ) concentration , an dVa r (u(p n )) , it s estimate dvari AA^ ance . Bot hy(p Q ) an dVa r (p(p Q ) ) ar e fairl y constan t fo r p Q< 1 7 percen t (correspondin gt o complet e dat a recovery fro m a once-per-six-da y samplin g schedule) . Onl y

a smal l numbe r o f site s hav e mor e tha n1 7 percen t dat a completeness . Th e consequen t ris e inth e estimate dvarianc e suggest s tha t no mor e tha na 1 7 percen t dat a completenes s requiremen t shoul db e use dt o estimat e the nationa l statu s an dtrendinleadconcentration s unde r curren t samplin grequirements .

TOTAL SUSPENDE DPARTICULAT E
Tabl e 5- 8 an

dFigur e 5- 8 sho

w y (Pg) , th e estimate dcomposit e annua l averag e concentratio no f tota l suspende dparticulat e (TSP) , andit s AAA estimate dvariance , Va r (y(p Q )) . Th e estimato r u(p Q ) i s fairl y constan t wit hpg , an

dit s estimate dvarianc e show s no patter nfo r increasin gpg . Therefore , i t i s no t possibl e t o judg e th e effec t tha t a nincrease ddat a A completenes s requiremen t woul dhav e o nth e varianc e o f u(p 0 ) . Similarly , Tabl e 5- 9 an dFigur e 5- 9 show

no appreciabl e patter ni nth e
A estimate dvarianc e o f x(p Q ) . Figur e 5-9, . however , suggest s tha t increas ingth e require dpercentage , pg , may induc e a positiv e bia s inth e estimat e o f th e nationa l averag e exceedanc e rate . Becaus e o f thi s possibl e bias , i t appear s tha t no mor e tha na 1 7 percen t dat a completenes s requiremen t shoul dbe usedt o estimat e th e nationa l statu s an dtrendi n TS P concentrations . SUMMARY
I ngeneral , we se e tha t th e advantage s o f includin ga larg e numbe r o f site s inth e estimatio no f nationa l ai r qualit y trend s outweigh s th e
831*t 6 9 7 2C O C O

o o OOOOOOOOO*.^J0D0BOW*»Ut<7>a>^J-J^ J OOOO-'-^-'-'aiWOi'oMOONMWWWW W -»-*0ol-»{>.U10>- , ^0l0l0a)lkCD-*00l0l0i D

— « - « v l 0 0 - » X

kC7 > -v l —'00lDO>O>lOWO>^l^fc- * — * — * OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O

OOOOOOOOOOOOOOOOOOOOO O tk^VJIO>4>lkJ>,UII\)-»l\)-UUlUI~JO*ivJ-JOi-vir>ov O 

### wo>WK)0)Wa)Mioa)a)K)N)i\)ON)Oo>-'a)ON ) OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O

OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O ^ ^ i > U l M - - —- — •OOOOOOOOO-' O —IS } U l IS)UIVJ»04^Ul-J~Jis.^\JlCTivJOiCX5-JvO— • l O * - • U l lOOlOWvllOMlOOOT.IWMJwUiOUI-'UllOWUi W T D O

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- 5

. s

- e > -.—. . T D O

^ — • .—. - o o 3 T D

— J f D r + f D 3 f D i n i n

. O

- h c + 3 " f D

-s f D J D c — J *

- 5 f D C X

- a f D

- j o f D 3 rt - O J U D f D V * T D C D > * O

- h C L a t r l - O J C D i n rt - —*. = 1 Q J rt- f D a . < O J ~. mJ. Ql 3 O f D ^ < a > -. mm-. s

- c
^ V T D 3

- . . ^-^ sr Ot i n

- h c 3ctions = i a i X — J
. = 1 c

- 4 J D C Z O J

- s rt - f D

- 5 —ml V C

. . J C D > Q J Q . V > x : *^-N
. • o o %« - t « Q J 3 C L —( . rt - t n — 1 T > oo i — r n t n i

~ j

. m i n r + — f
. = 3 Q J rt - ( D C X O O > = 1 T D O i n — j
. rt- f D O J < ( D

- 5 O J I O f D O - + >

### frZ

O J I/ I
- t i c 3 O rt mJ. o 3 i n O

- h rt 3 " f D n f D J D C

— t
. -i f D C X C L O J r l - Q ) o o 3 TD

• ^ f D rt f D 3 f D i n i n , * TD o

. - n i— , CT CZ P O m U l i v i

. m i n rt - —*• 3 Q J rt f D C X

— J O 3 U D 1 rt f D 1 3

—- J f D O i Q
. Q l — i
. -i JD C O i

— ' _ J
. rt t < T D O J -% Q ) 3 f D f D

- 5 l/ l ) . 0 0. 1

p a t D J D c f D C X T 3 f D

- 5 o f D 3 0 . 2 I Estimate d Mean

. 3 0. 1 0. 5 0, 6 0 ,

4 - 0 . 5

_ i 0 . 6

I 0. 8 0. 9 i 1. 0

4 - 44 -

4 - +

+ + 4 - • o o < ro

- i m

• o o

^.00 0

p a f D J D

" 5 f D T 3 f D

- s n f D 3 <- + Estimate d Varianc e

0,00 2 0.00 1 0.00 6 ' 0.00 8 -f^- I 4 - + 0.01 0

0 0

Q J

4 - 4 - O < f D T m c i n • o 

### o

4 - 4 -

Z dP. 3

TABLE 5-8
. Estimate d composit e averag e o f 24-hou rTSP , y(p Q ) , an d it s estimate d variance , Var(p(p n )) , a s function s o fth e require d percentage , p n , o fdat a completeness
. p 

# o 30.6850 0 16.7120 0 16.7120 0 16.4380 0 16.4380 0 16.1640 0 15.8900 0 15.8900 0 15.6160 0 15.3420 0 15.0680 0 14.7950 0 14.2470 0 13.9730 0 12.8770 0 12.0550 0 10.4110 0 8.2190 0 6.0270 0 3.8360 0 0.2740 0 0.2740 0 y(P 0 )

51.0819 9 53.5920 0 56.0500 0 56.5280 0 56.7260 0 56.5770 0 57.1089 9 57.1700 0 57.2869 9 57.4829 9 57.4350 0 57.2720 0 57.1340 0 57.2899 9 57.3100 0 57.4110 0 57.2049 9 56.9719 9 56.7820 0 56.7090 0 56.5259 9 56.5259 9 AA

Var(y(p Q ) ) 3.1793 1 1.3566 6 0.9099 8 0.6959 1 0.5204 5 9.2207 5 2.1236 0 1.1366 3 0.7509 1 0.5688 9 0.4440 4 4.1873 1 1.4216 3 0.8676 8 0.6587 2 0.5648 3 0.4551 0 3.0455 3 1.3726 8 0.8746 3 0.6633 4 0.6633 4

8311+ 6 75

### 9 Z

f D IC I c xi rt Q
. f D Q J " 5 rt- 3 Q J

—I o o o O - O 3 TD Q J ( D - 5 rt f D J D 3 C f D O J i n — ' i n -> • » rt TD O T D •D J

- s Q J 3 fD rt f D

- S i n sP

Q J -T I i n i— i CT

- h < = C P O 3 m o r i - t n O CO 3 • i n o n -t i m rt rt - -J 3 " 3 f D OJ rt - -i t D f D C L C — '
_. . o p o

f D J D
f D C X TJ f D (- > f D rt 10 . I 20 .

i Estimate d Mean

30 . 10 . 50 . L
_ 60 .
4 - 4 - 4 - 4 - 

## t 

# } o
<

r o

- j m
o

Estimate d Varianc e 3. 0 1. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

P O CD JD C

- 5 fD C X T D f D

- 5 r> ( D 3 - •=r J

-

4 - 4 -

" 4 -
++4- + i

+ i

4 -

4 - 1 1 !

4 - 1 1 1 1

4 - 0 3

O J

- J

• o o < f D m T 3 O

Vd-r-

c n

^ J OOWOlOOMNWAJiiUIUIUIVIIUlOlOiOiOiOi O MMODOM^OO)iOM>IOOIOiO)(»- > A<kNlNlO i Nl>JWNJ-»-'UlNlvl*,l00»lk-'l0l00M>H>l-'-» O JkAOlNjiO-*UlvlW-slUIO)N)(7ioOJi.a)a)NMU l OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O

K JIV ) Ji^lwUIUIUIUIAWWWO.^UIOvJOivHO'OM* ' O5O)00WJkvliO4>.M —VIW(OWVIUIO>JMVJ1N)N ) ~J-J-»UllO-»-JOiaDUlCT>Ulv000f>000O00OO-Nl 0 OOOOOOOOOOOOOOOOOOOOO O OOOOOOOOOOOOOOOOOOOOO O

0000000000000000--0000 0 -.-.-.NjOl-'- * ——- * U l O O - •—WM O -•- » N X" . WWOBlOWOM-'-'(»7>IOia)-'(D^*>IOK)rv)U I OOOOO-'UHiOlOtO^lOWWWOiUlUIJikOOOW W -'fc^OO-'OOOWWOOlWfcOOiOOOvlMlOv J uwwooNio-JajNiuiwuiwww^ji.-'uioioia ) T D o

T D o

a i

- 5
T D o o

o = ?

- a

— J f D r l - f D 3 r o i n i n

. o - t l rt - 3 - f D

- 5 f D J D c —i.

- 5 ( D C X T D f D

- 5 O f D 3 rt - a > I Q f D mf T D O < * O f D i n rt - _* . = 3 Q J rt- f D C X < C D

-s m l
. Q J 3 n f D » < a t

- s *- ^
> 7 *—~ * T D O ^— * ^. ^ , . Q J i n r o .£ » i ZT O £ Z

-s

— 1 O O T P a > X o f D f D C X a > 3 > n f D v > >-" > *m- «* T D O7 ^ ^ tf a > 3 C X — \ > oo 1 — m t n i vo

. m i n rt - ^ . = 1 a > r l - f D C X
= 1 f D Q J 3 Q J 3 3 C a >

— ' C X- h Ol c rt - 3 O J n r l -

i n a * f D o o 3 i n

TJ U l8 Z

Q J i n - t i c 3 <- > rt - — i
. O 3 i n O - t i r l - ZT f D

" 1 f D J D SZ mm.

- s f D C X C X Q J rf Q J - n t—m CT c : P O m O l i VO • m i n rt- — j
. 3 O J rt f D C L i n 3 " O

- s r l - r + t D ~l 3 O — I O C O 3 " O TD

—•Q J f D -" • r l - - 5 f D 3 J D I D C i n Q J i n — < TD v < o •TD Q J

- 5 Q J 3 f D rt f D ~i i n X I

f D J D
f D Q L tD

- 5 o f D 3 Estimate d Exceedanc e Rat e

0. 5 1. 0 1. 5 ' 2. 0 • 2. 5
, , 4 1 . _ 3. 0

+4- 4 4 - 4 - f ++ t r + -H - + T D O < f D -. m c m T D o

Estimate d

. 5 ' l. l Varianc e 1. 5 2. 0

P O f D

- O c fD
. C X T 3 f D

- 5 O f D 3 T O 4 -

4 - 4 - 4 - "H f4 - o >

• o o < m -. m c m

" O o

9 dP. 7



### disadvantage s o f includin gsite s havin ga lo w dat a completenes s propor tion , p.j . The broadinferenc e fro m thes e 198 1 results—whic hseem s likel y t o hol deve ni f mor e frequen t intermitten t sample s o r mor e complet e dat a ar e required—i s tha t th e wid e variabilit y betwee nsite s argue s agains t th e exclusio no f a larg e fractio no f site s solel y onth e basi s o f dat a completenes s requirements . Thus , th e requiremen t fo r estimatin gnationa l trend s shoul dbe mor e relaxe dtha ntha t fo r determinin gth e attainmen t statu s o f a

nindividua l site .

8314 6 9 7 9REFERENCE S P. 8

Abramowitz , M. , and I . A . Stegun . 1964 . Handboo k o f Mathematica l Functions . Dover , Ne wYork . Brillinger , D . R . 1969 . Th e calculatio n o f cumulant s vi a conditioning . Annal s Inst . Stat . Math. , 21:215-218 . Breiman , L. , 0 . Gins , and C . J . Stone . 1978 . "Statistica l Analysi s and Interpretatio n o f Pea k Ai r Pollutio n Measurements. " Technolog y Servic e Corporation , Sant a Monica , C A(TSC-PD-A190-10) . Breiman , L. , and C . J . Stone . 1983 . "Approximat e confidenc e bound s fo r extrem e quantiles. " I n progres s (wil l b e submitte d i n 198 4 t o J . Amer . Stat . Assoc.) . Cochran , W . G . 1963 . Samplin g Techniques , 2nd ed . Wiley , Ne wYork . Davidson , J . E. , and P . K . Hopke. , 1983 . "Implication s o f Incomplet e Samplin g i n a Statistica l For mo f th e Ambien t Ai r Qualit yStandar d fo r Particulat e Matter. " Pape r presente d a t th e 76t hAnnua l Meetin g o f th e Ai r Pollutio n Contro l Association , Atlanta , Georgia . EPA . 1979 . "Guidelin e fo r th e Interpretatio n o f Ozon e Ai r Qualit y Standards. " Environmenta l Protectio n Agency , Researc hTriangl e Park , NC (EPA-450/4-79-003) . EPA . 1981 . "U.S . Environmenta l Protectio n Agenc yIntra-Agenc yTas k Forc e Repor t o n Ai r Qualit yIndicators. " Environmenta l Protectio n Agency , Researc hTriangl e Park , NC (EPA-450/4-81-015) . Frank , N . H. , and T . C . Curran . 1982 . "Statistica l Aspect s o f a 24-Hou r Nationa l Ambien t Ai r Qualit yStandar d fo r Particulat e Matter. " Pape r presente d a t th e 75t hAnnua l Meetin g o f th e Ai r Pollutio n Contro l Association , Ne wOrleans , Louisiana , Jun e 1982 .

8314 6 6 

### 8 0P. 9



### Hajek , J . 1960 . Limitin gdistribution s i nsimpl e random samplin gfrom

a finit e population . Pub . Math . Inst . Hungaria nAcad . Sci. , 5:361-374 . Johnson , N . L. , andS . Kotz . 1969 . Discret e Distributions , Wiley , New York .

8314 6 6 

## 8 1P.1 0



### Appendi xA SULFU RDIOXID E DESCRIPTIV E STATISTIC S

8314 6 5P.1 1

APPENDI XA SULFUR DIOXID E DESCRIPTIV E STATISTIC S

Usin g progra mNA28 2 o f th e EPA' s Storag e and Retrieva l o f Aerometri c Dat a (SAROAD ) system , variou s summar yfile s o f 198 1 dat a wer e obtained . Figur e A- l show s th e distributio n o f dat a completenes s amon g ai r monitorin g stations . Tabl e A- l show s th e numbe r o f site s meetin g an annua l quot a o f 7 5 percen t dat a completenes s and meetin g a correspondin g quarterl yquot a i n a specifie d numbe r o f quarters . Tabl e A- 2 show s th e sam e informatio n fo r an annua l quot a o f 5 0 percent . In considerin g whethe r a quarterl y quot a shoul d b e require d s o tha t an eve n distributio n o f dat a woul d b e guarantee d throughou t th e season s o f th e year , i t i s o f interes t t o not e tha t roughl y7 0 percen t o f th e site s tha t me t an annua l quot a als o me t a correspondin g quarterl yquot a i n eac ho f th e fou r quarter s o f 1981 . Ther e ar e lo wcorrelation s betwee n th e percentag e o f dat a completenes s and reporte d annua l averages , standar d deviations , and coefficient s o f variatio n (Figur e A-2) . Histogram s o f "expected " exceedance s (i.e. , X . o r k./p . i n th e notatio n o f Sectio n 2 ) sho wtha t zer o expecte d exceedance s wer e reporte d b y9 6 percen t o f th e station s (Figur e A-3) . Th e greates t numbe r o f expecte d exceedance s wer e reporte d b

yth e station s tha t had th e mos t complet e dat a (Figur e A- 4 an d Tabl e A-3) .

