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# OAR Box 

# 1808 Prepped byCharmelle Mathews



### Document

Number: 

# 4 ) ll-A-1 4
Docket Number: 

# A-90-0 7

Printed 11/20/200810:28:18AM Sheet 4of 91P. 2 I . - .0- 0 . 

## •U- A-/</ EPA-450/5-83-00 4



# Th e NAAQ S Exposure Mode l (NEM ) Applie d t o Carbo n Monoxid e

Te d Johnso n an d Ro yA

. Pau l PEDC o Environmental , Inc

. 50 5 Sout h Duk e Street

. Suit e 50 3 Durham , Nort h Carolin a 2770 1 

### FEB? "199?

Prepare d fo r U.S

. ENVIRONMENTA LPROTECTIO N AGENC Y

Offic e o fAi ran d Radiatio n Offic e o fAi rQualit yPlannin g an d Standard s Researc h Triangl e Park

. N C 277 1 1
Thoma s McCurdy , Tas k Manage r

Decembe r198 3P. 3



### DISCLAIME R
Thi s repor t wa s furnishe d t o th e U.S . Environmenta l Protec

tio n Agenc yb

yPEDC o Environmental , Inc. , i n partia l fulfillmen t o f Contrac t No . 68-02-3390 , Wor k Assignment s No . 1 3 and 16
. Th e content s o f thi s repor t ar e reproduce d herei n a s receive d from th e contractor . Th e opinions , findings , and conclusion s expresse d ar e thos e o f th e author s and no t necessaril ythos e o f th e Environ

menta l Protectio n Agency . Thi s draf t repor t i s bein g circulate d fo r revie wand comment . Anyon e intereste d i n commentin g o r providin g informatio n concern in g th e materia l shoul d addres s thei r communication s t o Thoma s Feagans , Ambien t Standard s Branch , MD-12 , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolin a 27711
. I f yo u woul d lik e t o discus s th e report , pleas e cal l hi ma t (919)541-565 5 (FT S 629-5655)
.

il lP. 4



### CONTENT S Pag e Figure s vi i Table s . i x Acknowledgmen t xvi i 1
. Introductio n 1- 1 2
. Overvie wo f th e Exposur e Mode l 2- 1 2. 1 Th e exposur e distric t versio n o f NE M2- 1 2. 2 Th e neighborhoo d versio n o f NE M2- 3 ' 2. 3 Reference s 2- 5 3
. Simulatio n o f Populatio n Movemen t 3- 1 3. 1 Compositio n o f cohor t file s 3- 1 3. 2 Type s o f neighborhood s 3- 8 3. 3 Estimatio n o f cohor t population s 3-1 0 3. 4 Reference s 3-1 7 4
. Preparatio n o f Ai r Qualit yDat a 4- 1 4. 1 Selectio n o f representativ e dat a set s 4- 1 4. 2 Validatio n o f ai r qualit ydat a 4- 4 4. 3 Simulatio n o f missin g value s i n hourl y averag e C O dat a set s 4- 9 4. 4 Reference s 4-1 8 5
. Simulatio n o f Ai r Qualit yExpecte d a t Fixe d Monitorin g Sit e Unde r Alternativ e Carbo n Monoxid e Standard s 5- 1 5. 1 Th e rollbac k mode l 5- 1 5. 2 Ai r qualit yindicator s 5- 2 5. 3 Background concentration s 5-1 5 5. 4 Reference s 5-1 8CONTENTS (continued ) P. 5



### 6
. Simulatio n o f Carbo n Monoxid e Level s i n th e Microenvironmen t P a 

### ? e


### 6- 1 6. 1 Work-schoo l microenvironmen t 6. 2 Home-othe r microenvironmen t 6. 3 Transportatio n vehicl e microenvironmen t 6. 4 Roadsid e microenvironmen t 6. 5 Othe r outdoo r location s 6. 6 Summar y 6. 7 Reference s 6- 3 6- 9 6-1 8 6-2 5 6-2 6 6-2 6 6-2 9 7
. Exposur e Estimate s fo r Adult s wit hCardiovascula r Diseas e i n Fou r Urba n Area s 7- 1 7. 1 "Bes t estimate " result s 7. 2 Male/femal e comparison s 7. 3 Th e significanc e o f indoo r source s 7. 4 Uncertaint yi n NE Mexposur e estimate s 7. 5 Reference s 7- 1 7-3 9 7-4 2 7-4 2 7-5 5 8
. Nationwid e Extrapolation s 8. 1 Extrapolatio n procedur e 8. 2 Extrapolatio n result s 8. 3 Uncertaint yo f th e nationwid e estimate s Appendi xA Appendi xB Appendi xC Activit yPattern s b yAge-Occupatio n Subgroup Cohor t Population s b yStud yAre a Discussio n o f Ai r Qualit yIndicator s Use d i n th e NE MAnalysi s an d Estimate d Concentration s Use d i n th e Regulator y Analysi s 8- 1 8- 2 8- 4 8-1 6

A- 1 B- l

C- l

v iP. 6



### FIGURE S Numbe r Pag e 2- 1 Flo wDiagramo f Exposur e Distric t Versio n

o f NE M2- 4 2- 2 Flo wDiagramo f Neighborhoo d Versio n o f NE M2- 6 3- 1 Simulate d Movement s Betwee n Exposur e District s

I n Th e Lo s Angeles-Sa n Bernardin o Stud yAre a 3- 2 3- 2 Patter n o f Neighborhoo d Type s i n a Portio n o f

Th e Philadelphi a Stud yAre a 3- 3 3- 3 Representatio n o f People-Movemen t i n th e

Neighborhoo d Versio n o f NE M3- 4 3- 4 Content s o f Cohor t Activit yFil e 3-1 1 4- 1 Hourl yAverag e 197 8 Carbo n Monoxid e Dat a

Reporte d b

yMonitorin g Sit e 261040001G0 1 i n St . Loui s 4-1 5 4- 2 Hourl yAverag e 197 8 Carbo n Monoxid e Dat a fo r

Monitorin g Sit e 261040001G0 1 i n St . Loui s Afte r Initia l Simulatio n o f Missin g Value s 4-1 6 4- 3 Hourl yAverag e 197 8 Carbo n Monoxid e Dat a fo r

Monitorin g Sit e 261040001G0 1 i n St . Loui s Afte r Fina l Simulatio n o f Missin g Value s 4-1 7

VI 1P. 7



### 2
. Jame s L . Repace , Wayn e R . Ott , an d Lanc e A . Wallace , "Tota l huma n exposur e t o ai r pollution, " pape r 80-61.6 , presente d a t th e 73r d Annua l Meetin g o f th e Ai r Pollutio n Contro l Association , Montreal , Jun e 1980
. 3
. WilliamF . Biller , Thoma s B . Feagans , Te d R . Johnson , Georg e M . Duggan , and Jame s E . Capel , Estimate d Exposur e t o Ambien t Carbo n Monoxid e Concentration s Unde r Alternativ e Ai r Qualit yStandards ^ Strategie s and Ai r Standard s Division , Offic e o f Ai r Qualit yPlannin g and Standards , U.S . Environ

menta l Protectio n Agency , Researc hTriangl e Park , N.C . 27711 , Januar y1981
. 4
. Te d Johnso n and Ro yPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Nitroge n Dioxide , prepare d b yPEDC o Envir

onmental , Inc. , fo r Strategie s and Ai r Standard s Division , Offic e o f Ai r Qualit yPlannin g an d Standards , Environmenta l Protectio n Agency , Researc hTriangl e Park , N.C . 27711 , Augus t 1981
. 5
. Te d Johnso n and RoyPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Particulat e Matter , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s and Ai r Standard s Divi

sion , Offic e o f Ai r Qualit yPlannin g an d Standards , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N.C . 27711 , Augus t 1981
. 6
. WilliamF . Biller , Thoma s B . Feagans , Te d R . Johnson , Georg e M . Duggan , Ro yA . Paul , Thoma s McCurdy, , and Henr yC . Thomas , " Agenera l mode l fo r estimatin g exposur e associate d wit h alternativ e NAAQS, " pape r 81-18.4 , presente d a t th e 74t h Annua l Meetin g o f th e Ai r Pollutio n Contro l Association , Philadelphia , Jun e 1981
. i

xi xP. 8



### TABLE S Numbe r Pag e 3- 1 Descriptio n an d Apportionmen t o f Activit y Patter n Subgroup s 3- 6 3- 2 Neighborhoo d Type s (NT's ) and Code s 3- 9 3- 3 Geographi c Classificatio n o f Exposur e District s 3-1 2 3- 4 A- 0 Group Populatio n B yResidentia l Neighbor

hoo d Classification s i n Fou r Stud yArea s 3-1 3 3- 5 Assumption s Concernin g Wor k NT' s o f A- 0 Group s 3-1 5 3- 6 Collapse d Home-To-Wor k Tri p Tables , Expresse d

A s Numbe r O f Trip s And Fractio n o f Trip s 3-1 6

3 4- 1 Data . Set s (mg/ m) Selecte d Fo r Analysi s o f

Populatio n Exposur e T o Carbo n Monoxid e i n Fou r Citie s 4- 2 4- 2 Anomalie s Flagge d b yDat a Screenin g 4- 8 5- 1 Result s o f Fittin g Weibul l and Lognorma l

Distribution s t o 197 8 C O Dat a (ppm ) Fro m St . Louis , M O b

yLeas t Square s Metho d 5-1 0 5- 2 Result s o f Fittin g Weibul l and Lognorma l

Distribution s b

yMaximumLikelihoo d Procedur e t o Uppe r 5 0 Percen t o f Dail yMaximum1-Hour C O Dat a 5-1 1 5- 3 Result s o f Fittin g Weibul l and Lognorma l Dis

tribution s b

yMaximumLikelihoo d Procedur e t o Uppe r 5 0 Percen t o f Dail yMaximum8-Hour Runnin g Averag e C O Dat a 5-1 2 5- 4 Result s o f Fittin g Weibul l an d Lognorma l Dis

tribution s b

yMaximumLikelihoo d Procedur e t o Uppe r 2 0 Percen t o f Dail yMaximum1-Hour C O Dat a 5-1 3