8314 6 5p * - 3.. ' '-MMX
•- V G ..'.'.-7.0.0/7 * J
. .'.'.O'.'.'.u.' J * i •: . u.fjijii
* is..0.0.0.. /
* 1 b
. <J!JXJ:J *z\ ytvrj:) * 2 4 ..O.O.'/.: ' •••••2 V..'J.O.'.7 J
" 3«'
. tJiUu:] * 3 3..'J.O:./.-/ ' * 3 G .lir,,",'! •"3'. ' ..'J. O ,'

J
. a ••'' -1 2..07.'.•.•'; / * .15./,'.'.".•'.' J *!L I ..'/.O.o.- / * 5 1 .ffO.X X : ' ; I j < !
. w.0.0. 0 *<y/ .#:•;<)-J '•' : ufj. <:)£}:>.'• ••u J .ij:-J>:J:J * G 6
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. *\/\/ > \t \ •AAAAA A +,V\A.A,A A •AAAAAA A •AAAAA A •AA A •AA A •AAAAAA A
•AAA A •AAAAAAAA A •AAAAAAAA
. •AA A SYN20 L COUN TMEA N ST.DEV . A4/ 2 7G.98 7 23.05 8 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N 1 5 2f f2 5 3. 3 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5

+ A\ * AAAA AAAAAAA A :-AAA AAAAAAAA A + AAAAAAAAAAAAAAA A •A,"
. A , A, AAA
. A
. AAA , A
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1 5 2. 0 ;:L> 3. 7 3 5 4f f4 5 Uf f5 5 6f f6 5 7 0 V 5 8 0

8f f FREQUENC Y INT . 3 0 2 •3 0 7 2 0 5 5 5 C 6 7 6 3 3 7 4 9 9 8 3 1 5 1 2 1 6 2 1 2 6 4 0 5 1 6 6 7 5 3 8 1 0 0 0 SS CUM .

3 3 5 8 8 1 5 1 7 2 5 3 0 3 5 4 0 4 6 5 2 5 9 6 5 6 0 7 1 7 8 8 2 9 1 1 0 0 1 0 8 1 1 1 1 2 6 1 3 0 .15 4 1 7 5 2 0 1 2 4 1 2 9 2 3 5 8 4 3 3 4 7 1 4 7 2 4 7 2 4 7 2 4 7 2 4 V 2 PERCENTAG E

INT . 0 . 6 0 . 0 0 . 4 0 . 6 0 . 0 1 . 5 0 . 4 1 . 7 1 . 1 1 . 1 1 . 1 1 . 3 1 . 3 1 . 5 1 . 3 0 . 6 0 . 6 1 . 5 0 . 0 1 . 9 1 . 9 1 . 7 0 . 6 3 . 2 2 . 5 3 . 4 4 . 4 5 . 5 0 . 5 10. 8 14. 0 15. 9 8 . 1 0 . 2 ff.0 0 . 0 0 . 0 0 . 0 CUM .

0 . 6 0 . 6 1 . 1 1 . 7 I . V 3 . 2 3 . 6 5 . 3 6 . 4 V . 4 0 . 5 9 . V 11. 0 12. 5 13. 8 14. 4 15. 0 16. 5 IV. 4 19. 3 21. 2 22. 9 23. 5 26. 7 29. 2 32. 6 3 V . 1 42. 6 5 1 . 1 6 1 . 9 75. 0 91. 7 99. 8 100. 0 100. 0 1 BM. 0 MJPl.il 1 0 0
. 0 Numbe ro fSite s

8314 6 FIGURE A-la
. Histogra m o fth e percentage , p , o fdat a completenes s fo rthos e site s reportin g one-hou rS0 ? concentration s i n 1981 : SLAM S (includin g NAMS)
.P.1 3

L U
. Si o —r-->^rioinoro'*co>.i-vcri^r^^tvi'Cco5r^iac7iL'i"vDi^u-)'5-inL-)S:5iS!5-v 5 cs •• < z> mm —. re vL I o i ^

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### TABL E A-l . Numbe r o f site s recordin gone-hou r SO 2 durin ga t leas t 7 5 percen t o f th e tota l possibl e hour s in1981 , b y th e numbe r o f quarter s inwhic ha t leas t 7 5 percen t o f th e tota l hour s pe r quarte r ar e recorded .

Sit e Typ e SLAM S (include s

Othe r 

### N o



### w i 75%

NAMS ) . o f 

### t h Quarter s at Leas t Hours/Quarte r 

### 0 1 2 3 4 Tota l 

### 0 1 2 3 4 Tota l No . o f

> 75 % 

### 0 0 1 7 79 24 4 340 0 0 8 48 117 173 Site s

< 75 % 

### 3 5 48 38 9 0 130 49 8 9 5 1 5 9 0 248 Tota l



### 3 5 48 5 5 88 244 47 0 49 89 5 9 107 11 7 421

TABL E A-2 . Numbe r o f site s recordin gone-hou r S0 2 

### durin ga t leas t 5 0 percen t o f th e tota l possibl e hour s in1981 , b y th e numbe r o f quarter s inwhic ha t leas t 5 0 percen t o f th e tota l possibl e hour s pe r quarte r ar e recorded .

No . o f Quarter s wit ha t Leas t Sit e Typ e 50 % Hours/Quarte r SLAM S 0 (include s NAMS ) 1



### 2 3 4 Tota l Othe r 0 

### 1 2 3 4 Tota l No . o f

> 50 % 

### 0 0 1 9 42 343 40 4 0 1 1 5 102 170 288 Site s

< 50 % 

### 1 1 30 2 5 0 0 6 6 2 4 48 5 9 2 0 133 Tota l



### 1 1 30 4 4 42 34 3 47 0 2 4 49 74 104 170 421

83m 6 8SLAMS , SYMB0L= S OTHE R, SYMBOL= 0 N = B9 1 COR = .050 0 MEA NST.DEV . REGRESSIONLINE RCS.MS . X 70.49 0 25.72 2 X= ..0SG73*Y+ 68.32 8 6G3.3 6 Y 25.02 5 16.63 9 Y= .03S13*X + 22.47 9 276.3 0

CM o tn to tu 140. 0 +

122. 5 +

105. 0 +

37.5 0 +

70.0 3 +

52.5 0 +

35.0. 7 + ,X+ . .+ *

0 s s o o b o o 

### s o O S 0 O S SO S S

0 0 s

s s s s s s
17.5 0 +

. 0 0 00 0 00 * 0 s s 0 O S

S S O S 0 0 0 0 0 * 0 0 0 S S 0 0 s

s ssooo o 0 0 0 ' s s * s * * SS S O S O S s < ; 0 0 s * S O 0 S 0 s SOO O 0 OOOO * 0 sssoooo** * 0 0 oo s 00 0 SO O *0 0 S 0 0 O S 000*0 0 S S OOOSOOOOOO O 0 O S OS O 0* S 0 O S S O 0 0 OS-0 0 0 0 0 0 * 0 0 0* 0 * s s o

. 0 O S 0 00 0 S

0*SS* 0 00*000 0 SSSSS00*-00 S * "00 0 * s SS * S0"0*' 0

SO O OO S 0 SS S 00 * 0 s 0 0 0 s S O S s S 0 S * * 0 0 s s * S O S S * 0 0*S** * s * * * *S0*0 0 S OS* * S O S s o*s*o o 0 0 * s

s s 0 s SO S SSSS O os s s s sssso s s s s * s*s*s s s*ss« * 3 * * * S * s**s* * 2 * * -J ; rt ft rt rt * ft rt rt Q * * * * rt s**so s SS** ;

- - s* s * s ft rt

s s SS S sso s rtrtrtQ rtrtrt «*(-) * rt rt rt rt --s* s 0** 0 *s* s •••s o *ss s SS S 0.00.0 " + 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0

.00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGUR E A-2a . Scatte r plot s o f ambien t ai r qualit y statistic s versu s th e percen t o f tota l hour s recorde di n198 1 (p ) b y site s reportin g one-hou r S0 9 : annua l averag e versu s p .

8314 6SLAM S , SYMBOL- S OTHE R , SYMBOL= 0 N = 09 1 COR = .071 2 liEA N X7.v
. 4 9 3 Y39.20 5 ST.DEV . REGRESSIO NLIN E RES.II*; .

25.73 2 X = . .vriU.j-3-Y + 6U.22 3 GG2.0 7 32.73 3 Y = ..J9.J33 : -X + 32.-^ 5 10G7. 6

4.C0

30 0

2 0 0

17-. 7

1.C 0

0. 0 , + .X , ,+ *

0 s 0 s 0

0 0 0 0 s o 0 s s 0 0 O S s s 0 s o 00 * 0 O S s 0 O S S 0 0 O S

* 0 0 0 0 0 0 03 0 0 00 3 S S'.'O-' O 0 0 *•• * S S O 0 'Ju'- * -O S 00•-•••S

S 00'"' S iO O s o ••

• 30••• • 0 0 0 S O 00b005-0 * 0 0 OS S 0 0 s s 0 0 s rt 0 0 0 s

S 0 0 00 0 S 0 O'-OS S s OSOOO O 0 ••O S * s s s soaoo--*osu3* o U O 00 S SS03S0 0 «rto f t O•*-"* " •• • OSOO ;,; OOS*S ; *S*" ; MMVSO3SS ; '*" 3 •'S S *0 * S--S S 0 0 = 3-3S3**S-- * 0 0 * *0S 0 0 0 OS O 0 * *0"- v 0 0 0 S 0 0 0 ....+....+....X....+....+
. s S O S 0 0 s oos o 0 OS * O S o •••"o o *SSSS*0* * s*s***s* o rt rt rt rt rt rt rt rt rt * * rt * rt .-.

. 2 * S rt rt s rt rt rt

s rt s •• •* s * •'• ••s s s s soss s 7.50. J 22 . C. J 37.5 0 52.5 0 67.5 0 32.5 0 97.5 0 70 0 15.0 0 30.0 0 4 5.0 0 60.0 0 7 5.0 0 90.0 0 105. 0

FIGUR E A-2b . Standar ddeviatio nversu s p .

831«+ 6P.1 7

SLAM S OTHE R N - 89 1 COR=-.033 0 SYMBOL- S

SYMBOL- 0

MEA NST.DEV . REGRESSIO NLIM E RES.M S X 70.49 3 25.73 2 X=-1.0273*Y + 72.17 3 664.7 2 Y 1.G34 5 .3274 9 Y = - ..O0l'u6*X+ 1.709 1 .6047 7
,+....+....+.... + ,X+ . , + * 12. 0 +

C 7 . 3. 0 0 E
r, rr r

3.0 0

1 .3 0

0.0 0 . 0

. S

. s OOO O O S O 00 0 -OSO O s O S s o 0 0 0 O S O S O- O o* . 0 0 00 0 O S 0 O S 0 * 0 0 0 0 0 0 s o SO O 0 0

0 

### s o 0 s 0 0 O S 0 S O 0*0 0 S 0 0 00 0 *

s o*o- o •••

* * 0 0 SOO-O-- * -' S 0 0 0 000 3 *000'000 * 0 00 0 0 0 0 S O 0 0 0 SO O O S 0 0 3 0 0 S"30 ft *0-'0S 0 0**0 0 00S S

0 0 s s s s 0 0 0 0 0 s o * ••

* * s * * rt* « n *0'- 0 s * =• •o • •s s • SO S 0 O S o••••' •SO'- 1

O S O 0 • •a 0 ' S SSS'- S ss s *•••• •s o s 0**3** 0 — S

! '.:0"S*S*3 3 0 S 3 SSS * 0 0

. + . .X
. + . . <0*S !

*s y s * 0

0 0 * s 0 0 ••* o **os* o s S* 0 "* 0 rtrtrt rt .'.

- rtrtrt
* rt * rt rt rt rt rt * rt rt rt rt rt

s s s* * S3*0 0 0
7.50 0 22.5 0 37.5 0 52.5 0 G7.5 0 02.5 0 97.5 0 0.00 0 15.0 0 30..'7 0 4 5.0 0 60.0 0 7 5.0 0 90.0 0 105. 0

FIGUR E A-2c . Coefficient - o f variatio n(standar ddeviatio ndivide dby annua l average ) versu s p .

831U 6SYMBO L COUNT MEA N ST.DEV . A4 7/

T 0.18 0 1.42 4 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N 

## E

* . 6.0000 0 * 1 . 2.000 0 * 1 . 0.70.0 0 * 2 . 4000 0 * 3 .000 r ''7 ' * 3 . G00.0 0 * 4.2000 0 * 4 . 0000. 7 * 5 . 1.0.00 0 * 6..7.700 0 *6.G0O>)'0 ' ft).20000 * 7.8.000 0 * 3 . 4.0000 . «- j . i. r r r or/ 7 * 9 . G0. 0 0 0 M0.2.00. 7 -10.000 0 ')1.100 0 * 1 2 . 000. 7 'M2.G00 0 * 13 . 2.0.0 0 *13.i.!0('.' T 'Ml . 4.0.0 0 « 1 5 linf'A

I
• M5 . 6'"'' • 7 '••• • 1 f i . 205 0 "1G.'V". 0 * 1 y . -I ' • ' 7 * 1 0 0'-;.. a *Ki . G0O. 7 * 19.200 7 *1 9 .8"" ' J "20.407 0 rt ,> 1 . 000/ 7 *;: i .G.0.0 0 ft 22.2000

- 2 2.000 0 •/".A

A •AA A •AA A
• A A
• A + i

- + + + ' + +
• A
• A
• A A + + + + + + + 1

- + + + + +
• A + +
• A + +

» • + + + 5 "•.AAA / \

<

5 1 0 1 5 .AAAAAAAAA .

1 0 1 5 2 0 2 5

-.AAAAAAAA/ '

2 0 2 5 3 0
rt rt AAr t

3 0 3 5 4 0 4 5 5 0 5 5 AAAAAAAAAAAAAAAAAAAAAAAA A

3 5 4 0 4 5 5 0 5 5 G 0 6 5 7 0 7 5 8 0 AAAAAAAAAAAAAAAAAAAAAAA *

G 0 6 5 7 0 7 5 8 0 FREQUENC Y INT . 4 5 4 4 3 2 1 0 13 0 0 0 0

- 0 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 CUM . 4 5 4 4 5 8 4 6 1 4 6 3 4 6 4 4 G 4 4 G 4 4 0 4 4 6 4 4 0 4 4 6 4 4 6 4 4 0 5 4 G G 4- 6 f l 4 0 3 4 G' J 4 0 n 4 6 C l 4 G3 4 0 0 4 0 (. 1 4 0 0 4 0 0 4 Oi l 4 0 0 4 •'.'> 0 4 l i 0 4 0 9 4 0 9 4 0 9 4 7 0 4 / 0 4 7 0 4 7 0 4 7 0 4 7 0 4 7 0 PERCENTAG E

INT . 96. 6 0 . 9 0 . 6 0 . 4 0 . 2 0 . 0 0 . 0 0 . 0 0.0 0.0 0.0 0.0 0 . 2 0 . 2 0 . 4 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 2 0 . 0 0 . 0 0 . 2 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 CUM .