I XP. 9



### TABLE S (continued ) Numbe r Pag e 5- 5 Result s o f Fittin g Weibul l an d Lognorma l Dis

tribution s byMaximumLikelihoo d Procedur e t o Uppe r 2 0 Percen t o f Dail yMaximum8-Hou r Runnin g Averag e C O Dat a 5-1 4 5- 6 Ai r Qualit yIndicator s Fo r C O Dat a 5-1 6 5- 7 Estimate d Annua l Averag e Backgroun d Level s 5-1 7 6- 1 Studie s Considere d i n Developin g C O Micro

environmen t Factor s 6- 2 6- 2 Estimate s o f C O Concentration s i n

a n Offic e Wit hSmoker s 6- 5 6- 3 Weekda yC O Measurement s a t Stree t Canyo n Sit e 6- 6 6- 4 C O Concentration s (ppm ) a t Tw o Offic e Site s

Recorde d byMoschandreas , e t al
. 6- 7 6- 5 Indoor-Outdoo r C O Ratio s Determine d fo r Tw o

Offic e Building s byYocum , e t al
. 6- 7 6- 6 Averag e Indoor/Outdoo r C O Ratio s Recorde d by

Yocum , e t al
. 6- 9 6- 7 Ai r Exchang e Rate s Determine d b yMoschandreas , e t al
. 6-1 2 6- 8 Indoor/Outdoo r C O Dat a Recorde d b yCote , e t al
. 6-1 5 6- 9 Averag e Difference s Betwee n Kitchen , Livin g

Room , and Outsid e C O Concentration s 6-1 6 6-1 0 Averag e C O Level s i n Variou s Structure s 6-1 8 6-1 1 Ratio s o f Mea n Persona l C O Exposure s t o Mea n

C O Concentration s a t Fixe d Monitor s 6-2 3 6-1 2 Ratio s o f C O i n Moto r Vehicle s Concurren t t o

C O a t Cam

p Station s 6-2 4 6-1 3 Ratio s o f Mea n C O Concentration s a t Experimenta l

Site s and a t Fixe d Site s 6-2 6 6-1 4 Estimate s o f Additiv e Microenvironmenta l

Factor s ( a . ) 6-2 7

m , tP.10

_



### Numbe r TABLE S (continued ) Pa^ e 6-1 5 Estimate s o f Multiplicativ e Microenviron

menta l Facto r ( b) 6-2 8 7- 1 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f 1-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 2 7- 2 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Wh o Hav e 1-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 3 7- 3 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Whos e Maximum1-Hour C O Exposur e Occur s i n Selecte d Concentratio n Range s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 4 7- 4 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f 8-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 5 7- 5 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Wh o Hav e 8-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 6 7- 6 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Whos e Maximum8-Hour C O Exposur e Occur s i n Selecte d Concentratio n Range s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 7 7- 7 Estimate s o f Occurrence s fo r Adult s Wit h'

Cardiovascula r Diseas e o f COHbLevel s Exceedin g Selecte d Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7- 8 7- 8 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Wh o Experienc e COHbLevel s Exceedin g Selecte d Value s Assumin g 9 PPM/ 1 EXE X Standar d i s Attaine d 7- 9 7- 9 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Whos e MaximumCOHbLeve l Occur s i n Selecte d Range s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7-1 0

x i iP.1 1



### TABLE S (continued ) Numbe r Pag e 7-1 0 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f 1-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 1 7-1 1 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Wh o Hav e 1-Hou r C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 2 7-1 2 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Whos e Maximum1-Hou r C O Exposur e Occur s i n Selecte d Concentratio n Range s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 3 7-1 3 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f 8-Hou r C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 4 7-1 4 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Wh o Hav e 8-Hou r C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 5 7-1 5 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Whos e Maximum8-Hou r C O Exposur e Occur s i n Selecte d Concentratio n Range s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 6 7-1 6 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f COHbLevel s Exceedin g Selecte d Value s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 7 7-1 7 Estimate s o f Adult s Wit hCardiovascula r

Diseas e Wh o Experienc e COHbLevel s Exceedin g Selecte d Value s Assumin g 1 2 PPM/ 1 EXE X Standar d i s Attaine d 7-1 8 7-1 8 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Whos e MaximumCOHbLeve l Occur s i n Selecte d Range s Assumin g 1 2 PPM/ 1 EXE XStandar d i s Attaine d 7-1 9

X I IP.1 2



### TABLE S (continued ) Numbe r Pag e 7-1 9 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f 1-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 0 7-2 0 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Wh o Hav e 1-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 5 PPM/ 1 EXE X Standar d i s Attaine d 7-2 1 7-2 1 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Whos e Maximum1-Hour C O Exposur e Occur s i n Selecte d Concentratio n Range s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 2 7-2 2 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f 8-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 3 7-2 3 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Wh o Hav e 8-Hour C O Exposure s Abov e Selecte d Concentratio n Value s Assumin g 1 5 PPM/ 1 EXE X Standar d i s Attaine d 7-2 4 7-2 4 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Whos e Maximum8-Hou r C O Exposur e Occur s i n Selecte d Concentratio n Range s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 5 7-2 5 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f COHbLevel s Exceedin g Selecte d Value s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 6 7-2 6 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Wh o Experienc e COHbLevel s Exceedin g Selecte d Value s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 7 7-2 7 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Whos e MaximumCOHbLeve l Occur s i n Selecte d Range s Assumin g 1 5 PPM/ 1 EXE XStandar d i s Attaine d 7-2 8 7-2 8 Algorith

mUse d t o Calculat e Carboxyhemoglobi n i n Bloo d o f Cohort s 7-3 1

x m___A
_



### TABLE S (continued ) Numbe r Pag e 7-2 9 Value s Assigne d t o Variable s i n Algorith m Use d t o Estimat e Carboxyhemoglobi n " 7-3 2 7-3 0 Percentag e o f Adult s Wit hCardiovascula r

Diseas e Experiencin g COHbLevel s Exceedin g Selecte d Value s Assumin g 9 PPM/ 1 EXE X Standar d i s Attaine d 7-3 5 7-3 1 Percentag e o f Adult s Wit hCardiovascula r

Diseas e Experiencin g COH bLevel s Exceedin g Selecte d Value s Assumin g 1 2 PPM/ 1 EXE X Standar d i s Attaine d 7-3 7 7-3 2 Percentag e o f Adult s Wit hCardiovascula r

Diseas e Experiencin g COH bLevel s Exceedin g Selecte d Value s Assumin g 1 5 PPM/ 1 EXE X Standar d i s Attaine d 7-3 8 7-3 3 Estimate s o f Adul t Female s Wit hCardiovascula r

Diseas e Wh o Experienc e COHbLevel s Exceedin g Selecte d Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7-4 0 7-3 4 Estimate s o f Adul t Male s Wit hCardiovascula r

Diseas e Wh o Experienc e COH bLevel s Exceedin g Selecte d Value s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 7-4 1 7-3 5 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Wh o Hav e 1-Hou r C O Exposure s Abov e Selecte d Value s Unde r 9 PPM/ 1 EXE XStandar d Wit hIn

doo r Source s Omitte d 7- 4 3 7-3 6 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Wh o Hav e 8-Hou r C O Exposure s Abov e Selecte d value s Unde r 9 PPM/ 1 EXE XStandar d Wit hIn

doo r Source s Omitte d 7-4 4 7-3 7 Estimate s o f Occurrence s fo r Adult s Wit h

Cardiovascula r Diseas e o f COH bLevel s Exceedin g Selecte d Value s Unde r 9 PPM/ 1 EXE XStandar d Wit hIndoo r Source s Omitte d 7-4 5 7-3 8 Estimate s o f Adult s Wit hCardiovascula r Diseas e

Wh o Experienc e COH bLevel s Exceedin g Selecte d Value s Unde r 9 PPM/ 1 EXE XStandar d Wit hIn

doo r Source s Omitte d 7-4 6
xi v

### Numbe r

7

-

7

-

7

-

7

-

7

- -3 9

-4 0

-4 1

-4 2

-4 3 TABLE S (continued )

Estimate s o f Adult s wit hCardiovascula r Diseas e whos e MaximumCOHbLeve l Occur s i n Selecte d Range s unde r 9 PPM/ 1 EXE XStandar d wit hIndoo r Source s Omitte d Estimate s o f Adult s wit hCardiovascula r Diseas e Chicag o wit h1-Hour Carbo n Monoxid e Exposure s Abov e Selecte d Value s Unde r 1 2 PPM/ 1 EXE XStan

dar d Usin g Best , Lower , and Uppe r Microenviron

men t Factor s Pag e

7-4 7

7-4 9 Estimate s o f Adult s wit hCardiovascula r Diseas e i n Chicag o wit h8-Hour Carbo n Monoxid e Exposure s abov e Selecte d Value s unde r 1 2 PPM/ 1 EXE XStan

dar d usin g Best , Lower , and Uppe r Microenviron

men t Factor s 7-5 0 Estimate s o f Occurrence s fo r Adult s wit hCardio

vascula r Diseas e i n Chicag o o f COH bLevel s Exceedin g Selecte d Value s unde r 1 2 PPM/ 1 EXE X Standar d usin g Best , Lower , and Uppe r Micro

environmen t Factor s Estimate s o f Adult s wit hCardiovascula r Diseas e i n Chicag o Experiencin g COHbLevel s Exceedin g 7-5 1 P.1 4



### Selecte d Value s Unde r 1 2 PPM/ 1 EXE XStandar d Usin g Best , Lower , and Uppe r Microenvironmen t Factor s 7-5 2 7-4 4 Estimate s o f Adult s wit hCardiovascula r Diseas e

i n Chicag o whos e MaximumCOHbLeve l Occur s i n Range s unde r 1 2 PPM/ 1 EXE XStandar d Usin g Best , Lower , and Uppe r Microenvironmen t Factor s 7-5 3 7-4 5 Sensitivit yo f COHbEstimate s fo r Chicag o t o

Variation s i n Tw o Physiologica l Variable s 7-5 4 8- 1 Urbanize d Are a Populatio n Dat a Use d t o Extra

polat e Mode l Result s 8- 4 8- 2 Estimate s o f Occurrence s i n th e Cardiovascula r

Adul t Urba n U.S . Populatio n o f 1-Hour Averag e C O Exposure s abov e Selecte d Concentratio n Value s unde r Alternativ e Ai r Qualit yAssumption s 8- 5

x vP.1 5



### TABLE S (continued ) Numbe r Pag e 8- 3 Estimate s o f Cardiovascula r Adult s i n Urba n U.S .

wit h1-Hou r Averag e C O Exposure s abov e Selecte d Concentratio n Value s unde r Alternativ e Ai r Qualit yAssumption s 8- 6 8- 4 Estimate s o f Adult s i n Urba n U.S . Whos e Maximum

1-Hour Averag e C O Exposur e Occur s i n Selecte d Concentratio n Range s Unde r Alternativ e Ai r Qualit yAssumption s 8- 7 8- 5 Estimate s o f Occurrence s i n th e Cardiovascula r

Adul t Urba n U.S . Populatio n o f 8-Hour Averag e C O Exposure s abov e Selecte d Concentratio n Value s Unde r Alternativ e Ai r Qualit yAssump

tion s 8- 8 8- 6 Estimate s o f Cardiovascula r Adult s i n Urba n U.S .

wit h8-Hou r Averag e C O Exposur e Abov e Selecte d Concentratio n Value s Unde r Alternativ e Ai r Qualit yAssumption s 8- 9 8- 7 Estimate s o f Cardiovascula r Adult s i n Urba n U.S .

Whos e Maximum8-Hour Averag e C O Exposur e Occur s i n Selecte d Concentratio n Range s Unde r Alterna

tiv e Ai r Qualit yAssumption s 8-1 0 8- 8 Estimate s o f Occurrence s amon g Cardiovascula r

Adult s i n Urba n U.S . o f COHbLevel s Exceedin g Selecte d Value s unde r Alternativ e Ai r Qualit y Assumption s 8-1 1 8- 9 Estimate s o f Cardiovascula r Adult s i n Urba n U.S .

Experiencin g COHbLevel s Exceedin g Selecte d Value s unde r Alternativ e Ai r Qualit yAssump

tion s 8-1 2 8-1 0 Estimate s o f Cardiovascula r Adult s i n Urba n U.S .

Whos e MaximumCOHbLeve l Occur s i n Selecte d Concentratio n Range s Unde r Alternativ e Ai r Qualit yAssumption s 8-1 3 8-1 1 Percentag e o f Cardiovascula r Adul t Urba n U.S .

Populatio n Experiencin g COHbLevel s Exceedin g Selecte d Value s under

- Alternativ e Ai r Qualit y Assumption s 8-1 4

xv iP.1 6



### TABLE S (continued ) Numbe r Pag e 8-1 2 Estimate s o f Cardiovascula r Adult s i n Urba n U.S .

Experiencin g COHbLevel s Exceedin g Selecte d Value s a Give n Numbe r o f Day s Assumin g 9 PPM/ 1 EXE XStandar d i s Attaine d 8-1 5 C- l Estimate d Concentration s (EC's ) Develope d b y EP Aan d Correspondin g Ai r Qualit yIndicator s (AQI's ) fromTabl e 5- 6 (concentration s i n part s pe r million ) C- 4

x v nP.1 7



### ACKNOWLEDGMENT S
Th e developmen t o f a genera l mode l fo r assessin g populatio n exposure s associate d wit hpossibl e Nationa l Ambien t Ai r Qualit y Standard s (NAAQS's ) and th e applicatio n o f tha t mode l t o carbo n monoxid e (CO ) reporte d i n thi s documen t hav e involve d th e effort s o f manypeople
. Th e followin g person s associate d wit hPEDC o Environmental , Inc. , playe d importan t role s i n conductin g thi s study
. Coautho r Ro yPau l develope d th e populatio n movemen t algorithm s and create d th e populatio n dat a files
. Coautho r Te d Johnso n develope d th e statistica l model s use d t o proces s ai r qualit ydat a and manage d th e developmen t o f ai r qualit yand populatio n dat a bases
. Iren e Griffi n assiste d i n th e compilatio n o f populatio n and ai r qualit ydata
. Jame s Cape l create d and debugge d th e compute r program s whic hprocesse d ai r qualit ydata
. Barbar a Biagu n develope d estimate s o f backgroun d pollutan t con centrations
. Diann e Gupto n and Dia n Dixo n type d th e report . Georg e M . Duggan , Strategie s and Ai r Standard s Divisio n (SASD) , U.S . Environmenta l Protectio n Agenc y(EPA) , designe d and imple

mente d th e compute r program s use d t o calculat e exposur e estimates
. Thoma s McCurdy , SASD , EPA , facilitate d conduc t o f th e stud yand co-manage d th e SAS D exposur e assessmen t programwit hHenr yThomas
. Muc ho f th e cohor t dat a use d i n th e mode l i s base d upo n wor k don e b ySR I International. 1 

### Dr . Willia mF . Biller , EP Acontractor , an d Thoma s B . Feagans , SASD , develope d th e genera l exposur e mode l and th e metho d use d t o extrapolat e exposur e estimate s fo r individua l stud yarea s t o th e nation
. Th e genera l mode l make s us e o f idea s develope d b yEPA' s Offic e o f Researc han d Developmen t and others. 2 

### Th e mode l wa s firs t applie d t o carbo n monoxid e a t a n earl ystag e o f it s develop

ment . 3 

### Alate r versio n o f th e mode l wa s applie d t o nitroge n dioxid e and particulat e matter. 1 

### *' 5 

### An expositio n o f th e genera l mode l i s availabl e from EPA. 6



### REFERENCE S 1
. Mar c F . Roddin , Haze l T . Ellis , and Wahee d M . Siddiqee , Background Dat a fo r Huma n Activit yPatterns , Vols
. 1 and 2 , Draf t fina l repor t prepare d fo r Strategie s and Ai r Standard s Division , Offic e o f Ai r Qualit yPlannin g and Standards , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N.C . 27711 , Augus t 1979
.

xv i 1 1P.1 8



### SECTION1 INTRODUCTION
Unde r th e Clea n Ai r Act , th e Environmenta l Protectio n Agenc y (EPA ) i s responsibl e fo r establishin g Nationa l Ambien t Ai r Qualit y Standard s (NAAQS's ) an d fo r reviewin g them periodicall yt o deter

min e thei r adequacie s o n th e basi s o f recen t experienc e an d research
. I n vie wo f thes e responsibilities , the Strategie s an d Ai r Standard s Divisio n (SASD ) o f the Offic e o f Ai r Qualit yPlan

ning an d Standard s (OAQPS ) i s explorin g th e us e o f quantitativ e method s fo r assessin g healt hrisk s associate d wit hpropose d ai r qualit ystandards
. An importan t aspec t o f healt hris k assessmen t i s th e esti

matio n o f populatio n exposure . Fo r th e pas t fewyears , SAS D ha s bee n engage d i n th e developmen t o f a n exposur e mode l suitabl e fo r evaluating alternativ e ambien t ai r standards
. The mode l i s known a s NEM , a n acrony

mfo r NAAQ S Exposur e Model
. Tw o version s o f NE Mhav e bee n developed
. Th e exposur e dis

tric t versio n o f NE Msimulate s th e pollutan t concentratio n expecte d t o occu r i n selecte d exposur e district s withi n a stud yare a unde r user-specifie d regulatoryscenarios
. I t the n adjust s thes e estimate s t o accoun t fo r a n exhaustiv e se t o f microenvironment s an d simulate s typica l movement s o f populatio n subgroups , calle d cohorts , throughthe district s an d microenvironments
. Output s o f the simulatio n programar e populatio n exposur e estimate s a t specifie d pollutan t levels
. Thre e indice s o f exposur e ar e use d currently , an

d mor e ar e being investigated
. Th e othe r versio n o f NE Msubstitute s "neighborhoo d types " fo r exposur e districts
. Thi s repor t describe s thi s alternativ e mode l an

d it s applicatio n t o fou r U.S . urba n area s (Chicago , IL , St . Louis , MO-IL , Philadelphia , PA , an d Lo s Angeles , CA ) t o estimat e populatio n exposure s associate d wit halternativ e NAAQS' s 1- 1P.1 9



### propose d fo r carbo n monoxid e (CO)
. Result s o f thes e analyse s ar e include d i n thi s report . Th e contributio n o f indoo r C O source s t o tota l populatio n exposur e i s als o evaluated
.



### 1- 2P.2 0



### SECTION2 OVERVIE WO F TH E EXPOSUR E MODE L Analysi s o f populatio n exposur e unde r presen t an d propose d Nationa l Ambien t Ai r Qualit yStandard s (NAAQS's ) require s tha t th e significan t factor s contributin g t o tota l huma n exposur e b e take n int o account . Consequently , thes e factor s hav e bee n in

corporate d int o th e NAAQ S Exposur e Mode l (NEM) , a simulatio n mode l capabl e o f estimating huma n exposur e i n selecte d urbanize d area s unde r user-specifie d regulatoryscenarios
. Th e genera l mode l ha s bee n designe d s o tha t pollutant s a s divers e a s ozon e an d C O ca n b e accommodate d withou t makin g change s t o the basi c NE Mprogram . Instead , inpu t dat a file s ar e develope d t o reflec t th e assume d spatia l characteristic s o f th e specifi c pollutan t bein g analyzed
. I n on e versio n o f th e model , ai r qualit ydat a ar e selecte d t o represen t a smal l numbe r o f discret e exposur e districts
. Thi s versio n ha s bee n applie d t o NO

- an d particulat e matter . Anothe r versio n incorporatin g th e concep t o f "neighbor

hoo d types " i s th e basi s o f th e C O exposur e analysi s describe d i n thi s report . Thi s sectio n briefl ydiscusse s the difference s betwee n thes e two version s o f NEM . 2. 1 TH E EXPOSUR E DISTRIC T VERSIONO F NE M I n th e exposur e distric t versio n o f NEM , lan d area s withi n a selecte d stud

yare a ar e represente d b ylarge , bounde d "exposur e districts. " Th e populatio n withi n eac hexposur e distric t i s assigne d t o a singl e discret e point , th e populatio n centroid
. Th e ai r qualit yleve l withi n eac hexposur e distric t i s represente d b yth e ai r qualit yleve l a t th e populatio n centroid , whic hi s estimate d fo r eac hhou r o f th e yea r b yusing monitorin g dat a from adjacen t monitorin g sites
. Becaus e pollutant s i n th e ai r ca n b e
2- 1