96. 6 97. 4 9 8 . 1 9 S . 5 90. 7 98. 7 98. 7 98. 7 98. 7 98. 7 90. 7 98. 7 90. 9 9 9 . 1 99. 6 99. 6 99. 6 9 9 . G 99. G 99. 6 99. 6 9 9 . G 9 9 . G 9 9. 6 99. 6 9 9 . G "99. 6 9 9 . G 99. 8 99. 8 99. 0 100. 0 1 0 0 . 0 100. 0 10.7. 0 1 0 0 . 0 1 0 0 . 0 170. 0 Numbe r o f Site s

FIGURE A-3a . Histogra mo f expecte d primar yexceedances , E , fo r thos e site s reporting 24-hour S0 2 concentration s i n 1981 : SLAM S (includin g NAMS) . 8311+ 6EA C E + — *
. G7.70.7. 7 +8IJ O M .20.0.7. 7 + BBB C * 1 .0.0.00 0 +0 o * 2
. 4.7.0.0. 7 H- B * 3..0.7.0.0. 7 + B B * 3
. 0.0.7.0. 7 + B * 4
. 2 00.7. 7 + B * 4 .09.00. 7 + * 5
. 4.7.00. 7 + * 6.007.7 0 + "6. 0 0. 0 07

7 + * 7 .2 0 07 7 + * 7
. 07.70 0 + A; j
_. ; .1.100 0 + '•'9.000.0. 7 • * 9
. 60.0.7 0 + * 10
. 20.0. 7 + "10.0.70 0 + * 1 1
. 4 00 0 + '12.0.0.0. 7 + * 12
. 0.0.0. 7 + -13.270 0 + * 13
. 0. 0 0. 7 + * 14
. 4 0.07 7 + * 15.0.0.0. 7 + * 15
. 600. 7 + * 1 G
. 2.0.0 0 + * 1 G
. 0.70. 7 + * 17
. 4.7.0 0 + * 1 0
. .70 ' 7. 7 + * 18
. 0 0 0. 7 + * I 9
. 200. 7 + * 19.000 0 + • * 20.400 0 + * 21.000 0 + *21.000 0 + * 2 2
. 2.00. 7 • * 22.000 0 + 1 0 1 !

GUB
. BEiB'
. L - ' 3 B £C u 3 0 b U B S Y H SYMBO L 2 0 2 5 + ;

- - '_ > 0 L > B 3 0 U •

. M70 L B Kill * R E 3. 7

. - ; . — •L i 7 2 ' 3 B COUN T

4 2 1 SLUT S MEA NST.DEV .

0.06 7 0.30 0 1 OBSERVATIO N 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 f ( . ( 1 1 1 . + + + + BliUBBBCBUBBBBBbDBBBBBU'BBBBBU B BBBBBBBBBBBBBBBBBBBB * FREQUENC Y INT . CUM . 40 4 1 0 2 1 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

. 7 0 0 0 0 0 0 0 0 0 0 0 0 40 4 41 4 41 6 41 7 41 9 4 2 0 42 1 42 1 42 1 4.21 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 4 2 1 4 2 1 4 2 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 PERC E INT . 96. 0 2. 4 0. 5 0. 2 0. 5 0. 2 0. 2 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0 . 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 NTAC E CUM .

. 0

. 3

, C

. 0

. 5

, 8

. 0 .0 .0 96 . 99 , 93 . 99 . 99 . 99 , 100 . 100 . 100 . 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100 . 100 . 100 . 10 0 . 100. 0 10.7. 0 10.7. 0 10 0 . 0 1.70. 0 10 0 . 0 1.7.7. 0 . 0

. 0

. 0

. 0

100: 1 1.7 0 10 0 1 0. 7 1.7. 7 10.7. 0 1.7. 7
. . 7 10.7. 0 1 7 7. 0 1.7 0
. 0 1.7.7. 0 1 0.7. 0

•- + - 1 0 2 0 - - + - 2 5 3 0 3 5 - - + - 4 0 - - + - 4 5 - - + - 6 0 • - + -

7 0 - - +

8 0

8314 6 FIGUR E A-3b
. Othe rsite sP.2 0

SLAM S , SYMB0L= S OTHE R, SYMBOL= 0 N = 89 1 COR = .081 3 MEAN 70.45 7 .1263 2 ST.DEV .

26.07 3 1.067 9 REGRESSIO NLIM E RES.MS .

X = 1.S335-Y + 70.27 5 675.5 5 Y = .00333*X-.1073 0 1.13 4 1

, + * 10.0+

17. 5 +

15. 0 +

12. 5

10. 0

7.5. 7

5.J7

2 . 5 0 + O O
SOO S 0 

## s

s

0 0 

### s s 0*00 * 0* * 0.0 0 y*Q*Q****QQ**Q##*rt**********"***Q*****Q rt** *rtrt***rtrt*rt***:7 . rt rtrtrt 7" : rtrtrtrtg y +....+....+....+....+....+....+....+....+....+X...+....+....+....•....+
. 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 .00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0



### FIGUR E A-4 . Scatte r plo t o f th e percentag e o f tota l day s recorde di n198 1 (p ) versu s expecte dprimar y exceedance s (E ) fo r site s reportin g24-hou r averag e SCL 83H* 6TABL E A-3 . Frequencytabl e o f th e percentag e o f tota l day s recorde d in 198 1 (p )

versu s expecte d primar yexceedance s (E ) fo r site s reporting 24-hou r S0 ? averages .

0 - 28 X 43 X < » 60.5 X < - 71 X B0X 86 X 89. 5 X 93 X<- . 96. 5 X< - 100 X TOTA L 0 1 < - 2 < - 5 < » 2 0 TOTA L 8 7 0 0 1 0 8 8 8 8

fi 0 0 0 8 8 8 7

0 0 0 0 8 7 8 8

0 1(SI 0 9 1 8 8

0 5 1 0 9 4 8 1 7

0 1 1 0 8 3 7 7

fj 3 0 0 8 0 8 7

2 1 0 3 9 3 10 2

2 0(SI 2 10 8 7 3

A 1 0 1 7 9 8S 8



### e 1 2 7 6 89 1

8314 6
T J

### Appendi xB CARBON MONOXID E DESCRIPTIVE STATISTIC S

8314 6 5P.2 3

APPENDI XB CARBON MONOXID E DESCRIPTIV E STATISTIC S
Figur e B- l show s th e distributio no f dat a completenes s amon gai r monitor in gstations . Tabl e B- l show s th e numbe r o f site s meetin ga nannua l quot a o f 7 5 percen t dat a completenes s an dmeetin ga correspondin gquarterl y quot a ina specifie dnumbe r o f quarters . Tabl e B- 2 show s th e same informatio nfo r a

nannua l quot a o f 5 0 percent . Not e tha t roughl y 8 0 percen t o f th e site s tha t me t a nannua l quot a als o me t a correspondin g quarterl y

quot a ineac ho f th e fou r quarter s o f 1981 . Histogram s o f one-hou r expecte dexceedance s show tha t zer o expecte d exceedance s wer e reporte db y 9 9 percen t o f th e station s (Figur e B-2) . A scatte r diagram

o f expecte done-hou r exceedanc e versu s percentag e o f dat a completenes s i s presente dinFigur e B- 3 an dinTabl e B-3 . Simila r informatio nfo r overlappin geight-hou r exceedance s i s show ni n Figure s B- 4 an

dB- 5 an

dinTabl e B-4 . Mor e tha n1 0 percen t o f th e station s reporte dove r 4 0 expecte dexceedances . N o clea r relationshi p betwee nexpecte dexceedance s an ddat a completenes s i s evident .

8314 6 5

### p

* 3
. .7000. 7 * G .007''0 7 * 9
. JU.70.7
. J *12.0.7A' 0 * 1 5
. 00/7. 7 * 18..07.'.'.. f * 2 1 .0.7.' A> *'AA ' ..707. 7 * 2 7..'J,.,. 0 *.J0.0..'0. 7 * 3 3
. f)'ifi 7 * 3 G ..'10.0. 7 * 3 9.0. 0 0. 7 * 4 2 .0.00 0 * 4 5 .07.'.0. 0 * 4 o .0.00. 7 * 5 1 0"'i-"---T * 5 4 ..U.'J.O.' J *57.00.0. 7 * 3 0
. 00.0. 7 * 63..0.0.O. J * GO.'0.7.7 0 * G 0.0.0
. ::•..' * 7 2.000
. j * 7 5
. 0'fy. 7 * 7 0.0.0:7 ; J * 3 1 7 0770 7 * U 4 .000. 7 * 0/
. .0.7.0. 7 *y.O..'/.«'.'0. 7 "•03.0. 7 0. 7 * JO
. 0 0.0. 7 *9'J..O.o.O 0 * 102..0.0. 7 * 1.0 5 .0.0 0 *lu:j
. "'' 7 * 1 11 .00 0 * 1 1 4.00 0 SYMBO L COUN T A36 4 EAC H SYMBO L REPRESENT S 5 1 0 1 5 2 0 2 5 3. 7 3 5 4 0

•A •A •A ' •AA A •A A + •A •AAAAA A •v ^ \AAA A •AA A •A A •AAA A •AA A •AAAAAA A •A •AAAAA A •A A + '•AA A •AA A •AA A*\AA A •AAAAAAA A + A.\A.'\A.\AA A •AAAAA A
•AA."
. AA AAAAA A •AAAAAA A •AAAAA A •AAAAAAAAAAAAAA A + AAAAA;*- 1 "

•\<VA A +AAAAAA.V.AAAAAAAAAAAAAAAAAAAAAAAA A MEA N ST.DEV . 80.35 3 23.13 8 1 OBSERVATIO N 4 5 5 0 5 5 6 0 6 5 7 0

•AAAAA/-..' .AAAAAAA.V\AAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A
' + AAAAA;'.,'.
. \AAA
. '.AA AAA AA AAAA AA AAA AA AA AAA AAA AAfi .AAAAAAAAAAAAAAAAAAA A •A."..'.
. '.AAA
. :-.AAAAAAAA, a ,'^AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A
+ + + + 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5

7 5 8 0

8 0 FREQUENC Y INT . 1 1 1 3 ' 2 0 1 6 8 3 2 4 3 7 . 1 6 2 0 3 3 7 8 9 6 1 1 7 6 1 5 1 2 3 3 4 7 6 1 7 0 1 5 0 0 0 0 CUM
.

1 2 3 6 8 8 9 1 5 2 3 2 6 2 8 3 2 3 5 4 2 4 3 4 9 5 1 5 1 5 4 5 7 6 4 7 2 8 1 8 7 9 0 1 0 6 1 1 1 1 2 6 1 3 8 1 7 1 2 1 8 2 7 9 3 4 9 3 6 4 3 6 4 3 6 4 3G 4 3 6 4 PERCENTAG E

INT . 0 . 3 0 . 3 0 . 3 0 . 8 0 . 5 0 . 0 0 . 3 1 . 6 2 . 2 0 . 8 0 . 5 1 . 1 0 . 8 1 . 9 0 . 3 1 . 6 0 . 5 0 . 0 0 . 8 0 . 8 1 . 9 2 . 2 2 . 5 1 . 6 3 . 0 1 . 9 1 . 6 4 . 1 3 . 3 9 . 1 ' 12. 9 16. 8 19. 2 4 . 1 0 . 0 0 . 0 0 . 0 0 . 0 CUM .

0 . 3 0 . 5 0 . 8 1 . 6 2 . 2 2 . 2 2 . 5 4 . 1 6 . 3 7 . 1 7 . 7 8 . 8 9 . 6 11. 5 1 1 . 8 13. 5 14. 0 14. 0 14. 8 15. 7 17. 6 19. 8 22. 3 23. 9 26. 9 28. 8 30. 5 34. 6 37. 9 47. 0 59. 9 76. 6 95. 9 100. 0 100. 0 100. 0 100. 0 100. 0 Numbe ro fSite s

8314 6 FIGUR E B-la
. Histogra m o fth e percentage , p , o fdat a completenes s fo rthos e site s reportin g C O i n 1981 : SLAM

S (includin g NAMS)
.••



### p
* 3.0000 0 * 6 . .0.7.70 0 * 9 .07.00 0 * 12 . 00.0 0 * 1 5 .0.0.7. 7 * 1 o . .7.0.7 0 * 2 1 .0.0.7 0 * 24 . 7''-'"' f * 2 7.00.00 7 * 30.0.0.0. 7 * 3 3..0.7:7 0 * 3 0.00:7 0 * 3 9 f •" ' '

> '} * 4 2 . 0.0.7: 7 * 4 5.0. 0 7. 7 .* 4 0..7r77. 7 * 5 1 .007. 7 * 5 4.00.0. 7 * 5 7.00.7. 7 * G0.0.0.7. 7 * 63.00.07 7 * 6 6.007. 7 * 6 9.007. 7 .- * 72.0.0.7 0 *7 5 nrc-'/ j * 7 U . 07.0. 7 * 3 1 .0.00. 7 •3 4 .000 7 * 3 7.0.07 ) . 7 * 90.0.7.0. 7 * 9 3.0.0.0. 7 * 9 G. 00'0 0 * 9 9 .000. 7 * 102.0.0 0 * 1. 0 5..077 0 •108.00 0 •111 . 00. 7 * 1 1 4 . .0.7 0

8314 6 • •

EAC H S Y 5 1 0 1 5 2 0 .•Lit } + CIS B + C B + B + L; B
• UL , • LiL.nC + .v: . i',:.-.3 3
• OOB B + U0 C + !',:L:I!D 7 • Coll! " + 1 7 0 07' , B
• UOL B
• C B + + B + + B + + 03 B + G
• lA'O B +BBBB B
• C B + +I;L.[; B

• UL. B + B + D7,;.733BBBBB B
• CO.'UB^iBBBBBB B +CLBBB7 B
• BBLBBiiB B + + + + + 5 1 0 1 5 2 0

----- - • • •

SYMBO L COUN T MEA NST.DEV . B 11 6 58.95 2 31.63 1 •IBO L REPRESENT S 1 OBSERVATIO N 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0

2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0

Numbe r o f Site s

FIGUR E B-lb . Othe r sites .

--..-.

_—.. . —. . _. — 6 5

6 5

. - . •

7 0

7 0

—. . 7 5

7 5 •

8 0

8 0

. %

FREQUENC Y INT . 2 3 2

, 1 2 2 4 6 4 3 6 4 5 4 2 0 1 0 1 0 3 1 4 5 2 0 4 3 1 1 2 1 4 7 8 0 0 0 0 0 CUM . 2 5 7 8 1 0 1 2 1 6 2 2 2 6 2 9 3 5 3 9 4 4 4 8 5 0 5 0 5 1 5 1 5 2 5 2 5 5 5 6 6 0 6 5 6 7 6 7 7 1 7 4 7 5 8 7 10 1 10 8 11 6 11 6 11 6 11 6 1 1 6 11 6 • •

PERCENTAG E INT . 1. 7 2. 6 1 . 7 0. 9 1 . 7 1 . 7 3. 4 5. 2 3. 4 2. 6 5. 2 3. 4 4. 3 3. 4 1 . 7 0. 0 0. 9 0. 0 0. 9 0. 0 2. 6 0. 9 3. 4 4. 3 1 . 7 0. 0 3. 4 2. 6 0. 9 10. 3 12 . 1 6. 0 6. 9 0. 0 0. 0 0. 0 0. 0 0. 0 CUM .