### modifie d considerabl ywhe n entering a buildin g o r vehicle , the s ambien t ai r qualit yestimate s ar e adjuste d t o accoun t fo r fiv e differen t microenvironments : indoor s a t wor k o r school , indoor
. a t hom e o r othe r locations , insid e a transportatio n vehicle , outdoor s nea r a roadway , an d othe r outdoo r locations
. NE Msimu

late s hour-by-hou r movement s o f representativ e populatio n group s throughdifferen t district s o f th e cit yan d throughdifferen t microenvironments , accumulating th e resulting exposur e ove r a perio d o f on e year . Becaus e degre e o f exposur e an d susceptibilit yt o effect s o f pollutio n varywit hage , occupation , an d intensit yo f exercise ; th e tota l populatio n o f eac hstud yare a i s divide d int o age occupatio n (A-0 ) groups , an d eac hA- 0 grou

p i s furthe r subdivide d int o thre e o r mor e subgroups
. Fo r eac hsubgroup , a typica l pat

ter n o f activit ythroughth e fiv e microenvironment s i s establishe c an d a n exercis e leve l (high , medium , o r low ) withi n eac hi s speci

fie d
. Unit s o f populatio n analyze d byNE Mar e calle d cohorts
. Eac hcohor t i s identifie d byexposur e distric t o f residence , by exposur e distric t o f employment , byA- 0 group , an d byactivity

patter n subgroup
. Durin g eac hhou r o f th e year , eac hcohor t i s assigne d t o a particula r exposur e distric t an d a particula r microenvironment
. Sinc e NE Msimulate s hour-by-hou r ai r qualit y i n eac hdistric t an d eac hmicroenvironment , th e hourl yexposure s o f eac hcohor t mayb e summe d ove r a on e yea r period
. Annua l cohor t exposure s ar e summe d t o provid e exposur e estimate s fo r eac hA- 0 group , which , i n turn , ar e summe d fo r al l group s t o provid e a n estimat e o f tota l populatio n exposur e fo r a particula r stud yarea . Outpu t o f NE Mi s a serie s o f table s showing fre

quenc ydistribution s o f tota l exposur e a t differen t averaging time s (e.g. , 1 hour , 8 hours , 1 year ) using differen t measure s o f exposur e (e.g. , numbe r o f person s wit hexposure s abov e selecte d pollutan t levels)
. I n developing dat a base s fo r thi s versio n o f NEM , PEDC o had t o establis hexposur e district s withi n eac hstud yare a tha t woul d accommodat e th e availabl e breakdown s o f transportatio n an d censu s 2- 2X l

d i d

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. p n

1 I NP.2 3

ANALYST SELECT S ( 1 ) TES T CITY (2 ) NAAQ S STAR TPROGRA M

• SELEC T NEX T COHOR T

DETERMINE COHOR T POPULATION COHOR T POPULATION FIL E

NEX T HOUR 

# ~r~
DETERMINE EXPOSUR E OISTRIC T MICROENVIRON , ACTIVIT YLEVE L COHOR T LOCATION FIL E

DETERMIN E AMBIEN T AI RQUALIT Y (AQ ) I N EXPOSUR E DISTRIC T

c > DETERMIN E ADJUSTE DAQ PERNAAO S 1 — HOURL YAI RQUALIT Y FIL E

ROLL-BAC KFACTOR S

DETERMINE AQIN MICROENVIRONMEN T MICROENVIRONMEN T FACTOR S

ACCUMULAT E 1 HOURO F EXPOSUR E A T Af l LEVE LI

N A REGISTE R



# - B LAS T HOUR ?

YE S

N O EN

DO F A- 0 GROUP ?

YE S

. SUMMARIZ E COHOR T EXPOSURE S FO R AGE-OCCUPATION

(A-O ) GROUP S
N O AL LGROUP S

COMPLETE ?
YE S
(OUTPUT ) FREQUENC YDISTRIBUTION O F EXPOSURE S B

YA- 0 GROU P 

### Figur e 2-1 . Flow

diagram o f exposur e distric t versio no f NEM . 2- 4P.2 4



### Th e neighborhoo d versio n o f NE Mi s particularl yappropriat e fo r analyzin g C O exposure . Sinc e suburba n neighborhood s generall y hav e lowe r populatio n densitie s an d lowe r traffi c densitie s tha n center-cit yneighborhoods , theygenerall yhav e lowe r C O levels
. Likewise , commercia l an d industria l neighborhood s generall yhav e C O sourc e pattern s differen t fromresidentia l neighborhoods
. Figur e 2- 2 show s th e flo wdiagramfo r the neighborhoo d versio n o f NEM . Th e principa l difference s betwee n th e two version s li e i n th e concep t o f people-movemen t an d i n th e structur e o f dat a file s use d a s inputs
. Th e concep t o f neighborhood-typ e an d method s o f creatin g populatio n dat a base s ar e describe d i n th e nex t section
. 2. 3 REFERENCE S 1
. Te d Johnso n an d RoyPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Nitroge n Dioxide , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s an d Ai r Standard s Divi

sion , Offic e o f Ai r Qualit yPlannin g an d Standards , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N . C . 27711 , May1981
. 2
. Te d Johnso n an d RoyPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Particulat e Matter , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s an d Ai r Standard s Division , Offic e o f Ai r Qualit yPlanning an d Standards , U.S . Environ

menta l Protectio n Agency , Researc hTriangl e Park , N . C . 27711 , Augus t 1981
.

2- 5P.2 5

ANALYS T SELECT S (1 ) TES T CITY (2 ) NAAQ S STAR T PROGRA

M )GRA

SELEC T NEX T COHOR T

DETERMINE COHOR T POPULATION

NEX T HOUR 

# ~l
DETERMINE NEIGHBORHOODTYP E MICROENVIRON , ACTIVIT YLEVE L

DETERMINE AMBIEN T AI RQUALIT Y (AQ ) I N NEIGHBORHOODTYP E 3 COHOR T POPULATION FIL E

COHOR T LOCATION FIL E

DETERMIN E ADJUSTE DAQ PERNAAQ S

DETERMINE AQI

N MICROENVIRONMEN T 

# I ACCUMULAT E I HOURO F EXPOSUR E A T A qLEVE LI

N A REGISTER 

# ig— j LAS T HOUR ? HOURL YAI RQUALIT Y FIL E

ROLL-BAC KFACTOR S

MICROENVIRONMEN T FACTOR S

N O EN

OO F A- 0 GROUP ?
YE S

SUMMARIZ E COHOR T EXPOSURE S FO R AGE-OCCUPATION

(A-O ) GROUP S
N O AL LGROUP S

COMPLETE ?
YE S
(OUTPUT ) FREQUENCYDISTRIBUTION

OF EXPOSURE S B

YA- 0 GROUP Figur e 2-2 . Flo

w diagram

o f neighborhoo d 2- 6 versiono f NEM .P.2 6

SECTIO N3 SIMULATIO NO F POPULATIO NMOVEMEN T

NE Msimulate s movemen t o f small , homogeneou s group s calle d cohort s throug hzone s o f varyin g ai r quality
. Thi s sectio n describe s th e developmen t o f compute r file s delineatin g cohor t movement s an d th e allocatio n o f stud yare a populatio n amon g th e j cohorts
.
3. 1 COMPOSITIO NO F COHOR T FILE S Acohor t i s define d a s a grou p o f individual s havin g a statistica l facto r i n commo n i n a demographi c study
. I n th e neighborhoo d versio n o f NEM , al l member s o f a particula r cohor t (1 ) liv e i n th e sam e neighborhoo d typ e (NT) , (2 ) wor k i n th e sam e NT , (3 ) ar e member s o f th e sam e age-occupatio n group , an d (4 ) ar e member s o f a subgrou p with^ a specifie d dail y activit ypattern . Consequently , a compute r fil e describin g a cohor t i s labele d a s t o hom e NT , wor k NT , age-occupatio n group , an d activit ypattern . I n th e exposur e distric t versio n o f NEM , th e activit ypat

ter n fo r a cohor t contain s hourl yassignment s t o predetermine d exposur e districts
. Cohor t movemen t ca n b e visualize d a s trans

fer s betwee n geographicall yconnecte d districts
. Fo r example , Figur e 3- 1 illustrate s movemen t betwee n variou s district s o f th e Lo s Angeles-Sa n Bernardin o studyarea . B ycontrast , th e activit y patter n fo r a cohor t i n th e neighborhoo d versio n o f NE Mcontain s hourl yassignment s t o predetermine d NT's . Aparticula r N T ma yb e scattere d ove r a n entir e stud yare a an d mixe d wit hothe r NT's , a s show n i n Figur e 3-2
. Movemen t fro mon e N T t o anothe r ma yrepre sen t a significan t chang e i n ai r qualit ylevel , withou t involvin g a significan t chang e i n geographi c location
. 3- 1 !C J

I



# Fi9ur

e3 1 

# 'ffCssriiKK : ans-?" * " -P.2 8



### MILE S
Figur e 3-2
. Patter no f neighborhoo dtype s i na

portio no f th e Philadelphi a studyarea .