1 . 7 4. 3 6. 0 6. 9 8. 6 10. 3 13. 8 19. 0 22. 4 25. 0 30. 2 33. 6 37. 9 4 1 . 4 43. 1 43 . 1 44. 0 44. 0 44. 8 44. 8 47. 4 48. 3 51. 7 56. 0 57. 8 57. 8 6 1 . 2 63. 8 64. 7 75. 0 87 . 1 93 . 1 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0P.2 6



### TABL E B-l . Numbe r o f site s recordin gC Odurin gat leas t 7 5 percen t o f th e tota l possibl e hour s in1981 , b y th e numbe r o f quarter s i n whic ha t leas t 7 5 percen t o f th e tota l hour s pe r quarte r ar e recorded .

Sit e Typ e SLAM S (in c

Othe r :lude s 

### No .

w i 75%

NAMS ) o f Quarter s t ha t Leas t Hours/Quarte r 

### 0 1 2 3 4 Tota l 

### 0 1 2 3 4 Tota l N o . o f

> 75 % 

### 0 0 5 5 3 212 "270 " 

### 0 0 0 1 7 33 "50 " Site s

< 75 % 

### 1 5 37 33 9 0 "9 4 1 7 3 5 8 6 0 "66 " Tota l



### 1 5 37 38 62 21 2 "364 

### 1 7 35 8 23 3 3 

## Tl ?

TABL E B-2 . Numbe r o f site s recordin gCOdurin gat leas t 5 0 percen t o f th e tota l possibl e hour s in1981 , b y th e numbe r o f quarter s inwhic h at leas t 5 0 percen t o f th e tota l hour s pe r quarte r ar e recorded .

Sit e Typ e SLAM S (include s

Othe r 

### No . o

f wit h 

### 50 %

NAMS ) Quarter s

a t Leas t Hours/Quarte r 

### 0 1 2 3 4 Tota l 

### 0 1 2 3 4 Tota l N o . o f Site s

> 50 % 

### 0 0 1 0 42 261 "313 " 

### 0 0 1 1 6 49 

## 1J6 " < 50 %



### 7 23 20 1 0 

## Jl 9 30 1 1 0 0 "5 0 Tota l



### 7 23 3 0 43 26 1 

## 364 " 9 30 1 2 16 . 49 11 6

831U 6 8••

E

*
. 3.7.700 0 '•''
. 00.000 0 • :

. 9.00.00 0 * 1
. 200.0. 7 * 1
. 50.0.7 0 * 1 .170.0.0 0 •'•• 2
. 1.0.00 0 •••2
. 4.70.0 0 ft 2. /.O.O7 0

- 3 .0.0.00 0 ••'•'3
. 30.0.7. 7 •••3.''0. 0 0 0 " 3 .90.00. 7 -4.2000/ 7 v -' 4 .!" ' 00 7 <~

f * 4
. l i .0.0.0. 7 *5.1000 0 * 5
. 4 00.0. 7 * 5
. 70.0.0. 7 *6.0000 0 * 6
. 30.00. 7 * 6
. 6 00.0. 7 * 6
. 9.0.00 0 * 7
. 2.0.0.7. 7 * 7
. 5000. 7 * 7 .30.00 0 ''••Xi. 101''f- f7 * 3
. 4 0.00. 7 * 3
. 700.0 0 * 7
. fiiin.0 0 * 9
. 3000 0 * 9
. 600.0 0 * 9
. 90.00 0 * 10
. 2.0.0 0 * 10
. 5.00 0 * 10
. 8.00 0 *11.100 0 * 1 1
. 400 0

8314 6

- - - - - ••••• •

SYliBO LCOUN TMEA N ST
. DEV
. A.7, 4 0..7G 0 .7.09 1 EAC H SYliUO LREPRESENT S 1 OBSERVATIO N 5 1 0 1 5 2 0 2 5 3. 7 3 5 4 0 4 5 5. 7 5 5 G 0 6 5 7 0 7 5 8 0 •AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA-AAAAAAAAAAAAAAAAAAAAAAAA A + + + • A + + A + + + + + + + + + • + + + + + + + + + + •A + + + + + + • A + + •4 - + 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 6 5 0 5 5 6 0 6 6 7 0 7 5 8 0 Numbe ro fSite s FIGUR E B-2a
. Histoqra m o fexpecte d primar yexceedances , E , fo rthos e site s reportin g one-hou rC O concentration s i n 1981 : SLAM S (includin g NAMS

)

- . - - - - - - ..... . .. . • . _. . _ . . ._.... . ....._ . _ . . •

FREQUENC Y

INT
.

* 30 0 0 0 0 1 0 l 0 0 0 0 0 0 H 0 0 ll kl 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1

. 7 0 0 0 -

^^^^ M CUM
.

3 0 0 3!;. 7 "6 <J I'J 3 0 0 3 6 1 3 0 1 UCi 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 6 2 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 0 2 3 7 2 3 0 2 3 0 2 3 0 3 3 0 3 .36 3 3 0 3 3 0 7 3 0 3 3 6 3 3 0 4 3 0 4 3 0 4 3 0 4 3G 4

- •

PERCENTAG E INT
. 9U. 9 0 . 0 0 . 0 0 . 0 0 . 3 0 . 0 (J
. U 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 3 0 . 0 0
. 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 3 0 . 0 0 . 0 0 . 0 0 . 0 CUM
.

9 8. 9 9 0
. 9 9 3. 9 90. 9 9 9
. 2 9 9. 2 0 0
. D 9 9. 5 9 9. 6 9 9. 5 9 9. 5 99. 5 9 9
. 5 9 9
. 5 9 9. 5 9 9. 5 99. 5 9 9. 5 9 9. 5 99. 5 9 9. 5 9 9. 5 9 9. 5 9 9. 5 9 0. 5 9 9. 5 9 9. 7 9 9
. 7 9 9. 7 9 9
. 7
' 9 9
. 7 9 9. 7 99. 7 1.7.7. 0 10.7. 0 1.70. 0 1.0. 0
. 0 100. 0 •30000 0 60000 0 90000 0 2000 0 5000 0 8000 0 1000 0 4000 0 7000 0 0000 0 3000 0 6000 0 9000 0 2000 0 5000 0 8000 0 1000 0 4000 0 7000 0 6.0000 0 6.3000 0 6000 0 9000 0 2000 0 5000 0 8000 0 1000 0 *8.4000 0 * 8.7000 0 *9.0000 0 * 9.3000 0 * 9.6000 0 •9.9000 0 •10.200 0 •10.500 0 •10.800 0 •11.100 0 •11.400 0 * 1 . * 1 . • 1 . • 2 , • 2 , • 2 . •3 . •3 . •3 . •3 . • 4 . • 4 . • 4 . •5 , •5 . •5 . SYMBO L COUN T OTHE R B 11 6 EAC H SYMBO L REPRESENT S MEA NST.DEV . 0.09 4 1.01 2 1 OBSERVATION S 1 0

• - + - 1 5 2 0 2 5 3 0 3 5

- - + - 4 0

- - + - 4 5

- - + - 5 0

- - + - 6 0

- - + - 6 5

- - + - 7 0

- - + - 7 5 8 0

- - + FREQUENC Y INT . CUM . + + - +BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBUBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * + • + + + + + + + + + + + + + + + + + +

• - + -

1 0 • - + - 1 5 - - + - 2 0 - - + - 2 5 - - + - 3 0 - - + - 3 5 - - + - 4 0 4 5 5 0 - - + -

5 5 - - + - 6 0 - - + - 6 5 - - + - 7 0 - - + - 7 5 - - + 8 0 Numbe r o f Site s 11 5 0 0 0 • 0 0 0 0 0

. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 l 0 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 11 5 1 1 5 11 5 1 1 5 11 5 11 5 11 5 11 5 1 1 5 11 5 1 1 5 1 1 6 11 6 PERCENTAG E INT . CUM . 99 . 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 9 0. 0 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99. 1 99 . 1 99. 1 99 . 1 99. 1 99 . 1 99 . 1 99 . 1 99 . 1 99. 1 99 . 1 99 . 1 99. 1 99 . 1 99 . 1 99. 1 99 . 1 99. 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 99 . 1 100. 0 100. 0

FIGUR E B-2b . Othe r site s 8314 6P.2 9

SLAM S OTHE R N
- 48 0 COR=-.006 8 MEA N X 75.23 4 Y .0679 2 SYMBOL= S

SYMBOL= 0

ST.DEV . 27.01 5 .7794 3 REGRESSIONLINE RES.MS .

X=-.23588*Y + 75.25 0 731.2 9 Y=-196E-6*X + .0826 9 .6087 6

, + . .X . + . 12. 0 +

10. 5 +

9.0 0 +

7.5 0

6.0 0

4.5 0

3.0 0 +

1.5 0 +
0.0 0 Y* 0 0* * S** 0 0***** * "*0*S***0 * SS * •SSS***S*****SSS************** S Y .+....+....+....+....+....+....+....+....+....+....X
. .. . + ... . + .. . . + ... . + . 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0.00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0



### FIGUR E B-3
. Scatte rplo to fth e numbe ro fexpecte d primar yexceedance s (E ) versu s th e percentag e (p ) o ftota l hours recorde d i n 198 1 fo rsite s reportin g one-hou rC

O concentrations
.

8 311* 6TABL E B-3 . Frequencytabl e o f the percentag e o f tota l day s recorde d in 198 1 (p )

versu s expecte d primar yexceedance s (E ) fo r site s reportin g 1-hour CO averages .


## E 0 < - 1 1 0 - • 26 X

4 6 1 < = 46.5 X

4 8 0 <=• 71 %

5 0 1 < - 83 X

4 6 0 < - 90%

6 5 1 

## P O91.5 X

2 8 1 < - 94 X

5 0 1 < - 96 X

4 8 0 < - 97.5 X< - 100%

4 3 5 1 1 0 0 1 i TOTA L 47 5
TOTA L 4 7 4 8 5 1 4 6 6 6 2 9 5 1 4 8 4 3 5 1 I 48 0

8314 6EAC H SYMBO L COUN T A3G 4 SYMBO L REPRESENT S MEA NST.DEV . 34.30 1 112.44 9 1 OBSERVATIO N
•40.000 0 •80.000 0 •120.00 0 •160.00 0 •200.00 0 •240.00 0 •280.00 0 •320.00 0 •360.00 0 •400.00 0 •440.00 0 •480.00 0 •520.00 0 •560.00 0 •600.00 0 •640.00 0 •680.00 0 •720.00 0 •760.00 0 •800.00 0 •840.00 0 •880.00 0 • 9 20.00 0 •960.00 0 •1000.0 0 •1040.0 0 •1080.0 0 •1120.0 0 • 1 160.0 0 •1200.0 0 •1240.0 0 •1280.0 0 •1 3 20.0 0 •1360.0 0 •1400.0 0 •1440.0 0 •1480.0 0 •1520.0 0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0

+ + + + • + + + ^ + *

( . ^ + + + 1 . + +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA * •AAAAAAAAAAAAAAAAAA A •AAAAAA A •AAAAAAA A • AA A AAA A A AA A A A A A AA A FREQUENC Y PERCENTAG E INT . CUM . INT . CUM .

+ +
• A

1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 30 9 1 9 7 

### a 3 4 1 3 2 2 3 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3.0 9 32 8 33 5 34 3 34 6 35 0 35 1 35 4 35 6 35 8 36 1 3G 1 36 1 36 1 36 2 36 2 36 2 36 2 36 2 36 2 36 2 36 3 36 3 36 3 36 3 36 3 30 3 36 3 36 3 3 6 3 36 3 36 3 36 3 36 3 36 4 36 4 36 4 36 4 84. 9 5. 2 1 . 9 2. 2 0. 8 1 . 1 0. 3 0. 8 0. 5 0. 5 0. 8 0. 0 0. 0 0. 0 0. 3 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 3 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 3 0. 0 0. 0 0. 0 • 8 4 9 0 9 2 9 4 9 5 9 6 9 6 9 7 9 7 9 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 0 10 0 10 0 10 0 9 1 0 2 1 2 4 3 8 4 2 2 2 2 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 7 7 7 0 0 0 0 Numbe ro fSite s

8314 6 FIGURE B-4a . Histogra mo f expecte d primaryexceedances , E , fo r thos e site s reporting 8-hour CO concentration s in 1981 : SLAM S (including NAMS )

## E •40.000 0 •30.000 0 •120.00 0 •160.00 0 •200.00 0
• 2 40.00 0 •280.00 0 •320.00 0 •3G0.00 0 •400.00 0 •440.00 0 •480.00 0 •520.00 0 •560.00 0 •600.00 0 •640.00 0 •600.00 0 •720.00 0 •760.00 0 •800.00 0 •840.00 0 •880.00 0 •920.00 0 •960.00 0 •1000.0 0 •1040.0 0 •1000.0 0 •1120.0 0 •11G0.0 0 •1200.0 0 •1240.0 0 •1200.0 0 •1320.0 0 •1360.0 0 •1400.0 0 •1440.0 0 •1480.0 0 •1520.0 0 SYMBO L COUN T MEA NST.DEV . OTHE R B 11 6 28.34 8 90.30 0 EAC H SYMBO L REPRESENT S 1 OBSERVATION S 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 +BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * • BBB B + B + B + B + + B + B + B + B + B + + + + B + + - + + + + + + + + + + + + + + + + + + + + + 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 FREQUENC Y INT . 10 3 4

• 1 0

0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 CUM . 10 3 10 7 10 8 10 9 11 0 1 1 0 1 1 1 11 2 11 3 114 11 5 1 1 5 1 1 5 11 5 11 6 11 6 11 6 11 6 1 1 6 11 6 11 6 11 6 11 6 11 6 1 1 6 11 6 1 1 6 1 1 6 11 6 1 1 6 11 6 11 6 1 1 6 11 6 11 6 11 6 11 6 11 6 PERCENTAG E INT . 88. 8 3. 4 0. 9 0. 9 0. 9 0. 0 0. 9 0. 9 0. 9 0. 9 0. 9 0. 0 0. 0 0. 0 0. 9 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 CUM . 83. 8 92. 2 93. 1 94. 0 94. 8 94. 8 95. 7 96. 6 97. 4 98. 3 99. 1 99 . 1 99 . 1 99 . 1 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 10 0 . 0 100. 0 Numbe ro fSite s FIGUR E B-4b
. Othe rsites , 8314 6SLAM S OTHE R SYMBOL= S

SYMBOL- 0

140 0 +

122 5 +

105 0

875 .

700 .

525 .

350 .

175 .

0.0 0 N = 48 0 COR=-.037 6 MEA N X 75.48 2 Y 32.86 2

OS " ST.DEV .

27.26 0 107.4 6 ,+X . REGRESSIONLINE RES.M S X=-.00953*Y + 75.79 5 743.6 3 Y=-.14812*X + 44.04 3 1155 5

Y S O +* 0 0* * S*0 0 00****S0«** * *S*SO*S S 0 s 

### s s s 0 s 

### s s O S s 

### s s s s s s s s s s s S O S s s 

### o s*s* * s**s s s s s ssos s s s osss**os********s**s*s********* s i-1.. . + ... . + ....+X.. . + ... . + ... . + .. • 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0.00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0



### FIGUR E B-5 . Scatte r plo t o f th e numbe r o f expecte dprimar yexceedance s (E ) versu s th e percentag e (p ) o f tota l hour s recorde di n198 1 fo r site s reportin g8-hou r C Oconcentrations .

8314 6TABL E B-4 . Frequencytabl e o f the percentag e o f tota l days recorde d in 198 1 (p )

versu s expecte d primaryexceedance s (E ) fo r site s reportin g 8-hour C O averages .

0 25. 5 46 X< = 70.5 X< - 82.5 X< - 89 X< - 91.5 X< - 94.5 X< - 96.5 X< - 98.5 X< - 100 X TOTA L 0 1 - 5 < - 1 0 <=• 5 0 < - 10 0 < - 140 0 TOTA L 3 6 0 1 3 0 6 4 6 3 1



### a 5 7 1 5 4 9 3 1

3 3 7 3 3 5 0 2 9

3 6 6 1 3 4 8 2 7

5 4 5 1 4 4 6 3 1

1 3 9 0 2 4 6 2 6

7 5 4 2 6 5 0 2 1

6 5 1 2 0 1 4 5 2 5

S 0 1 5 3 4 5 2 2 1

2 1 1 1 4 9 4 8 27 8

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

8314 6

### Appendi xC NITROGEN DIOXID E DESCRIPTIV E STATISTIC S

8314 6 5P.3 6



### APPENDI XC NITROGE N DIOXID E DESCRIPTIV E STATISTIC S
Figur e C- 1 show s th e distributio no f dat a completenes s amon gai r monitor in gstations . Ther e ar e lo w correlation s betwee nth e percentag e o f dat a completenes s an

dreporte dannua l averages , standar ddeviations , an d coefficient s o f variatio n(Figur e C-2) .

8314 6 5U J •I O " 3 S i C l C l O l • « s3 C O ( ^ CS

I CS J V O mm 5 5 L O - C C l C l -C

O & LN I O S l 3 ! C l r ~ —•« •C M L O rv . L O 3 : S l 3 ! S i S 3 ws : < z> ^ —> cs i cs i cs l C

M ^ v o C i 5 : —

, c o L O o c i S ; cs i - o v o r ^ c i ,-N J o ro mm m _- . ,-v . t - n __ CM c o ff: 5 ; S ; S ; S i t - O rt rt rt rt rt rt C M C M .N J CS J ,\ J ,S J 0 1 C O C O K T* * L O L O V O CS C O C l C l 3 ; v vS i 3 ; 3 1 2 mmrt m« mmm* LU < J •I O L

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se dSLAM S , 5YMD0L= 5 OTi-IE R , SYMDOL= 0 N= 32 4 COR = .092 4 MEA N ST.DEV
. REGRESSIO N LIN E RLS.KM
. X64.23 1 2 S
. tZ 7 X = .11430-Y + 5U.27 5 7 3 !
. J u Y43.24 7 22.53 7 Y = . .074 4 3 : -;< + 33.43 5 50/.3 3

1 40. 0

ta . CS J O c r o O J 7 0
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7.50. 7 22.5. 7 37.5 5 52.5 0 67.5 0 82.5 0 97.5 0 0.00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 \Z.



### FIGUR E C-2a . Scatte r plot s o f ambien t ai r qualit y statistic s versu s th e percentag e o f tota l hour s recorde di n198 1 (p ) b y site s reportin g N 0 2 

### : annua l averag e versu s p .SLAM S OTHE R , 5YMDOL= S

, SYMBOL= 0 N = 32 4 COP. = .00 4 4 MEANST.DEV . X 64.23 1 23.02 7 Y 27.53 5 13.33 5 REGRESSIO NLIN E R E S.MS . X = ...-.I';'

J 2 * Y + 63.33 5 737.3 6 Y = .0.3 2 1 9 •••;:

+ 2/..14 5 193.3 9

S S O O

+ 0

. 0 7 0 0



### 0 s o oo s 0 0 0 s o s

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0 0 0 0 . 00

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### s s o

O S S S

0 S O S

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### s s 0 ••S * 0 0 0-

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_ , j , . . ._ . j S O 0 0 3 3 S 3 J J 3-A :; J ' S 3 " S O 03 S 3 S 0 0 0-0 0 3"0 . 3 3 0 0 0 0 0

7.30 0 ..•....•....•....•....•..•.+....+..X.+... .

22.3 0 37.2 0 52.5 0 67.5 0 n ? nc ; 13.0 0 30.0 0 45.0 0 60.0 0 75.0 0 UL.J S 97.5 0 90.0 0 105. 0



### FIGUR E C-2b . Standar ddeviatio nversu s p .P.4 1

SLAM S , SYMDOL= S Oi/liiR ' , 3Yi-iBOL= 0 N = 32 4 COR--.143 0 iiEA NST.DEV . REGRESSIO NLIN E RES.HI , •' 6-1.23 1 23.027 . X= -2. 3 . 1 39 * Y+ 77,;0 6 /IJ.I. Y,J/30 4 .2035 1 -Y= -..:.J103*X + .7427 7 .0414 C

X. . + .

0 0 

### s 0 0 0 0 0 0 OJ 0 J O s 3 S 30033 0 0 0 3 0 00 3 3 - J - 0 3 S O S 3 * 3 0 0 S 3

0 0 3 0 0 0 ' 0 0 0 S S 3 S S

SOOO 0 0 0 *3 S S S O 0 0 S * S 0* 0 03 S 3 3 S* 0 5 0 SJO S * 3 3 0 3 3 3 S S 33 0 03 3 3 S SS O 0 * S 3 3 3 S S 3"3"3- ; -'-"-- t 0 0 3 - 0 SS O SSO S 3 3-0'""3 3 •M J3 3 3- : S- •• •3 3 S 0J3 0 S 0 - ViS J : .3-3-33S S

3 0 3 SO 0 3 3 0 33--303 S S 3 SO 0

1 .y. 0
. . . + ... . + ... . + ... . + ... . + ... . + ... . + ... . + ..X
. + . .. . + . . . . + .... + . !2.3 0 37.3 0 52.3 0 67.3 0 32.3 0 9/.3 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0



### FIGUR E C-2c . Coefficien t o f variatio n(standar ddeviatio n divide db

y annua l average ) versu s p .P.4 2



### Appendi xD OZON E DESCRIPTIV E STATISTIC S

831A 6 5P.4 3

APPENDI XD OZON E DESCRIPTIV E STATISTIC S
Figur e D- 1 show s th e distributio no f dat a completenes s amon gai r monitor ingstations . Histogram s o f "expected " exceedance s (i.e. , x. or k./p . inth e notatio no f Sectio n2 ) sho

w tha t roughl y

8 5 percen t o f th e station s reporte dseve no r fewe r expecte dexceedance s in198 1 (Figur e D-2) . (Thes e statistic s ar e purel y fo r descriptiv e an dcomparative.purpose s an dd o no t directl y pertai nt o th e attainmen t o f th e ambien t standard , sinc e thi s i s determine dfro

m thre e year s o f data , no t fro m a singl e year. ) Somewha t greate r expecte dexceedance s wer e reporte db y station s havin gnearl y complet e data ; 4 percen t o f th e station s reporte dzer o expecte dexceed ance s (Figur e D- 3 andTabl e D-1) . Judgin gb y Tabl e D- 1 an

dth e lo

w correlatio ngive ninFigur e D-3 , n o clea r relationshi pi s eviden t betwee n expecte dexceedanc s an ddat a completeness .

8314 6 5*3. 0000 0 * 6. 0000 0 * 9.00000 *1 2 *1 5 *1 0 *2 1 *24 *2 7 *30 *3 3 *3 6 *3 9 *4 2 *4 5 *4 8 *5 1 *54 *5 7 *G 0 *6 3 *6 6 *6 9 *7 2 •7 5 *7 8 *8 1 *34 *3 7 *9 0 *9 3 *9 6 *9 9 000 0 000 0 000 0 000 0 000 0 0000 000 0 000 0 000 0 000 0 00.0 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0

. 000 0 * 102.00 0 * 105.00 0 * 108.00 0 * 1l1.00 0 * 114.00 0 SYMBO L COUN T A54 8 EAC H SYMBO L REPRESENT S MEA N ST. DEV . 81.76 7 18.52 8 1 OBSERVATIO N 1 0 1 5 10 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0

•AAAAAA A • A • A •AAA • AAA A • A • AA • A A • AA A • AA A •AAAAAAAA A • AA A •AAAAAAA A •AAAAAA A •AAAAAAAA A •AAAAA •AAAAAAAAA A •AAAAAAAAAAAAA A •AAAAAAAA A •AAAAAAAAAA A +AAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAA A

1 0 —»•

- 1 5 2 0 2 5 3 0 3 5 - - + - 4 0 5 0 - - + -

5 5 6 0 • - + -

6 5 • - + - 7 0 - - + - 7 5 - - + 8 0 FREQUENC YPERCENTAG E INT . CUM . INT . CUM . 0 0 0 0 7 1 1 3 4 1 Z 2 3 3 9 3 8 7 9 5 1 0 1 4 9 1 1 1 2 2 6 2 7 3 1 5 5 5 1 6 2 7 3 7 8 2 1 0 0 0 0 0 0 0 0 7 8 9 1 2 1 6 1 7 1 9 2 1 - 2 4 2 7 3 6 3 9 4 7 5 4 6 3 6 8 7 8 9 2 10 1 1 1 2 12 4 15 0 17 7 20 8 26 3 31 4 37 6 44 9 52 7 54 8 54 8 54 0 5 4 0 5 4 8 0. 0 0.0 0.0 0.0 1 . 3 0. 2 0. 2 0. 5 0. 7 0 . 0 . 0 . 0 . 0 , 1 . 0 . 1 . 1 . 1 . 0. 1 . 2 . 1 . 2 . 2 . 4 , 4 . 5 . 10. 0 9. 3 11. 3 13. 3 14. 2 3. 8 0. 0 0. 0 0. 0 0. 0 0.0 0.0 0.0 0.0 1 . 3 1 , 1 , 2 , 2 3 3 . 3 4 4 6 7 , 8 9 1 1 12. 4 14. 2 16. 8 18. 4 20. 4 22. 6 4 3 38. 0 4 3. 0 27 . 32 . 57. 3 68. 6 81" . 9 96. 2 1 00. 0 100. 0 100. 0 100. 0 100. 0
Numbe r o f Site s

H ? ] i,( , FIGUR E D-la . Histogra m o f th e percentage , p , o f dat a completenes s fo r thos e site s reportin g 0- , concentration s i n 1981 : SLAM S (includin g NAMS) .SYMBO L COUN T B 17 5 EAC H SYMGO L REPRESENT S MEA N ST. DEV . 64.90 6 27.49 9 1 OBSERVATIO N 1 0 1 ! *3.0000 0 *6.0000 0 * 9.0000 0 * 12.000 0 * 15.000 0 •18.000. 9 * 2 1 .000 0 *24.000 0 * 2 7.000 0 * 30.000 0 •33.000 0 '36 . '39 . '42 . '45 , '48 . '5 1 . •57 . *G0 . *63 . •66 . •09 . •72 . •75 . •73 . •8 1 . •84 . •87 . *90 . •93 . •96 . •99 . 000 0 000 0 000 0 000 0 000 0 00.0 0 •54.000 0 0 0 0 0 000 0 000 0 000 0 .000 0 000 0 000 0 0.00 0 000 0 000 0 000 0 000 0 000 0 000 0 000 0 '102.00 0 '105.00 0 1 108.00 0 '11 1 . •114' . + + + • » + B •B B + B + +BBBB B + BB B
• E D
• B B
• BBB B +BBBCB B •BBBBBBB B
• BBB B + B3 B •BBBBB B
• B B +BBBB B
• BBB B + B
• B B + B R •BBBBBBB B +BBBB B • B B •BBBBBBB B •BBBBBBB B +BBBB B •BBBBBBBBB B •BBBBBB B •BBBBB B •BBBBBBBBBB B •BBBBBBBBBBBBB B +GBB3BBBBBBBB B +0BBBBGB3B B +BBBB B 2 0

- - + - 2 5 3 0 3 5 4 0 4 5

- - + - 5 0 5 5 6 0 6 5 7 0 7 5

- - + - 8 0

00 0 00 0 1 0 • - + - 1 5 - - + - 2 0 3 0 - - + - 3 5 • - + - 4 0 - - + - 4 5 - - + - 5 0 6 0 - - + -

6 5 - - + - 7 0 7 5 - - +

8 0 Numbe r o f Site s FREQUENC Y INT . CUM . 1 2 1 0 5 3 2 2 4 6 8 4 3 6 2 5 4 1 2 2 8 5 2 8 8 5 1 0 7 6 1 1 1 4 1 3 1 0 5 0 0 0 0 1 3 4 4 9 1 2 i a 1 6 2 0 2 6 3 4 3 8 4 1 4 7 4 9 5 4 5 8 5 9 6 1 6 3 7 1 7 6 7 0 O G 9 4 9 9 10 9 11 6 12 2 13 3 14 7 16 0 17 0 17 5 17 5 17 5 17 5 17 5 PERCENTAG E INT . CUM . 0. 6 1 . 1 0. 6 0. 0 2. 9 1 1 1 2 3 4 2 1 3 1 2 2 0 1 1 4 2 1 4 4 2 5 4 3. 4 6. 3 8. 0 7. 4 5. 7 2. 9 0. 0 0. 0 0. 0 0. 0 0 . 1 . 2 . 2 . 5 . 6 . g . 0 9 . 1 1 . 14 . 19 . 2 1 . 23 . 26. 9 20 . 30 . 33 . 33 . 34 . 36 . 40 . ' 4 3 . 4 4 . 49 . 5 3 . 56 . 62 . 66 . 69 . 76 . 04 . 9 1 . 97 . 1 00 . 1 00. 0 100. 0 100 . a 100. 0 . 0 9 1 7 o