3- 3Assignmen t

fo r Hou r _

1 Neighborhood-Typ e 5 (suburbanresidential )
Midroenvironmen t 2 (indoors , non-work )
i Exercis e leve l 1 * - (low ) COHOR T Definedby : (1 ) Neighborhood-Typ e o f Residenc e (5 ) (2 ) Neighborhood-Typ e fo r Wor k(2 ) (3 ) Age-Occupatio n Group(2 ) (4 ) Activit y

Patter n Subgroup(1 ) Assignmen t fo r Hou r # 2 Neighborhood-Typ e 2 (center-cit y

commercial )
Microenvironmen t 1 (indoors-at-work )
Exercis e leve l 1 (low )

Figur e 3-3 . Representationo f people-movemen t in

the neighborhoo dversiono f NEM .P.3 0



### I n additio n t o NT assignments , th e activit ypatter n fil e contain s hourl yassignment s o f eac hcohor t t o a microenvironmen t an d an exercis e leve l fo r typica l weekdays , Saturdays , an d Sundays
. Exposur e t o C O during a particula r hou r i s determine d b yadjusting ambien t C O fo r the assigne d NT according t o the assigne d micro

environment
. Becaus e highexercis e level s mayinduc e a highe r uptak e o f airborn e chemical s int o the body , NE Mkeep s trac k o f exercis e level s s o tha t exposur e distribution s can b e calculate d fo r eac hexercis e leve l separately
. ' I n developing activit ypattern s appropriat e fo r analyzing C O exposure , w e divide d eac hA- 0 grou p int o thre e t o si xsub

group s whic hcoul d b e describe d b yon e o r mor e demographi c vari

able s affecting exposur e (see Tabl e 3-1)
. Thes e variable s in

clud e commuting time , wor k shift , wor k locatio n (e.g. , inside , outside , i n moto r vehicle) , age , an d degre e o f mobility
. Th e populatio n o f eac hage-occupatio n grou p wa s apportione d among it s constituen t subgroup s according t o demographi c statistic s obtaine d fro

mthe Burea u o f Censu s an d othe r sources. 1 

### Wheneve r possible , the activit ypattern s develope d fo r th e subgroup s wer e base d o n actua l human activit ydata
. Becaus e suchdat a ar e limite d t o a smal l numbe r o f studie s initiate d fo r othe r purposes , man ysimplifying assumption s wer e mad e i n constructing the activit y patterns . Fo r example , retire d person s wit hlimite d mobilit y wer e assigne d t o the outdoo r microenvironmen t fo r fewe r hour s than retire d person s wit hful l mobility
. Housewive s wit hschool

ag e childre n a t home wer e assigne d t o the transportatio n vehicl e microenvironmen t mor e ofte n than housewive s wit hn o childre n a t home
. I n eac hcase , an attemp t wa s mad e t o construc t a n activit y patter n whic hwa s consisten t wit hou r intuitive expection s o f wha t member s o f tha t subgrou p woul d d o o n a typica l weekday , Saturday , o r Sunday
. The resulting activit ypattern s ar e containe d i n a separat e document. 2 

### Sampl e activit ypattern s ar e presente d i n Appendi xA .

3- 5P.3 1



### TABL E 3-1
. DESCRIPTIONAND APPORTIONMENT O F ACTIVIT YPATTER

NSUBGROUP S
Age-occupationgrou p Student s 1 8 an

dove r

Manager s an

dprofessional s

Sale s worker s

Clerica l an

dkindre

dworker s

Craftsme

nan dkindre

d worker s

Operative s an

dlaborer s Code a



### Oil 01 2 013 014 021 02 2 02 3 02 4 031 03 2 03 3 03 4 03 5 041 042 - 

### 043 04 4 045 046 051 05 2 053 054 055 056 061 06 2 06 3 064 065 06 6 Subqrou p Descriptio

n <3 0 mi ncommute , 8 a.m . <3 0 mi ncommute , 9 a.m . >3 0 mi ncommute , 8 a.m . >3 0 mi ncommute , 9 a.m . <3 0 mi ncommute , singl e hous e <3 0 mi ncommute , other s >3 0 mi ncommute , singl e hous e >3 0 mi ncommute , other s clas s clas s clas s clas s famil y
famil y

Indoo r work , <3 0 mi ncommut e Indoor work , >3 0 mi ncommut e Outdoor wor

k Indoor an

doutdoor wor

k Travelin

g Indoo r work , 1s t shift , commut e Indoor work , 1s t shift , commut e Indoo r work , 2n

dshift , commut e Indoor work , 2n

dshift , commut e Outdoor wor

k Indoor an

doutdoor wor

k Indoor work , 1s t shift , commut e Indoo r work , 1s t shift , commut e Indoo r work , 2n

dshif t Indoo r work , 3r

dshif t Outdoor wor

k Indoo r an doutdoor wor

k Indoor work , 1s t shift , commut e Indoor work , 1s t shift , commut e Indoo r work , 2n

dshif t Indoor work , 3r

dshif t Outdoor wor

k Worki nmotor vehicl e <3 0 mi n >3 0 mi n <3 0 mi n >3 0 mi n

<3 0 mi n >3 0 mi n

<3 0 mi n >3 0 mi n Percent



### 23 4 5 1 1 21
4 7 2 1 22 1 0 43 21 5 9 2 2
5 6 26 9 4 1 4
50 24 1 0 2 4 1 0
39 1 8 6 3 1 8 1 6 (continued ) 3- 6TABL

E 3- 1 (continued )
Aqe-occupatio ngrou p Service , military , and privat e househol dworker s

Housewive s

Unemploye dand-retire d

Childre nles s tha n5

Childre n5 t o 1 7 Code 3 

### 08 1 08 2 08 3 08 4 08 5 08 6 09 1 09 2 09 3 10 1 10 2 10 3 10 4 10 5 106 111 11 2 11 3 11 4 12 1 12 2 12 3 124 12 5 12 6 Subqroup

Descriptio n Service , da ytim e work , <3 0 mi n commut e Service , da ytim e work , >3 0 mi n commut e Service , nigh t tim e Service , i n moto r vehicl e Militar y Privat e househol d N o childre na t hom e Som e childre n<1 3 N o childre n<13 , som e 1 3 t o 1 8 Unemployed , jo bhuntin g Unemployed , no t jo bhuntin g Disable d Retired , ful l mobilit y Retired , limite dmobilit y Retired , confine dindoor s 0 t o 1 2 month s 1 3 t o 2 4 month s 2 5 t o 3 6 month s 3 7 t o 6 0 month s Elementar yschool , <3 0 mi n commut e Elementar yschool , >3 0 mi n commute , wal k o r bik e Elementar yschool , >3 0 mi n commute , vehicl e Hig hschool , <3 0 mi n commut e Hig hschool , >3 0 mi n commute , wal k o r bik e Hig hschool , >3 0 mi n commute , vehicl e Percen t


### 3 6 1 7 2 2 

### 3 14 

### 8 4 2 4 9 

### 9 2 0 2 4 2 0 3 0 

### 4 2 2 1 2 0 2 0 3 9
5 6 

### 4 7 2 6 

### 2 5
Firs ttwo digit s indicat e age-occupatio n group , thir d digi tindicate s subgroup

.

3- 7____ _



### 3. 2 TYPE S O F NEIGHBORHOOD S Lik e th e exposur e distric t versio n o f NEM , estimatio n o f huma n exposur e t o C O using th e neighborhoo d versio n involve s a simpl e two-waytri p model
. Thi s mode l assume s tha t eac hcohor t i s locate d eithe r i n it s home NT o r it s wor k NT during eac hhou r o f th e year . T o us e thi s model , i t i s necessaryt o determin e hourl yambien t C O concentratio n i n home NT' s an d wor k NT's . I n reviewing ai r qualit ydat a availabl e fromC O monitors , PEDC o foun

d tha t informatio n abou t neighborhoo d setting s o f moni

tor s is.verylimited , excep t fo r tw o Nationa l Ai r Monitorin g System s (NAMS ) monitor s i n eac hcit ywher e site s hav e bee n sur veye d i n detail
. Fo r mos t monitors , neighborhoo d dat a ar e limite d t o th e station-typ e (ST ) identifier s liste d i n the Storag e an d Retrieva l o f Aerometri c Dat a (SAROAD ) system . Th e S T identifier s classif ymonitor s according t o geographi c locatio n an d lan d use . Geographi c locatio n categorie s includ e 1
. Cente r Cit y- cor e are a o f th e city , no t it s incorporate d limit s 2
. Suburba n 3
. Rura l 4
. Remot e - fa r enoughfroman yactivit yt o measur e back

ground levels
. Lan d us e categorie s varywit hgeographi c locatio n a s follows : 1
. Cente r Cit yan d Suburban a . Industria l - product-oriente d establishment s suc h a s manufacturing concerns , utilities , mining , an d graineries
. b
. Commercia l - service-oriente d establishment s suc h a s retai l establishments , shopping centers , ga s stations , an

d laundromats
. c . Residentia l - becaus e othe r area s ar e als o use d residentially , thi s categoryi s use d onl yi n the absenc e o f a dominating industria l o r commercia l influence
. d
. Mobil e - site s locate d i n airports , truc k o r bu s terminals , o r an expresswaycloverleaf
. Site s place d nea r parking lot s woul d probabl yb e bette r categorize d a s industria l o r commercial
.

3- 8P.3 4



### 2
. Rura l

3
. a . Industria l - same a s cente r cit yan d suburba n industrial
. b
. Commercia l - same a s cente r cit yan d suburba n industrial
. c . Nea r urba n - site s locate d i n a rura l area , ye t clos e enought o a majo r urba n cente r t o b e affected : b yth e urba n area . d
. Agricultura l - site s locate d nea r orchards , cro p raising , cattle , an d sheep grazing
. Remot e T o simplif yth e selectio n o f monitor s t o represen t NT's , w e establishe d NT' s t o conformt o th e SAROA D ST's . Sinc e al l stud y area s wer e urbanized , ST' s wit hrura l an d remot e categorie s wer e droppe d fromconsideration
. The remainin g eigh t ST' s provid e the basi s fo r eigh t NT' s use d fo r classifyin g cohort s i n a populatio n exposur e analysi s (se e Tabl e 3-2)
. Thes e NT' s ar e code d wit h number s 1 through9 t o facilitat e thei r us e i n compute r files
.

TABL E 3-2
. NEIGHBORHOO

D TYPE S (NT's ) AN

D CODES



### N T Center-cit yresidentia l Center-cit ycommercia l Center-cit yindustria l Center-cit ymobil e Suburba nresidentia l Suburba ncommercia l Suburba nindustria l Suburba nmobil e No t use do r "other " Compute r cod e 

### 1 2 3 4 5 6 7 8 9

3- 9'.3 5



### Onc e NT' s ar e established , theyca n b e use d lik e exposur e district s withi n a n activit ypatter n compute r file
. Distric t code s 1 t o 9 ca n b e replace d wit hNT code s 1 t o 9 i n bot hth e definitio n o f cohort s and i n hour-by-hou r assignments , a s shown i n Figur e 3-4
. Th e concep t o f "home " no wrefer s t o hom e NT rathe r tha n hom e district , and "work " refer s t o wor k NT rathe r tha n wor k district
. Th e 2-wa ytri p mode l i s retained ; commuter s mov e froma hom e NT t o a , wor k NT i n th e mornin g and retur n i n th e evening
. Consequently , activit ypattern s develope d fo r th e neighborhoo d versio n o f NE Mus e th e same forma t a s activit ypat

tern s develope d fo r the exposur e distric t version
. 3. 3 ESTIMATIONO F COHOR T POPULATION S Ther e wer e severa l problem s associate d wit hestablishin g cohort s an

d determinin g cohor t population s i n th e neighborhoo d versio n o f NEM . First , NT' s di d no t provid e a convenien t uni t fo r assemblin g populatio n data
. A s shown o n a previou s ma p (Figur e 3-2 ) neighborhoods

- occu r i n irregula r pattern s scattere d throughou t a city
. Boundarie s o f neighborhood s d o no t correspond t o th e boundarie s o f censu s tract s o r an yothe r uni t use d b y th e Burea u o f Censu s t o organiz e populatio n data
. Second , eve n i f i t wer e theoreticall ypossibl e t o collec t populatio n dat a fo r eac hNT , suc ha n effor t woul d requir e a significan t expenditur e o f resource s whic hwer e no t availabl e fo r thi s purpose . Conse

quently , w e mad e certai n simplifyin g assumption s s o tha t popu latio n dat a tha t ha d alread ybee n assemble d fo r th e exposur e distric t versio n o f NE Mcoul d b e use d i n C O exposur e analysis
. Populatio n dat a assemble d fo r previou s NE Manalyse s consiste d o f th e number s o f peopl e i n 1 2 A- 0 group s wh o reside d i n eac ho f th e exposur e district s comprisin g eac ho f fou r stud yareas . Th e firs t ste p i n usin g thi s dat a wa s t o determin e th e numbe r o f peopl e i n eac hA- 0 grou p residin g i n center-cit yneighborhood s an d th e numbe r o f peopl e residin g i n suburba n neighborhoods
.

3-1 0P.3 6



### Dumm y fo r cit y name Day-of-wee k

cod e Cohor t I D \ I I 1 T CITY).XXXH042

W CITYXXXXH042

W1 2Wll TA. A AM-P M

cod e | , , 1 H2-1H21H21H21H21H21431W11W11W11W11W11



### 12-h r locatio n assignments

Hom e — N T A- 0 group J Patter n— (Subgrou p 1-6 ) 

### Wor kN T AA A 1W11W11W31H21H21H21H21H21H21H2 1

L-Activit y

leve l cod e (2n

dhr )
1 

### —Microenvironmen t cod e (2n dhr )

' Locatio nassignmen t (2n dhr ) Work(W ) o r Home(H ) Neighborhoo dType s (NT )

Day-of-wee kcodes : 1 = weekda y 2 = Saturday 3 = Sunday
AM-PM codes : Activit y codes : 1 = low activit y leve l 2 = mediu

m activit y

leve l 3 • highactivit y

leve l
Microenvironmen t codes : 1 = AM , hr s 1-1 2 2 = PM , hr s 1-1 2 1 - indoor s a t wor k 2 = indoors , othe r 3 = transportatio nvehicl e 4 = transportation , othe r 5 = outdoor s

Figur e 3-4 . Content s o f cohor t activit y file .

3-1 1P.3 7



### Thi s wa s possibl e becaus e eac hexposur e distric t coul d b e classi

fie d center-cit yo r suburba n b yit s geographi c locatio n an d pre dominan t lan

d us e pattern . Classification s o f exposur e district s wer e establishe d i n stud yarea s use d fo r previou s NE Manalyses , a s show n i n Tabl e 3-3
.
TABL E 3-3
. GEOGRAPHIC CLASSIFICATIO NO F EXPOSUR

E DISTRICT

S

Stud yare a Chicag o Philadelphia St . Loui s Los Angeles Exposur e district s Center-cit

y 1,2,3,4, 5 1 1,2,3, 4 1 Suburba n 6,7, 8 2,3,4,5, 6 5,6, 7 2,3,4,5,6, 7

Using thi s breakdown , th e A- 0 grou p residenc e dat a coul d b e classifie d int o suburban o r center-city , a s liste d i n Tabl e 3-4
. Th e nex t ste p wa s t o furthe r subdivid e thes e genera l neighborhoo d classification s int o specifi c NT's . Fo r thi s breakdown , i t wa s necessaryt o us e transportatio n dat a an d certai n assumption s abou t movement s o f A- 0 group s an d thei r plac e o f residence
. T o simplif yth e problemo f NT assignments , w e assume d tha t al l peopl e liv e i n a residentia l neighborhood
. Thi s migh t b e considere d obviou s b ydefinition , bu t some neighborhood s ar e bette r characterize d b ypredominan t lan

d uses . Fo r example , ..som e peopl e live i n a predominantl yindustria l neighborhood
. However , i t i s no t importan t t o us e pur e definition s o f neighborhoods , bu t t o differentiat e highpollutio n residentia l neighborhood s from presumabl ylo wpollutio n residentia l neighborhoods
. Using th e NT' s liste d i n Tabl e 3-2 , thi s dichotom yca n b e approximate d b y center-cit yresidentia l (hig hpollution ) an

d suburban residentia l (lo wpollution)
. I n St . Louis , fo r example , w e approximate d th e populatio n living i n center-cit yresidentia l NT' s b ythe per son s living withi n neighborhood s classifie d center-cit yi n Tabl e 3-3 , an d the populatio n living withi n suburban-residentia l NT' s 3-1 2

### TABL E 3-4 . A- 0 GROU P POPULATION B YRESIDENTIALNEIGHBORHOO D CLASSIFICATION S IN

FOU RSTUDYAREA S

c o i o o 

### Ag e 1 . 2 . 3 . 4 .

N 5 . 

### 6 . 7 . 8 . 9 . 10 . 11 . 12 . -occupatio

ngrou p Student s 18 + Professionals/Manager s Sale s worker s Clerica l an

dkindre

d worker s Craftsmen , foremen , kindre d Operative s an

d laborer s Far m worker s Military , servic e househol d Marrie dhousewive s Unemploye

dor retire

d Childrenunde r 5 Children5-1 7 TOTAL S 

### Ch i Center Cit y 83,98 2 387,74 1 82,70 1 269,59 9 174,64 8 206,36 3

- 137,20 1 170,20 9 57,39 9 50,29 5 120,70 3 1,704,84 3 cag

o
Suburba n 25,63 9 119,33 6 25,48 2 66,87 7 60,79 5 55,62 6

- 30,80 3 92,43 9 16,38 5 38,45 5 92,29 2 624,11 5 Philadelphi a

Center Cit y 18,42 9 43,00 2 14,39 8 64,79 2 39,05 2 98,76 8 

### 86 2
57,69 5 93,11 0 96,97 9 75,48 1 209,44 4 812,00 9 Suburba

n 75,59 4 214,87 8 74,56 7 199,80 1 116,30 3 161,89 0 1,89 1 103,17 2 290,81 4 212,05 5 166,76 6 508,24 3 2,125,97 0 

### St .

Center Cit y 16,31 9 35,84 8 11,72 9 50,08 8 24,11 5 63,18 8 

### 685
46,63 6 65,40 2 87,66 8 49,97 3 147,65 9 599,32 0 Loui s

Suburban 23,19 1 70,85 3 23,06 3 48,28 4 27,66 4 40,01 8 

### 84 3
26,15 5 81,38 5 54,18 0 50,02 9 163,02 6 608,69 0 Lo s Angele s

Center City 75,04 7 155,87 6 46,36 4 151,10 0 66,58 9 134,67 9 

### 97 8
71,97 2 166,34 5 202,60 1 115,73 1 267,64 4 1,454,92 4 Suburba

n 266,63 4 645,75 8 198,84 7 490,55 5 333,38 1 478,97 3 12,84 7 321,55 2 810,28 6 563,15 4 538,81 4 1,617,64 2 6,278,41 2P.3 9



### b yth e numbe r o f peopl e living i n al l area s classifie d suburban
. Thi s allocatio n procedur e allowe d the populatio n o f eac hstud y are a t o b e divide d int o residentia l neighborhoo d categorie s whic h ar e als o geographi c areas . Th e resulting breakdow n o f populatio n i s show n i n Tabl e 3-4
. W e nex t determine d wor k NT' s b ymaking simple , intuitiv e assumption s abou t the wor k environmen t o f A- 0 groups . Fo r example , w e assume d tha t childre n unde r 5 year s di d no t g o t o work , bu t staye d a t home
. W e assume d tha t childre n 5-1 7 year s o f ag e wen t t o "work " a t a School , bu t tha t the schoo l wa s locate d i n the same NT a s thei r residence
. W e assume d tha t operative s an d laborer s worke d primaril yi n industrie s locate d withi n an indus

tria l NT . Th e ful l roste r o f assumption s i s liste d i n Tabl e 3-5 ; thes e statement s allowe d the wor k NT o f eac hA- 0 grou p t o b e classifie d residential , commercial , o r industrial , bu t theydi d no t determin e whethe r NT' s ar e center-cit yo r suburban
. Fo r thi s purpose , transportatio n dat a wer e use d i n the for mo f home-to

wor k tri p tables
. A s documente d i n othe r reports, 3 

### ' 1 

### * home-to-wor k tri p table s wer e previousl ydevelope d fo r eac hstud yare a base d o n dat a pro vide d b yregiona l transportatio n planning agencies
. Thes e tri p table s mayb e visualize d a s a n n xn arra ywhic hlist s the numbe r o f trip s take n during a typica l da yfro meac htransportatio n zon e o f a cit yt o everyothe r zone . I n previou s NE Manalyses , array s wer e reduce d i n siz e b yaggregating transportatio n zone s int o exposur e districts
. The resulting smalle r array s showe d the numbe r o f trip s fro m eac hexposur e distric t t o everyothe r ex posur e district
. I n the C O analysis , eac hstud yare a tri p tabl e wa s furthe r condense d int o a 2 x2 array , becaus e the onl ygeographi c element s use d wer e suburban an d cente r cit yNT classifications
. I n othe r words , al l exposur e district s wer e aggregate d int o eithe r a suburban super-distric t o r a center-cit ysuper-district
. Th e resulting collapse d tri p table s ar e liste d i n Tabl e 3-6
. A s i n previou s NE Manalyses , w e assume d tha t the fractio n o f al l trip s 3-1 4P.4 0

TABL E 3-5 . ASSUMPTION S CONCERNINGWORKNT' S OF A- 0 GROUP S



### 1 . 2 .

3 . 4 . 5 . 6 . 7 . A- 0 Group Student s 18 + Professiona l an

d

Sale s worker s
Clerica l worker s
Craftsme n administrativ e

Operative s an

dlaborer s

Farmer s Assumption s Wor kN T i s same a s home NT . Al l wor kina commercia l neighbor hood ; some wor ki nsuburba nareas , other s incenter-city . Wor kneighborhoo di s suburban commercia l o r center-cit y commercial . Wor kneighborhoo di s suburban commercia l o r center-cit y commercial . Wor kneighborhoo di s suburban industria l o r center-cit y industrial . Wor kneighborhoo di s suburban industria l o r center-cit y industrial . Ther e ar e no farmer s inurbanize d area . 8 . Service , militar y an dhousehol d
9 . Housewive s 10 . Unemploye dan

dretire d

11 . Childre nunde r 5 12 . Childre n5 t o 1 7 Wor kneighborhoo di s same a s home . Wor kneighborhoo di s same a s home . Wor kneighborhoo di s sam e a s home . Wor kneighborhoo di s same a s home . Wor kneighborhoo di s same a s home .