. 0

. 6

. 4

, 6

. 1

, 7

. 6

. 3

. 3

. 7

. 0

. 0 4 1

, 0

FIGUR E D-lb . Othe r sites . 831'if ,

## E

• 7.0000 0 •14.000 0 •21.000 0 •28.000 0 •35.000 0 •42.000 0 •49.000 0 •56.000 0 •63.000 0 •70.000 0 •77.000 0 •84.000 0 •91.000 0 •98.000 0 •105.00 0 •112.00 0 •119.00 0 •126.00 0 •1 3 3.00 0 •140.010 0 •14 7.00 0 •1 5 4.00 0 •161.00 0 •1 6 8.00 0 •175.00 0 •182.00 0 •189.00 0 •196.00 0 •203.00 0 •210.00 0 •217.00 0 •224.00 0 •231.00 0 •238.00 0 •245.00 0 •252.00 0 •259.00 0 •266.00 0 SYMBO L COUN T MEA NST.DEV . A54 0 7.44 5 22.39 8 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA * +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAA A • AAA A •AAAAA A
• A A
• A •AA • AAA A +
• A +
• A • AA A • AA A + • AA • AA A + • AA • AA A
• A + + + + + + + + + + + + + + + + 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 FREQUENC Y INT . 46 3 3 5 1 2 4 6 2 1 2 4 0 1 0 1 3 3 0 2 3 0 2 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 CUM . 46 3 4 9 8 51 0 51 4 52 0 52 2 52 3 52 5 52 9 52 9 53 0 53 0 53 1 53 4 53 7 53 7 53 9 54 2 54 2 54 4 54 7 54 0 54 0 54 0 54 8 54 0 54 0 54 8 54 0 54 0 54 0 54 0 54 0 54 8 54 8 54 8 54 0 54 8 PERCENTAG E INT . 34. 5 6. 4 2. 2 0. 7 1 . 1 0. 4 0. 2 0. 4 0. 7 0. 0 0. 2 0. 0 0. 2 0. 5 0. 5 0. 0 0. 4 0. 5 0. 0 0. 4 0. 5 0. 2 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 CUM . 8 4. 5 90. 9 93 . 1 93. 8 94. 9 95. 3 95. 4 95. 8 96. 5 96. 5 96. 7 96. 7 96. 9 97. 4 98. 0 98. 0 98. 4 98. 9 93. 9 99. 3 99. 0 100. 0 100. 0 100. 0 100. 0 100. 0 1 0 0 . 0 100 . 0 100. 0 10 0 . 0 100. 0 10 0 . 0 100 . 0 10 0 . 0 100. 0 100. 0 100. 0 100 . 0 Numbe ro fSite s

8314 6 FIGUR E D-2a . Histogra

mo f the numbe r o f expecte d primar yexceedance s (E ) for site s reporting 0 3 concentration s in 1981 : SLAM S (including NAMS )SYMBO L COUN T MEA N ST.DEV . B 17 5 9.38 8 35.65 7 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N E 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0

+ + + + + + + + + + + _+ + + + + + •7.0000 0 +B3BBBBB3BBBBBBBBB5BBBBBBB3BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * •14.000 0 +BBBBB3BB B •2 1 .000 0 +BBBB B •28.000 0 +B B •35.000 0 +BB B * 4 2.00>3 0 + B •49.000 0 +B B •56.000 0 + •63.000 0 + •70.000 0 + • 7 7.000. 7 + •84.000 0 + B •91.000 0 + •90.000 0 + •105.00 0 + •112.00 0 + •119. 00 0 + •126.00 0 + B •133.00 0 + •140.00 0 + •147.00 0 + •1 5 4.00 0 + •161 . .00 0 + •160.0.0. 7 + •175.00. 0 + •182.00 0 + •189.00 0 + B •196.00 0 + •203.00 0 + •210.00 0 + •217.00 0 + B •224.0.0 0 + ' •231.00 0 + •238.00 0 + B •245 . .00. 0 + •252.00 0 + •259.00 0 + B •266.00 0 •

+ + + + + + + + + + + + + + + + + 5 1. 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 Numbe r o f Site s FIGURE D-2b . Othe r sites . FREQUENC Y INT . 14 7 9 5 2 3 1 2

. 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 CUM . 14 7 15 6 16 1 16 3 16 6 16 7 16 9 16 9 16 9 16 9 16 9 17 0 17 0 17 0 17 0 17 0 17 0 17 1 17 1 17 1 17 1 17 1 17 1 17 1 17 1 17 1 17 2 17 2 17 2 17 2 17 3 17 3 17. 3 174 17 4 17 4 17 5 17 5 PERCENTAG E INT . 84. 0 5 . 1 2. 9 1. . 1 1 . 7 0. 6 1 . 1 0. 0 0. 0 0. 0 0. 0 0. 6 0. 0 0. 0 0. 0 0. 0 0. 0 0. 6 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 6 0. 0 0. 0 0. 0 0. 6 0. 0 0. 0 0. 6 0.. U 0. 0 0. 0 0. 0 CUM . 84. 0 89 . 1 92. 0 93 . 1 94. 9 95. 4 96. 6 96. 6 96. 6 96. 6 96. 6 97 . 1 97 . 1 97 . 1 97 . 1 97 . 1 9 7 . 1 9 7. 7 97. 7 97. 7 97. 7 97. 7 97. 7 97. 7 97. 7 97. 7 90. 3 90. 3 90. 3 98. 3 90. 9 9 0. 9 90. 9 99. 4 9 9. 4 9 9. 4 100. 0 1 00
. 0SLAM S OTHER K - 72 3 COR
- .007 3 SYMBOL= S

SYMBOL= 0

, • . MEA N 77.68 5 7.915 4 ST.DEV .

22.23 8 26.21 4 REGRESSIO N LIN E RES. MS . X = .00621*Y + 77.63 6 495.1 9 Y= .00863*X + 7.245 2 688.0 8

. . + + ..X . + + + 28 0 +

24 5 +

21 0

17 5 +

14 0 +

10 5 +

70 .

35 .

0. 0 0 OO S O

O S 0 S

S O 0 S S S 

### s s s s SS S S 

### s s s o s S S S 

### s s s s s s s s s s s 0 s s SO S s s 0 s ososss s s s s s Yo ssoo o s s * s s**o s ssssss*s*s*s*ss s Y + 0 0 0 **o*o* o s* * ** s o****ss*s*ss * *****s*s********************* s + .....................+....+....+....+....+....+....+.X..+....+....+....+
. 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0.000 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0
. 90.0 0 105. 0



### FIGUR E D-3 . Scatte r plo t o f th e percentag e o f dat a completenes s i n198 1 (p ) versu s th e numbe r o f estimate dprimar y exceedance s (£ ) fo r site s reportin gO gconcentrations .

831U 6TABL E D-1 . Frequencytabl e o f the percentag e o f tota l day s recorde d in 198 1 (p )

versu s expecte d primaryexceedance s (E ) fo r site s reporting 1-hou r ozon e averages .

0 41X< = 62.5 X < • 75 X < - 81.5 X< - 86 X 89 X 92X 95X< - 97.5 X< - 100 X TOTA L 0 1 - 2 < - 5 <"25 5 T Ui A L 5 1 at 9 1 2 7 2 4 1

e 5 2 0 7 1 4 2

O 1 0 1 4 7 5 4 3

ia 7 1 0 7 0 31 .

1 2 1 6 9 7 3 2 9

1 2 1 3 9 6 3 3 4

1 2 1 6 1 7 7 9 3 7

1 4 1 6 1 1 7 8 2 5

1 2 8 2 0 6 5 3 0

1 3 1 5 1 9 7 7 36 8

99 11 5 14 1 72 3

8314 6


# sP.5 0



### Appendi xE LEA DDESCRIPTIVE STATISTIC S

8314 6 5P.5 1



### APPENDI XE LEADDESCRIPTIV E STATISTIC S
Figur e E- 1 show s th e distributio no f dat a completenes s amon gai r monitor ingstations . Fo r SLAMS , th e mod e o f th e dat a completenes s distributio n i s inth e interva l o f 15-1 8 percent , correspondin gt o nearl y complet e dat a recover y from a once-per-six-da y

samplin gschedule . Ther e ar e lo w correlation s betwee nth e percentag e o f dat a completenes s an dreporte d annua l averages , standar ddeviations , an dcoefficient s o f variatio n (Figur e E-2) .

8314 6 5' 3 *6 . l 9 . •1 2 0000 0 0000 0 0000 0 000 0 •15.000. 0 •13.000 0

. 000 0

. 000 0

. 00.0 0

. 000. 0

. 000 0

, 000. 7 •39.000 0 •42.000 0

. 0.0.0 0 •2 1 . •24 . •27 . •30 . •33 . •36 . •4 5 *4 8 *5 1 •54 •5 7 •6 0 •6 3 •6 6 •6 9 •7 2 •7 5 •7 0 *3 1 *G 4 •8 7 •9 0 000 0 000 0 000 0 000 0 000 0 000 0 .000 0 0.0.0. 0 0000 0.00 0 000 0 0.00 0 000 0 0.00 0 .0.00. 0 "93.0.0.0 0 •96.000. 0 * 9 9.0.0.0 0 * 102.0.0 0 •10!}
. 00 0 •100.00. 0 •111. 00 0 •11 4 .£'0 0 SYMBO L COUN T A17 1 EAC H SYMBO L REPRESENT S MEA N ST. DEV . 11.91 7 10.05 9 1 OBSERVATIO N 1 0 1 ! 5 5

- - + - 6 0 6 5 7 0 7 5

- - + - 8 0

- - + 2 0 2 5 3 0 3 5 4 0 4 5 5 0 + + + , . + + ^ + + + + . +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A
• A A •AA A •AAAA A •AAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA * •AA A

• A
• A
• A A + + + + + + + + + FREQUENC Y INT . CUM .

• A +

1 0 2 0 3 0 3 5 4 0 4 5 6 0 7 0 7 5 8 0 4 9 2 3 5 1 9 0 5 3 0 0 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 4 9 5 1 5 4 5 9 7 8 16 3 1G 6 16 6 16 6 16 7 16 8 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 0 17 1 17 1 17 1 17 1 17 1 17 1 17 1 PERCENTAG E INT . CUM . 28 . 1 . 1 . 2 . 11 . 49 . 1 . 0. 0 0. 0 0. 6 0 . 1 . 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 6 0. 0 0 . 0 0. 0 0 . 0 . 0. 0 28. 7 29. 8 3 1 .C 7 34. 5 45. 6 95. 3 97. 1 97 . 1 97 . 1 9 7 9 0 9 9 9 9 9 9 9 9 99. 4 99. 4 99. 4 99. 4 99. 4 93. 4 9 9.. ' 99. * 99 , 99 . 99 . 99 . 99 . 99. 4 9 3./ ; 99. 4 100. 0 1 0 0 . 0 1 00
. 0 1 0 0 . . 0 1 00
. 0 1 00
. 0 1 0 0 . 0 Numbe r o f Site s
FIGUR E E-la . reportin g P b Histogra mo f th e percentage , p , o f dat a completenes s fo r thos e site s

i n 1981 : SLAM S (includin g NAMS) . P , 3 1 4 <>

### p * 3.0000 0 •6.0000. 0 * 9 .0000. 1 •12 . 0.00 0 •15.000 0 •13.000 5 •21.000 0 •24.000 0 •27.000 0 •30.000 0 •33.0.00 0 •36.000 0 •39.0.O0 0 •42.0.00 0 •4 5 .0.0.0 0
• 4 8.0.00 0 •5 1 .0.0.0 0 *5 4 .Cnna • 5 7.0.00 0 •60.00.0 0
• 6 3.0.00 0
• 6 6.00.0 0 •69.0.08 0 •7 2 , "ff'0 0
• 7 5.0000 . •7 8 .0.0.0 0 •8 1 .0.00 0 * S1. 000 0 * 8 7.000 0 •90 . .000. 0 • 9 3..00.0 0 •9G..O00 0 '•99.000 0 •1 0 2.00 0 •105..00 0
• 1 fJ 3 .00 0 •111 . .00. 0 •114 . .00 0 5 SYM30 L COUN T MEA NST.DF.V . B 52 5 7.61 4 7.02 3 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0
+ B BBB B EBBBBBBBBBBB^BBBBCSBBBQBBBBE B BEBB B BBBBB B BBSBBBBBBBBB'L-BBBBBBBBBBBBBBBBBBBBBB *
• EBECBL' B 3BBBBBQB B
• BBBBBBBISBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB5BBBBBBBEBBBB * •BBBBBB B •BBCBBB B •BBBBBB B + + + + B + B + B + + + + + + + + + + + + + + + + + + + + + + + + + + 5 iGBBBBBUBP-iCBCBBBBCGUBBBB B

2 B BBB B BBB B ;;

• BE E BBBBBBBBBBIJB B 3BBBEBBBB3' i QBEBBBBBBBBBBBBBBBBBBBBBBBBEBDBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB3B *

1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 FREQUENC Y INT . 21 2 1 6 9 5 3 3 3 4 13 2 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0

• 0 0 0 0 0 0 0 0 0 0 0 0 0 0 CUM . 21 2 22 8 32 3 35 6 39 0 52 2 62 2 5 2 2 5 2 2 52 3 52 4 5 2 5 52 5 5 2 5 5 2 5 52 5 62 5 52 5 5 2 5 52 5 5 2 5 5 1 5 5 2 5 5 2 5 5 2 5 5 2 5 52 5 5 2 5 5 2 5 52 5 52 5 52 5 52 5 52 5 52 5 5 2 5 5 2 5 52 5 PERCENTAG E I N T . 40. 4 3. 0 18 . 1 6. 3 6. 5 25 . 1 0. 0 0. 0 0. 0 0. 2 0. 2 0. 2 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0.0 0. 0 0. 0 CUM . 40. 4 43. 4 6 1 . 5 67. 8 74. 3 99. 4 99. 4 99. 4 99. 4 99. G 9 9 . U 100. 0 100. 0 100. 0 1 0 0 . 0 100. 0 1 0 0 . ( ? 100 . a 1 0 0 . 0 100. 0 1 00
. 0 100. 0 100. 0 1 0 0 . 0 1 00
. 0 1 0 0 . 0 100.0 100.0 100 .0 1 00
. 0 1 00
. 0 1 00
. 0 1 00
. 0 1 00
. 0 100.0 1 00
. 0 100.0 1 0 0 . 0 Numbe r o f Site s
FIGURE E-lb . Othe r sites ,

H ''• ] ' i f ,SLAM S OTHE R N - 69 6 COR=-.008 0 MEA N X8.671 1 Y.4457 8 SYMBOL- S

5YMBOL- 0

ST.DEV . 8.085 0 .6763 9 REGRESSIO N LIN E RES.MS . X=-.09538*Y + 8.713 6 65.45 7 Y=-668E-6*X + .4515 7 .4581 4

cn

JD a. c to 0 1 12. 0 +

10. 5 +

9.0 0 +

7.5 0 +

6.0 0 +

4.5 0

3.0 0

1.5 0

0.0 0 SS O

* S O S O * S * 0 ss * * 0 0
. 0 0 s* * 

### * * *oo*o***** s s s •*00**0****** S O S * ' S Y ••00*00*0*0* * + + ....+X..
. + ... . + ... . + ... . + ... . + ....•... . + ..'..•...
. + ... . + ... . + . .. . + ... . + . 7.50 0 22.5 0 37.5 0 .52.5 0 67.5 0 82.5 0 97.5 0 00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0



### FIGUR E E-2a . Scatte r plot s o f ambien t ai r qualit y statistic s versu s th e percen t (p ) o f dat a completenes s fo r site s reportin gP bconcentration s i

n 1981 : maximu

m quarterl y

averag e versu s p .

8314 6SLAM S , SYMBOL' S OTHE R , SYMBOL= 0 N
- 67 0 COR=-.006 8 MEA NST.DEV . REGRESSIONLINE RES.MS . X B.973 4 Q.0O.J1 X= - .0 8 i 29* Y + 8.999 1 65.54 5 Y .3161 0 .676o 0 Y= -559E-5*:< + .3212 0 .45B7 2

10.0 0 +

3.75 0 +

7.50 0 +

S 6.25. 7 + 0

. 0~0

+ . X
. . . . + .