3-1 5P.4 1

TABL E 3-6

. COLLAPSE D HOME-TO-WOR KTRI P TABLES , EXPRESSE D A S NUMBE R O F TRIP S AN D FRACTIO N O F TRIP S Study are a Chicag o Philadelphi a
St . Loui s
Lo s Angele s Fro mhom e

Center-cit y Suburba n Center-cit y Suburba n Center-cit y Suburba n Center-cit y Suburba n 

### T o Cente r cit y 3,182,820(0.935) a 524,260(0.843 ) 270,517(0.718 ) 405,867(0.353 ) 114,627(0.793 ) 76,977(0.435 ) 246,970(0.570 ) 581,480(0.133 ) wor k Suburba n 221,720(0.065 ) 97,300(0.157 ) 106,507(0.283 ) 743,723(0.647 ) 29,920(0.207 ) 99,957(0.565 ) 1,861,400(0.430 ) 3,800,720(0.867 ) Numberi n parenthesi s i s fractio n o ftrips

. 

### take nfro mon esuper-distric t t o anothe r

coul db euse dt o repre - sen t tri p distribution s fo r al lA- 0 groups . Thes efraction s wer e use di namodifie d2-way tri p mode lt o calculat enumbe r o f person s i neac hcohort , a s follows :

*
____ . IAI 1 

### (3-1 )
wher e P 

### H,A,S, W( P

### H,A / ( F 

### S ) "H-W

" H /



### H,A,S, W H, A

'H-W

"H = home NT

= age-occupatio n category

= subgrou

p specifie d b

yactivit ypatter n

= wor k NT

= populatio n o f a cohor t whic hi s define d b ythe subscript s

= populatio n o f a n age-occupatio n categoryi n a home NT (center-cityresidentia l o r suburban residential )

= fractio n o f person s i n A- 0 grou p allocate d t o subgrou p

= numbe r o f trip s fro ma home super-distric t t o a wor k super-distric t

= tota l numbe r o f trip s b yal l A- 0 group s fro ma home super-distric t t o bot hsuper-district s (suburba n o r center-city)
.
3-1 6P.4 2



### Calculatio n o f cohor t population s mayb e illustrate d b yan example
. Using the modifie d tri p model , on e cohor t mayb e define d a s thos e person s residing i n suburban-residentia l NT i n St . Loui s | wh o ar e manager s o r professional s (A- 0 Grou p 2) , wh o followtypi

ca l activit ypattern s o f subgrou p 2 , an d wh o ar e locate d i n center- ! cit ycommercia l N T during working hours
. Thi s definitio n i s con sisten t wit hthe lis t o f assumption s i n Tabl e 3-5
. Thi s tabl e show s tha t 70,85 3 peopl e live i n suburban residentia l NT' s i n '• St . Loui s an

d belong t o A- 0 Grou p 2
. FromTabl e 3- 1 w e fin d tha t the fractio n o f A- 0 Grou p 2 belonging t o subgrou p 2 i s 2 1 percent . : 

### Fromth e collapse d tri p table , Tabl e 3-6 , w e fin d tha t 110,04 6 I peopl e ou t o f a tota l o f 397,20 0 peopl e fro msuburban residentia l ! NT' s g o t o a center-cit yNT fo r work
. Thus' , w e maycalculat e the cohor t populatio n a s follows : J

P 

### 5,2,2, 2 - (70,853 ) (0.21 ) -f^§§f f = 4,12 2 persons . \ 

## j Population s o f al l cohort s wer e calculate d similarly ; a complet e ' lis t o f cohort s an

d estimate d cohor t population s i s provide d i n j Appendi xB . Onc e method s fo r representing peopl e movemen t wer e estab

lished , an

d method s wer e devise d fo r calculating number s o f peopl e following variou s movemen t patterns , ther e remaine d the tas k o f estimating ai r qualit ylevel s t o whic hcohort s wer e exposed
. Developmen t o f ai r qualit ydat a i s the subjec t o f sub

sequen t sections
. 3. 4 REFERENCE S 1
. Memorandu

mfro mTe d Johnson , PEDC o Environmental , t o Thoma s McCurdy , Strategie s an d Ai r Standard s Division , U.S . En

vironmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolin a 27711 , Apri l 6 , 1982
. 2
. Te d Johnson , Activit yPattern s fo r NE MAnalysi s o f Carbo n Monoxid e Exposure , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s an

d Ai r Standard s Division , Offic e o f Ai r Qualit yPlanning an d Standards , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N . C , Octobe r 1982
. 3-1 7P.4 3



### 3
. Te d Johnso n an d RoyPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Nitroge n Dioxide , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s an d Ai r Standard s Division , Offic e o f Ai r Qualit yPlanning an d Standards , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N . C , May1981
. 4
. Te d Johnso n an d RoyPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Particulat e Matter , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s an d Ai r Standard s Division , Offic e o f Ai r Qualit yPlanning an d Standards , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N . C. , Augus t 1981
.

3-1 8P.4 4



### SECTION4 PREPARATIONO F AI R QUALIT YDAT A

NE Mrequire s representativ e outsid e ai r qualit ydat a fo r eac hneighborhoo d typ e i n th e formo f a complet e yea r o f hourl y averag e values
. Thi s sectio n describe s th e procedure s use d fo r i 

### selecting appropriat e dat a sets , fo r validatin g thes e data , an d fo r filling i n missin g values
. 4. 1 SELECTIONO F REPRESENTATIVE DAT ASET S T o simplif yth e compute r simulation , ai r qualit yi n al l neighborhood s classifie d a s belongin g t o a specifi c NT wa s assume d t o b e a linea r functio n o f ai r qualit ymonitore d a t a singl e rep resentativ e monitorin g site
. Consequently , fo r eac hstud yare a w e had t o selec t on e monitorin g sit e pe r NT . W e originall ycon sidere d usin g th e 8 NT' s liste d i n Tabl e 3-1 ; however , evalua

tio n o f dat a availabilit yindicate d tha t ther e wa s a n insufficien t numbe r o f center-cit ymobil e an d suburba n mobil e site s t o includ e thes e NT' s i n the exposur e analysis
. Th e remaining NT' s were : o center-cit yresidentia l (CR) , o center-cit ycommercia l (CC) , o center-cit yindustria l (CI) , o suburba n residentia l (SR) , i 

### o suburba n commercia l (SC) , an d o suburba n industria l (SI)
. Tabl e 4- 1 list s dat a set s selecte d t o represen t thes e NT's . Thes e dat a set s wer e selecte d accordin g t o the following procedure
. (1 ) Dat a fo r th e same yea r wer e use d fo r al l site s i n a i stud yarea . Th e yea r wa s selecte d t o maximiz e the numbe r o f NT' s tha t coul d b e represente d b yacceptabl e

4- 1P.4 5

TABL E 4-1 . DATA

SET S (mg/m J ) SELECTE DFORANALYSI S OF POPULATION EXPOSUR E TOCARBON

MONOXID E I

N FOURCITIE S

Studyare a andyea r Chicag o (1979 )

Lo s Angele s (1977 )

Philadelphi a (1978 )

St . Loui s (1978 ) 

### N

T C R C C C I S R S C SI C R 

### -C C C I S R S C SI C R C C C I S R S C S I C R C C C I S R S C SI S T C C C C C I S R S C S C C R C C SI S R S C SI C C C C SI S R S R SI C R C C C I S R S C C I SAROAD cod e 141220039F0 1 141220040F0 1 141220026H0 1 140780002G0 1 145680001G0 1 147160005G0 1 056400003F0 1 05390000110 1 05090000210 1 05872000110 1 05023000110 1 05090000210 1 397140026H0 1 397140026H0 1 397140022H0 1 3-97140004H0 1 397140004H0 1 397140021H0 1 264280007H0 1 264280064H0 1 264280061H0 1 26020000260 1 261040001G0 1 264280061H0 1 Prob e

heigh t (ft ) 

### 11 1 1 2 6 1 5 1 5 3 9 3 2 2 0 1 5 15 1 5 1 5 13 13 13 17 17 13 3 5 1 

### 12 13 14 12 1-hour

obs
. 617 2 839 2 761 5 866 4 766 2 842 5 792 1 794 0 777 5 777 7 788 8 777 5 777 3 777 3 808 8 819 3 819 3 848 5 594 4 746 6 753 9 681 7 701 0 753 9 Geo . mea n 

### 1. 8 2. 9 2. 6 1. 3 1. 4 1. 4 1. 8 2. 6 3. 9 3. 4 3. 0 3. 9 2. 2 2. 2 1. 3 0. 8 0. 8 1-
. ? 

### 5. 4 2. 5 2. 6 2. 6 2. 5 99t h per centil e 

### 7. 0 15. 8 

### 9. 8 6. 7 7. 0 .6. 4 

### 9. 2 18. 4 17. 3 13. 8 13. 8 17. 3 10. 4 10. 4 

### 5. 8 5. 8 5. 8 8. 1 6. 4 10. 7 11. 8 

### 9. 3 9. 8 11. 9 Note s 

### b a

b

a b a a

a. b 

### a a, b 

### a a, c
a, d 

### a

b
detaile dsit e locatio ndescriptio navailabl e a t MDAD . sit e wit hmatchin gS T no t available . sit e wit hmatchin gS T no t appropriate . geometri c mea nno t calculate dbecaus e dat a completenes s <7 5 percent .