3
. 75. 3 + S

2.50 0 + S

0 c s S os s 1 .23 0 + * 0 0 0 ,

• 0 0 OS O ' < SO 0 SS :
- * •ooo oi •••""••••••••• s Y^OO-' O —S*-A.. S 0.J20 + •••••o

o 0'--- v 0--0' A•*•••' • 7.5.J. 3 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0.05 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGUR E E-2b . Standar ddiviatio nversu s p ,SVMBOL= S SYMBOL= 0 SLAM S OTHE R N = 67 0 COR=-.025 2 MEANST.DEV . REASSIG NLIN E P.CS.AS . X8.973 4 B..US.7 1 X = - . S5225 v i Y-i

- 9.3 ; ;?. 9 65.5J 7 Y .5431 1 .3121 3 Y= -97 1 L-5-;! + ,CJ518 2 .0975 4

C 0 E F F V A R 3. 2

2. 3

2 . 4

1. 6

1 . 2

.00

.4 0

0. 0 0 0

0 S - s

0 0 3 0 * S •• * 0 s SO * * 0 S S 0 * 0 s o * 0 0 s S 0 0 0 0 0 * * 0 •'• ' OOOCO OCO-' S * o oo*•'•-••••" S

* SCO - *•••• ••••••••v s * OOOOOO 0"'•'•' * "•• 0 * 00 0 "*•** * ••• o OOGGO*** * * oooooo o * •••••••

• 4 0 OO-'-' O o ••••••

* * S 00 0 0 0' * 0 0 ss .

- 0 0 0 0 0 0

0 s S s 0

7.50 0 22.5 0 . 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0 0 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGUR E E-2c . Coefficien t o f variatio n(standar ddeviatio ndivide dby maximu m quarterl y

average ) versu s p .P.5 7



### Appendi xF TS P DESCRIPTIVE STATISTIC S

8314 6 5

### ©

© P.5 8

APPENDI XF 

# e > TS P DESCRIPTIV E STATISTIC S



### C D

© •



# 0

O

05



### © Figur e F- 1 show s th e distributio n o f dat a completenes s amon g ai r monitor

ing stations . Th e mod e o f th e distributio n i s th e interva l o f 15-1 8 percen t dat a completeness , correspondin g t o nearl ycomplet e dat a recover y fro ma once-per-six-da ysamplin g schedule . Tabl e F- 1 show s th e numbe r o f site s meetin g an annua l quot a o f 7 5 percen t dat a completenes s and meetin g a correspondin g quarterl yquot a i n a specifie d numbe r o f quarters . Tabl e F- 2 show s th e sam e informatio n fo r an annua l quot a o f 5 0 percent . Not e tha t roughl y7 0 percen t o f th e site s tha t me t an annua l quot a als o me t a correspondin g quarterl yquot a i n eac ho f th e fou r quarter s o f 1981 . Ther e ar e lo wcorrelation s betwee n th e percentag e o f dat a completenes s and reporte d annua l averages , standar d deviations , and coefficient s o f variatio n (Figur e F2) . Histogram s o f "expected " exceedance s (i.e. , X
- o r k./p . i n th e notatio n o f Sectio n 2 ) sho wtha t roughl y9 5 percen t o f th e station s reporte d eigh t o r fewe r expecte d exceedance s i n 198 1 (Figur e F-3) . Th e greates t numbe r o f expecte d exceedance s wer e reporte d b yth e station s havin g relativel yles s complet e data ; 9 1 percen t o f th e station s reporte d zer o expecte d exceed

ance s (Figur e F- 4 and Tabl e F-3) . Judgin g b yTabl e F- 3 and th e lo w correlatio n give n i n Figur e F-4 , n o clea r relationshi p i s eviden t betwee n expecte d exceedance s and dat a completeness .



### ©

8314 6 5 

### ®SYMBO L COUN T MEA N ST.DEV . A229 5 15.72 2 9.71 8 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N FREQUENC YPERCENTAG E P 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 INT . CUM . INT . CUM .

+ + + + + + + + + + + + + + + + + * 3.0000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A4 0 •6.0000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A7 6 •9.0000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA * 8 6 •12.000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA * 16 5 * 15.000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA • 5 3 4 •18.000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA * 1 2 4 0 • 2 1.000 0 +AAAAAAAAAAAAAAAA A1 7 • 2 4.000 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A4 7 • 2 7.000 0 +AAAAAAAA A9 * 30.000 0 +AAAAAAA A8 • 3 3.000 0 AAAAAAAAAAAAAAAAAAAAAAAAAAA A2 7 * 36.000 0 + 0 •39.000 0 +A

A2 • 4 2.000 0 +AA2 * 45.000 0 +

A1 • 4 8.000 0 +A

A2 •51.000 0 +A

A2 •54.000 0 +

A1 •57.000 0 +A1 •60.000 0 + 0 •63.000 0 +

A1 •66.000 0 +

A1 •69.000 0 +AAAAA

A6 •72.000 0 +AA

A3 •75.000 0 + 0 •78.000 0 +

A1 •81.000 0 +AAA

A4 •84.000 0 +

A1 •87.000 0 + 0 •90.000 0 +A

A2 •93.000 0 +AAA

A4 •96.000 0 +AAAAAA

A7 •99.000 0 +AA

A3 •102.00 0 +A

A2 •105.00 0 + 0 •108.00 0 + 0 •111. 00 0 + 0 •114.00 0 + 0

+ + + + + + + + + + + + + + + + + 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 Numbe ro fSite s FIGURE F-la
. Histogra m o fth e percentage , p , o fdat a completenes s fo rthos e site s reportin g TS P concentration s i n 1981 : SLAM S (includin g NAMS)
. 4 0 11 6 20 2 36 7 90 1 214 1 21G 9 220 5 221 4 222 2 224 9 224 9 225 1 225 3 225 4 225 6 225 8 225 9 226 0 226 0 226 1 226 2 226 3 227 1 227 1 227 2 227 6 227 7 227 7 2 27 9 228 3 229 0 229 3 229 5 229 5 229 5 229 5 229 5 1

3 3 7 2 3 5 4 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 3 7 2 3 0 7 0 4 3 2 0 1 1 0 1 1 0 0 0 0 0 3 1 0 0 2 0 0 1CSI 3 1 1 0 0 0 0 1 5 8 1 6 3 9 9 3 Q 4 9 6 9 6 9 6 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9 8 9 3 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 0 10 0 10 0 10 0 10 0 7 1 8 0 3 3 a 1 5 8 0 0 1 2 2 3 4 4 5 5 5 6 8 0 0 0 2 2CSI 3 5 8 9 0 0 0 0 0

8 3 I 'if .* 3.0000 0 * 6.0000 0 * 9.0000 0 •12.000 0 •15.000 0 •18.000 0 •21.000 0 •24.000 0

. 000 0

. 000 0

. 000 0

. 000 0 '27 . '30 . "33 . '36 . "39 . "42 . '45 , '48 . '5 1 '54 . . 000 0

. 000 0

, 000 0

. 000 0

, 000 0

. 000 0 *57.000 0 •60.000 0 •63.0.00. 0 * 6 6.000 0 •63.000 0 •72.000 0

. 000. 0 .000 0

. 000 0

. 000 0
• 3 7.000 0 •90.000 0
• 9 3.000 0 •96.000 0 •99.000 0 •102.00 0 •105.00 0 •108.00 0 •111.00 0 * 114.00 0 •75 . •78 . •3 1 •84 . SYMBO L COUN T B 137 2 EAC H SYMBO L REPRESENT S MEA N ST.DEV . 15.84 5 15.56 3 1 OBSERVATIO N 1 0 + • BBB B • BBB B • BBB B • BBB B • BBB B • BBB B • BBB B • BBB B • BBB B + BB B • BBB B + BB B + B + BB B 1 5

• - + - 2 0 3 0 3 5 4 0

- - + - 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 FREQUENC YPERCENTAG E INT . CUM . INT . CUM . BBB3BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * BBB3BBBBBBBBBBBBBBBCBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * BBBBB3BBBBBBB3BBBBBBB0BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * BBBBBBBBBBBBBBBBBBBBBEBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB * BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB3BBBBBBBBBBBBBBB * BBBBBBBBBBB B BBBBBBBBBBBB B B3BBBBBBB B BBBBBBBBBBBBBBBBBBBBBBBBB B

SBB J B + 3B B +BBBB E + B +BBBB E + B • B B • BBB B +BEBB E • BBB B + B U • B B +BBBB E +BBEB E +BBBB E • B B + B • BBB B •BBBBBBB B • B JBB B SBB B !BB B

1 0 - + -

1 5 • - + - 2 0 2 5 3 0 - - + -

3 5 - - + - 4 0 - - + - 4 5 - - + - 5 0 - - + - 5 5 6 0 - - + -

6 5 - - + - 7 0 - - + - 7 5 - - + 8 0 8 7 14 5 13 5 11 9 25 9 46 8 1 6 1 7 1 4 3 3 0 3 1 3 0 3 6 1 5 1 2 4 5 4 2 2 7 7 7 2 1 4 8 1 0 0 0 0 8 7 23 2 36 7 4 3 6 74 5 121 3 122 9 124 6 126 0 126 3 129 3 129 6 129 7 130 0 130 0 130 3 130 9 131 0 131 5 131 6 131 8 132 2 132 7 133 1 133 3 133 5 134 2 134 9 135 6 135 8 135 9 136 3 137 1 137 2 137 2 137 2 137 2 137 2 6. 3 10. 6 9. 8 8 , 18 . 34 . 1 . 1 ,

• 1 . 0 . 2 . 0 . 0 . 1 0. 2 0. 0 0. 2 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 0 . 1 0 . 1 0. 3 0. 6 0 . 1 0. 0 0. 0 0. 0 0. 0 6 . 16 . 26 . 35 . 54 . 88 . 89 . 90. 8 9 1 . 8 92 . 1 94. 2 94. 5 94. 5 94. 8 94. 8 95. 0 95. 4 95. 5 95. 8 95. 9 96 . 1 96. 4 96. 7 97. 0 97. 2 97. 3 97. 8 98. 3 98. 8 99. 0 99 . 1 99. 3 99. 9 100. 0 100. 0 100. 0 100. 0 100. 0
Numbe r o f Site s FIGUR E F-lb . Othe r sites .P.6 1

TABLE F-1
. Numbe ro fsite s recordin g 24-hou rTSP durin g a tleas t 75 percen to fth e schedule d monitorin g day s i n 1981 , b yth e numbe ro f quarter s i n whic h a tleas t75 percen to fth e schedule d day s pe rquarte r ar e recorded
.

Sit e Typ e SLAM S (include s

Othe r 

### No .

w i 

### 75 %

NAMS ) o f Quarter s tha t Leas t Days/Quarte r 

### 0 1 2 3 4 Tota l 

### 0 1 2 3 4 Tota l No . o f

> 75 % 

### 0 2 6 9 

### 45 2 133 5 185 8 

### 0 0 7 0 

### 18 5 59 0 84 5 Site s

< 75 % 

### 7 9 

### 14 8 14 5 6 5 0 43 7 

### 16 0 20 4 11 9 4 4 0 52 7 Tota l



### 7 9 

### 15 0 21 4 51 7 133 5 229 5 

### 16 0 20 4 18 9 22 9 59 0 137 2

TABLE F-2
. Numbe ro fsite s recordin g 24-hou rTSP durin g a tleas t 5 0 percen to fth e schedule d monitorin g day s i n 1981 , b yth e numbe r o fquarter s i n whic h a tleas t5 0 percen to fth e schedule d day s pe rquarte rar e recorded
.

Sit e Typ e SLAM S (include s

Othe r No . o f Quarter s

wit ha t Leas t 50 % Days/Quarte r 

### 0 NAMS ) 1



### 2 3 4 Tota l 

### 0 1 2 3 4 Tota l No . o f

> 50 % 

### 0 0 5 2 

### 23 5 182 5 211 2 

### 0 3 6 2 

### 17 5 78 5 102 5 Site s

< 50 % 

### 3 2 8 9 6 1 

### 1 0 18 3 

### 7 5 

### 18 6 8 3 

### 3 0 34 7 Tota l



### 3 2 8 9 

### 11 3 23 6 182 5 229 5 

### 7 5 

### 18 9 14 5 17 8 78 5 137 2
8314 6 8P.6 2

SLAMS OTHE R SYMBOL= S SYMBOL= 0 N = 365 4 COR=-.012 2 MEA N 15.82 1 56.52 6 ST.DEV .

12.22 0 20.82 7 REGRESSION

X=-.00714*Y + Y=-.02074*X + LIN E

16.22 5 56.35 4 RES.MS
.

149.3 4 433.3 1

40 0 +

35 0 +

30 0 ,X+
.

tn 25 0 c to tv

i- + J tu B o O l 20 0 + ' 0 S s 0 s 15 0 + s 0

s s 0 00* 0 0 0 10 0 + s *os**s *

* * * * 2 ' * " 0 0 * *>'•'** * * rt••" : rt rt rt rt* ) rt* V ; rt* rt-. * * } * rt rt rt rt rt* rt )**;.-Qrtrtrt * Q V * * 0 •'-• * * 0 0 0 0 ^...
. + . . . Y0 * 5 0
. +0" . 0 " . 0 " 0 . 0 + ** S S * S * rt * rt rtrtrt rtrt * rtrtrt rtrtrt rtrtrt rtrtrt rtrtrt rtrtrt * s s s s s s sss s *s * O S SO S s** s **o s s*os*o o 

### *s»* « * s 

### ***o s *0*** o 0* S 0 S 0 00 0 0 0 0 0 0 0 0* * c O S 0 s s s S SO S S 0 SO S 0 0 S S S 0 0 S *0 0 S 0 0 0 0 0 0 0 0 S O 00*00 0 0 0 * 0 0 00 0 0 0 0 0 0 0 0 0 0 S S O 

### s s oo s SSS S * S s o * 0 S 0 0 0 0 0
7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0.00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGUR E F-2a . Scatte r plot s o f ambien t ai r qualit ystatistic s versu s th e percen t o f dat a completenes s (p ) fo r site s reportin g TS P concentration s i n 1981 : annua l geometri c mea n versu s p .

831^ 6P.6 3

SLAM S OTHE R SYMBOL= S

SYMBOL= 0 N - 365 4 COR = .079 7 MEA N 15.82 1 1.56.7 0 IT.DEV
. REGRESSIO N LIN E RES.MS
.

12.22 0 X = 4.3S43*Y + 8.951 1 148.4 2 .2220 0 Y = .00145-X + 1.544 1 .0489 9

5 . 0 +

4 . 5

4
. 0

3 . !

3 . 0 0

s
2 . 5 + 0

2 . 0 +

1. 5 Y

1
. 0 *....+
.

0 .•X
.

so
0 O O 0 0 0 s COO * oo s s s * 0 * s s • 0 0 * OS s 0 0 0 * *s s SQS00*3"*0 S 0 -•'• ' SO* " * '•

' * * * * 0*S-0 ' SS O S 0 s o 0 0 0

0 0

00 0 0 0 0 0 rtrt * * A 3 0 * * S * * rt Q « * v. - * * ** * rt QO

S s oooo s * rt rt rt rt rt rt rt rtrtrt* rtrtrtg Q g * S 2 rt rt rt rt * rt rt rt * rt rt g 2 * S

V : rt OS O rt* rt rt rt rt rt s rtrt * rt rt -r trt i * rt rt * * * * * OS

S*SO**O S 0 0 **OOOS** S S S * 0 0 S 0 ' SS O s 0 . s

0 0 0 0 S 0 0 0 0 0 0

0 0 00 0 *OSO S s o S S s s 0

ooo o OOSOO O 0 S 0 0 S s 0

0 * 0 OSO S *0S S S S S *0 S S S S S S SO 0

,x+ . 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0 0 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGURE F-2b
. Geometri cstandar d deviatio n versu s p .2. 4

2. 1

1. 8

C 0 E F F V A R 1. 5

1. 2 SLAM S OTHE R N = 365 4 COR = .008 2 MEAN X15.82 1 Y .0326 2 SYMBOL= S

SYMBOL= 0

ST.DEV . 12.22 0 .0393 1 REGRESSIO NLIN E RES.MS .

X = 2.5264*Y + 15.73 9 149.3 5 Y = 26GE-7*X + .0321 9 .0015 9

.9 0

.6 0

.3 0

0. 0 0 S

0 O S 0 * 0 0 s o* s OO* *** * OS O 00 0 0 V/Qr t rt„*r t rtrtrt * X rt * rt * * * Q * Q * * ;V Q * Q Q

<s*s*** o S s * .*r t ST****!! ; * ^*Art'Jt**lCt s 0 0 0 OOO O * 0 *0 0 00*00 0 00*00 0 0 O S * 0 '"S S 0 0 SOS S S O S S S O 0 SSS*S*OS * 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 0.00 0 15-.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGUR E F-2c . Coefficien t o f variatio n (geometri c stnadar d deviatio n divide d byth e annua l geometri c mean ) versu s p .

9 . 3 1 L , e .SYMBO L COUNT MEA

N ST.DEV . A229 5 1.48 9 9.43 8 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 *8.0000 0 •16.000 0 •24.000 0 •32.000 0 •40.000 0
• 4 8.000 0 •56.000 0
• 6 4.000 0 * 7 2 .00.0 0 *80.000 0 * 3 3.000 0 * 9 6.000 0 •104.00 0 •112 . 00 0 •120.00 0 •128.00 0 •136.00 0 •14 4 .00 0 •1 5 2.00 0 •160.00 0 •163.00 0 •1 7 6.00 0 •184.00 0 •1 9 2.00 0 * 200.00 0 •203.00 0 •216.00 0 •224.00 0 •232.00 0
• 2 40.00 0 * 2' ! 0 . 00 0 •256.00 0 •264.00 0 •272.00 0
• 2 30.00 0 •288.00 0 •296.00 0 •304.00 0 +AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A

+AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA A +AAAAAAAAAAAAAAA A •AAAAAA A •A A • AA A •AAA A •A A + • AA •A A •A A + + + + + + + + + + + + + + + + • A + + + • A + + + + + FREQUENC Y INT 19 6 5 7 1 6 7CSI 3 4(SI 0 2 2CSI 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 CUM . 219 6 22 5 3 226 9 227 6 227 8 228 1 228 5 228 7 228 7 22& 9 229 1 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 3 229 4 229 4 229 4 229 4 229 5 229 5 229 5 229 5 229 5 229 5 PERCENTAG E INT . 95. 7 2. 5 0. 7 0. 3 0 . 1 0 . 1 0. 2 0 . 1 0. 0 0 . 1 0 . 1 0 . 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 CUM . 95. 7 98. 2 9e. 9 99. 2 99. 3 99. 4 99. 6 99. 7 99. 7 99. 7 99. 8 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 99. 9 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 Numbe r o f Site s

FIGUR E F-3a . Histogra

mo f the numbe r o f estimate d primar yexceedance s (E ) for site s reporting TS P concentration s i n 1981 : SLAM S (including NAMS) . 831M 6SYMBO L COUN T MEA N ST.DEV . B 137 2 1.48 3 8.14 4 EAC H SYMBO L REPRESENT S 1 OBSERVATIO N E 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0

+ + + + + + + + —.- - + - + + + + + + + + •8.0000 0 +BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB*130 2 130 2 •16.000 0 +BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB B •24.000 0 +BBBBBB3BB B •32.000 0 +BBBBB B •40.000 0 +BBB B • 4 8.000 0 +BB B •56.000 0 + B • 6 4.00.9 0 + • 7 2.000 0 +B B •80.000 0 + B • 8 8.000 0 + B • 9 6.0.00 0 + •104.00 0 + •112..CO 0 + B •120.00 0 + B •128.00 0 + •136.00 0 + B •144.00 0 + •152.00 0 + •160.00 0 + •168.00 0 + M7G.Jf-.O 0 + •1 8 4.00 0 + •192..0.0 0 + • 2 0.0.00 0 + * 203.00 0 + •216.00 0 + • 2 2 4.0.0 0 + • 2 32.00 0 + •2 4 0.00 0 + •2 4 0.00 0 + •250.00 0 + •264. . 100

+ •2 7 2.00 0 + * 280.00 0 + * 23U.00 0 + •2 0 (3..0.00 + •3 0 4.00 0 +

+ + + + + + + + + + + + + + + + + 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 Numbe r o f Site s FIGUR E F-3b . Othe r sites . FREQUENC Y INT . 30 2 3 9 1 0 6 4 3 1 0(SI 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 CUM . 130 2 134 1 135 1 135 7 136 1 136 4 136 5 136 5 136 7 136 8 136 9 136 9 136 9 137 0 13 7 1 137 1 137 2 137 2 137 2 1 3 7 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 137 2 PERCENTAG E INT . 94. 9 2. 8 0. 7 0. 4 0. 3 0. 2 0 . 1 0. 0 0 . 1 0 . 1 0 . 1 0. 0 0. 0 0 . 1 • 0 . 1 0. 0 0 . 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 CUM . 94. 9 97. 7 98. 5 98. 9 99. 2 99. 4 99. 5 99. 5 99. 6 99. 7 99. 8 99. 8 99. 8 99. 9 99. 9 99. 9 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 100. 0 10 0 . 0 100. 0 1.00. 0 100. 0 10 0 . 0 100. 0 10 0 . 0 10 0 . 0 100. 0 100. 0 100. 0 100. 0 1 0 0 . 0 1 00. 0 100. 0

H ~sI 'if ,P.6 7

SLAM S OTHE R N = 366 7 COR = .012 5 SYMBOL= S

SYMBOL= 0

MEA N 15.76 5 1.486 7 ST.DEV .

12.23 3 8.974 5 REGRESSIO NLIN E RES.MS .

X = .01703*Y + 15.74 1 149.6 6 Y = ,00919*X + 1.341 8 80.55 1

28 0

24 5 +

21 0

17 5

14 0

10 5

70 .
35 .
0. 0 ,X+ .

0 0 S S 0 O S * s s s D 0 O O S 0 0 s o s o 0 osss* * 0* * S*** Q s s

s o 0 0 s s s s ***** * sss * S 00 0 O S S S 0 0 0 y******«*ft********«r*****Q**0S 0 S0*0* 0 * o *o*os*o*oo * *0*00 0 *S**S*OS * Y +....+....X....+....+....+....+....+....+....+....+....+....+....+....+ . 7.50 0 22.5 0 37.5 0 52.5 0 67.5 0 82.5 0 97.5 0 00 0 15.0 0 30.0 0 45.0 0 60.0 0 75.0 0 90.0 0 105. 0

FIGUR E F-4 . Scatte r plo t o f th e percentag e o f dat a completenes s (p ) versu s th e numbe r o f estimate d exceedance s (E ) fo r site s reportin g TS P concentration s i n 1981 .

8314 6TABLE F-3
. Frequenc ytabl e o fth e percentag e o ftota l day s recorde d i n 198 1 (p )

versu s expecte d primar yexceedance s (E ) fo rsite s reportin g 24-hou rTS P averages ,


## E 0 i - 1 0 < = 2 0 < » 26 0 TOTA L 0 - 6 % <

33 9 0 2 7 34 8 = 10.5 X <

32 6 7 1 6 6 35 5 C= 13 X<

30 8 2 8 3 8 34 7 - 14.5 X< - 15 % <

30 8 2 7 8 5 34 8 23 1

1 3 2 2 24 8 - 15.5 X<

36 7 2 3 1 0 3 40 3 C - 16 X<

42 6 2 3 6 5 46 0 - 16.5 X< - 17 X<

54 2 2 1 1 2 8 58 3 21 9

1 7 1 0 3 24 9 - 100 X

25 7 5 2 9 8 32 6 TOTA L

332 3 2 1 1 7 8 5 5 366 7

8314 6



## mP.6 9



### Appendi xG SUMMARYOF CURREN T DATA COMPLETENES S CRITERI A

83U 6 5APPENDI XG SUMMARYO

F CURREN T DAT A

COMPLETENES S CRITERI A

The presen t dat a completenes s criteri a use dt o establis hvali dai r qualit y summar y statistic s vary

b y us e an dorganization . Table s G- l throug hG- 3 summariz e criteri a fo r NADB , th e Californi a Ai r Resource s Board , an dth e Indian a Ai r Pollutio nContro l Division . Inaddition , th e EPA Trend s Repor t (EPA , 1983 ) require s 5 0 percen t o r 438 0 hourl y observation s pe r yea r (or insome case s 400 0 hour s pe r yea r i s used) . The "EPA

fac t book " inth e Trend s Report , whic hsummarize s ai r qualit y level s i nStandar dMetropolita nStatistica l Areas , use s th e same criteri a a s i nth e Trend s Repor t bu t note s i f th e volum e o f annua l dat a i s less . Summarie s fro

m intermitten t measurement s base do nles s tha n3 0 day s o r les s tha nth e NADB criteri a ar e als o noted .

REFERENCE S
CARB . 1983 . Californi a Ai r Qualit y Data , Summary

o f 198 2 Ai r Qualit y Data , Gaseou s andParticulat e Pollutants . Californi a Ai r Resource s Board , Sacramento , CA . EPA . 1977 . Aero s Manua l Serie s Volum e III : Summary an dRetrieval . U.S , Environmenta l Protectio nAgency , Researc hTriangl e Park , NC (EPA 450/2-76-009a) . EPA . 1979a . "Implementatio nPlan s fo r Lea dNationa l Ambien t Ai r Qualit y Standards. " 4 3 Federa l Register , 46266 .

83m 6 5

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o

o

o

0



# o

o



# o

o P.7 1



### EPA o 1979b . Guidelin e fo r LeadMonitorin gi nth e Vicinit y o f Poin t Sources . U.S . Environmenta l Protectio nAgenc y (EPA-450/4-01-006) . EPA . 1983 . Nationa l Ai r Qualit y an dEmissio nTrend s Report , 1981 . U.S . Environmenta l Protectio nAgency , Researc hTriangl e Park , NC . EPA . 1984 . "Propose dRevision s t o th e Nationa l Ambien t Ai r Qualit y OStandard s fo r Particulat e Matter. " 4 9 Federa l Register , 10434 .

O 831»t 6 5

uium HP.7 2

TABLE G-l
. Nationa l Aerometri cDat a Bank' s criteri a fo rvalidit yo fdata
. (Source : EPA , 1977 )
Continuou s Samplin g (1 , 2 , an d 4-hou rdata ) Quarterl ystatistics--75 % o r164 2 hour s Annua l statistics--75 % o r657 0 hour s Intermitten tSamplin g (24-hou rdata ) Quarterl ystatistics—fiv e sample s pe rquarte r ( I fon e mont h has n o values , a tleas ttw o value s i n othe rmonths ) Annua l statistics—fou rvali d quarter s ir Not e tha t1 2 sample s pe rquarte rar e require d t o demonstrat e attainmen to fth e NAAQ S fo rlea d (EPA , 1979a , b)
. Thi s requiremen ti s als o unde r consideratio n fo rparticulates
. (EPA , 1984)
.

831H6 r 8

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# o

o

o TABLE G-2
. Californi a Ai rResource s Board' s criteri a fo rrepresentativenes s

o fai rqualit ymeasurement s an d statistics
. (Source : CARB , 1983 ) 

### Representativ e Calenda r Statisti c
Yea r |

( 

### Quarte r \

\ / 

### Mont h<

( 

### Samplin gTime

Perio d 4 representativ e calenda r quarter s 2 4 hour s 

## O r

< 2 4 hour s 2 4 hour s 

## O r

< 2 4 hour s

Da y



### Mea no f M Hou r Perio d 1-hou r O r 2-hour ; o r 3-hour ; o r 24-hou r

2 4 8 6 3 2 1 Basi s o f Statisti c o r

Requiremen t Numbe r o f Representativ e Hour s o rDays Require d



### 3 representativ e month s Base dona dail y statistic ; o r
Base donhourl y

statistic s 4 o r mor e 24-hou r sample s Base dona dail y statistic ; o r Base donal l hourl y statistics ; o r Base donal l 2-hour statistics ; o r Base donal l 3-hour statistic s Mo mor e than2 consecutiv e sample s missin gineac h 1/ 3 day (hour s 0 thr u7 , 8 thr u15 , 1 6 thr u23 ) 6 9 o r mor e calenda r day s 1,63 8 or mor e hour s

2 3 o r mor e calenda r day s 54 8 o r mor e hour s 27 4 o r mor e 2-hou r statistic s 18 3 o r mor e 3-hou r statistic s 6 .o r mor e hour s in eac h1/ 3 day 1 1 o r mor e sample s 7 o r mor e sample s 2 2 bu t no t mor e than2 6 hour s o f sampling Numbe r o f Sample s Neede d 2 2 o r mor e hourl y

sample s 7 o r mor e hourl y

sample s 5 o r mor e hourl y

sample s 4 hourl y

sample s 3 hourl y

sample s 2 hourl y sample s 3 0 minute s o r mor e o f sampling * * AR B Qualit y

Assuranc e Manua l Sectio n2.0.23 . 

## O I314 6 

## uH lP.7 4

TABL E G-3 . Indian

a Ai r Pollution Contro l Division' s criteri a fo r completenes s o f data . (Source : Buch , 1983 ) Time Interva l Minimu mNumbe r o f Vali d Observation s
A . Continuou s Hou r Day Mont h Quarte r Yea r Three-Hou r Runnin g Averag e Eight-Hou r Running Averag e A t leas t forty-fiv e (45 ) minutes * A t leas t eightee n (18 ) hour s A t leas t twenty-on e (21 ) day s Thre e (3 ) month s A t leas t nin e (9 ) month s wit h a t leas t two (2 ) month s pe r quarte r Thre e (3 ) consecutiv e hour s Six.(6 ) hour s ou t o f eigh t (8 ) consecutiv e hour s
B . Six-Da

ySamplin

g Schedul e Quarte r

Yea r A t leas t te n (10 ) sample s unles s on e (1 ) mont hha s zer o (0 ) vali d samples , the n th e remaining two (2 ) month s mus t hav e a t leas t fou r (4 ) sample s each . A t leas t nin e (9 ) month s wit ha t leas t two (2 ) month s pe r quarte r an d a t leas t forty-fiv e (45 ) samples . C
. Dail ySamplin g Schedul e Quarte r

Yea r A t leas t sixt y(60 ) sample s unles s on e (1 ) mont hha s zer o (0 ) vali d samples , the n eac hremaining mont hmus t have a t leas t twenty-fou r (24 ) samples . A t leas t nin e (9 ) month s wit n a t leas t two (2 ) month s pe r quarte r an d a t leas t two-hundre d seventy-thre e (273 ) sample s
*I f a n hou r include s the dail yzero/span sequence , th e hou r i s considere d vali d i f a t leas t fift ypercen t (50.0% ) o f th e hou r i s valid .

8314 6