4- 2P.4 6

dat a sets . Adat a se t wa s considere d acceptabl e i f i t containe d a t leas t 5 8 3 9 observation s (66 % completeness)
. (2 ) Whe n possible , a n N T wa s represente d bya dat a se t wit h a correspondin g S T (e.g. , th e center-cit ycommercia l N T fo r St . Loui s wa s represente d bysit e 264280064H01 , whic hha s a center-cit ycommercia l ST)
. (3 ) I f tw o o r mor e site s wit hth e require d S T wer e available , th e sit e judge d mos t representativ e o f th e N T wa s select

ed
. I n 1 1 cases , degre e o f representatio n wa s determine d fro mphotograph s o f sit e surrounding s an d detaile d loca l lan d us e description s o n fil e i n th e Monitorin g an d Dat a Analysi s Divisio n (MDAD) , EPA . Summar ystatistics , prob e location , an d dat a completenes s wer e als o con sidere d i n selectin g sites
. (4 ) I f n o sit e wit hth e require d S T wa s available , th e sit e wit hth e mos t simila r S T wa s selected
. Wheneve r pos sible , th e MDA D photograph s an d lan d us e description s wer e use d i n selectin g alternat e sites
. I n si xcases , NT' s an d ST' s d o no t matc hbecaus e a sit e wit h th e appropriat e S T wa s no t available
. Fo r th e Chicag o center-cit y residentia l NT , w e selecte d a center-cit ycommercia l sit e wit h lo wgeometri c mea n an d 99t hpercentil e values
. Fo r th e Chicag o suburba n industria l NT , w e selecte d a suburba n commercia l sit e locate d i n Skokie , a tow n nea r Chicag o generall ycharacterize d a s industrial
. I n Lo s Angeles , w e use d a suburba n industria l sit e (th e onl yindustria l sit e i n th e studyarea ) t o represen t th e center-cit yindustria l NT . Asuburba n commercia l sit e i n Afto n wa s use d fo r th e St . Loui s suburba n industria l N T becaus e Afto n i s locate d nea r a n industria l area . Th e center-cit yre sidentia l N T i n Philadelphi a wa s represente d bya center-cit y commercia l sit e whic hphotograph s reveale d t o b e surrounde d b y apartments . Similarly , th e center-cit yindustria l N T i n Philadelphi a wa s represente d bya suburba n industria l sit e becaus e photograph s suggeste d tha t th e sit e i s actuall ylocate d i n a heavil yurbanize d area . 4- 3P.4 7



### I n on e case , a sit e wit hth e correc t S T wa s no t use d becaus e photograph s reveale d a sit e wit ha differen t S T wa s mor e appropriat e Th e onl ysuburba n commercia l sit e i n Philadelphi a (397140024H01 ) i s surrounde d o n al l side s b yPhiladelphi a Internationa l Airport
. Sit e 397140004H01 , althoug hlabele d suburba n residential , wa s use d instea d becaus e i t had commercia l establishment s nearby
. 4. 2 VALIDATIONO F AI R QUALIT YDATA Ai r qualit ydat a set s containin g erroneou s value s ca n bia s th e result s o f exposur e studies , especiall yi f the error s occu r a s extrem e values
. T o ensur e goo d dat a quality , the dat a set s liste d i n Tabl e 4- 1 wer e screene d fo r anomalou s value s using thre e methods : (1 ) th e gap test , (2 ) the pattern s test , an d (3 ) visua l inspection
. 4.2. 1 Th e Gap Tes t Th e Monitorin g an

d Report s Branc h(MRB ) o f MDAD ha s develope d a standardize d dat a revie wprogramcalle d th e MR B Validatio n Re

port. 1 

### Thi s programuse s two differen t concept s t o identif y anomalie s (unexpecte d dat a patterns ) i n hourl ydat a sets . Th e firs t approach , calle d th e Gap Test , i s a statistica l analysi s o f dat a ove r a 1-mont hperiod
. Thi s analysi s assume s tha t the dat a ca n b e modele d reasonabl ywel l b ya smoot hprobabilit ydis

tributio n curve . Tw o exponentia l curve s ar e fi t t o the dat a using th e 50t han

d 95t hpercentile s o f the dat a fo r on e fi t an d the 50t han

d 99.9t hpercentile s fo r th e othe r fit
. Bot hfit s emphasiz e th e uppe r tai l o f th e distribution
. Al l dat a value s ar e arrange d i n orde r o f magnitud e an d the programexamine s "gaps " i n th e data , i.e. , larg e difference s betwee n succeeding ordere d values
. Using th e fitte d distributio n functions , th e program calculate s th e probabilit ytha t a gap o f magnitud e "x " coul d b e obtaine d b

ychance
. Agap tha t i s greate r tha n woul d b e expecte d fromth e underlyin g assumption s i s flagge d a s a dat a anomaly
. Th e strengt ho f th e Gap Tes t i s tha t th e criteri a fo r identify

ing anomalie s ar e base d o n a n analysi s o f th e dat a se t itself
. 4- 4It s weaknes s i s tha t th e assume d distributio n i s no t alway s ap propriate ; consequentl ysom e fals e failure s ma yoccur . I n thi s study , th e outpu t fro mth e ga p tes t wa s evaluate d t o determin e whethe r o r no t th e flagge d dat a wer e plausibl e fro m othe r point s o f view
. I t wa s desire d tha t dat a no t b e rejecte d unles s a stron g cas e fo r erro r couldW-be-established
. Flagge d dat a wer e usuall yretaine d i f th e teste d dat a se t containe d a larg e numbe r o f missin g values , onl yon e o f th e two

- fitte d curve s indicate d a n anomaly , o r ther e wer e mor e tha n fiv e observation s abov e th e gap . Dat a flagge d b yth e ga p tes t wer e mor e ."likel yt o b e rejecte d i f the ywer e flagge d b yothe r tests . 4.2. 2 Th e Patter n Tes t Th e secon d tes t i n th e MR B Validatio n Progra mi s calle d th e Patter n Test . I t i s compose d o f 5 subtest s carrie d ou t fo r eac h 24-hou r period , a s follows : (1 ) High-valu e tes t - th e tes t flag s a n hourl yvalu e tha t exceed s a predetermine d limit
. Fo r carbo n monoxide , th e criterio n depend s o n whethe r o r no t th e measuremen t wa s take n durin g rus h hour s (7-1 1 a.m . o r 4- 9 p.m.)
. Durin g rus hhour s th e limi t i s 6 6 pp man d a t othe r time s i t i s 4 4 ppm . (2 ) Adjacent-hou r differenc e tes t - thi s tes t assume s tha t dat a tak e th e for m o f a n auto-correlate d tim e series , i.e. , a larg e jump o r dro p i n th e value s withi n 1 hou r i s no t expected
. I f ther e i s a jump o r dro p greate r tha n 2 2 ppm , th e suspec t valu e i s flagged
. (3 ) Dixon-rati o tes t - thi s i s a statistica l analysi s o f th e highes t an d lowes t valu e foun d durin g th e day
. I f Ai s th e differenc e betwee n th e tw o highes t value s an d B i s th e rang e o f value s fo r th e day , the n th e Dixo n Rati o i s A/B
. I f thi s rati o i s statisticall ysignificant , th e suspec t values-ar e flagged
. (4 ) Spike-tes t - th e difference s betwee n a suspec t hourl y valu e an d th e precedin g an d followin g hourl yvalu e i s measured
. i I f eithe r o f thes e tw o difference s i s greate r tha n 2 0 ppm , o r i f



### 4- 5P.4 9



### th e suspec t valu e i s 50 0 percen t greate r tha n eithe r o f the adjacen t values , th e suspec t valu e i s flagged
. (5 ) Consecutiv e highvalue s - i t i s unusua l fo r a serie s o f hourl ymeasurement s t o remai n a t a highlevel
. I f fou r con secutiv e hourl yvalue s ar e greate r tha n 4 0 ppm , th e dat a ar e flagged
. PEDC o evaluate d th e result s o f applyin g MR B Validatio n Pro

gramt o SO

- dat a i n fou r cities. 2 

### Thi s analysi s le d t o the developmen t b

yPEDC o o f a revise d validatio n program . Thi s ne w program(denoted her e a s MRB-2 ) contain s improvement s i n th e patter n test s an

d a n optio n fo r graphica l outpu t o f flagge d data
. Th e Dixo n Rati o Tes t wa s enhance d fo r al l pollutant s i n orde r t o incorporat e th e recommendation s o f a recen t EPAreport. 3 

### I n th e . ne wversion , th e formula s fo r testing th e hig han d lo whourl y value s from

eac h24-hou r perio d varyaccordin g t o th e numbe r o f hourl ymeasurement s recorde d durin g the period
. Th e spik e tes t wa s enhance d s o tha t a n individua l hourl yvalu e i s compare d t o th e two (rathe r tha n one ) preceedin g value s an d th e two succeeding values
. I n addition , MRB- 2 incorporate s a preliminaryscreening test , s o tha t i f al l th e value s i n a 24-hou r perio d ar e low , th e patter n test s ar e skipped
. B ypassin g ove r dat a tha t d o no t requir e testing , th e compute r programrun s mor e quickly
. Th e strengt ho f th e patter n tes t programi s tha t i t use s mor e tha n on e tes t t o identif ypossibl e anomalies
. It s weaknes s i s tha t th e criteri a fo r identifyin g anomalie s i s predetermine d fo r al l test s excep t th e Dixo n Rati o Test . Th e patter n tes t programcoul d b e improve d b yadjustin g tes t criteri a accordin g t o the dat a reporte d b yeac hindividua l monitorin g site
. 4.2. 3 Visua l Inspectio n Georg e Dugga n o f SAS D ha s develope d a compute r program whic h wil l plo t al l hourl yvalue s i n a yea r o f dat a o n a singl e graph
. Suc hdat a plot s ar e usefu l i n identifying unusuall yhighvalue s an d long string s o f identica l values
. Al l dat a set s use d i n th e

4- 6P.5 0



### C O exposur e analysi s wer e plotte d using thi s program an d reviewe d b yPEDCo . Value s whic happeare d anomalou s wer e flagge d fo r furthe r investigation
. 4.2. 4 Result s o f Dat a Screening C O level s recorde d a t monitorin g site s ca n b e drasticall y altere d b

yshort-termchange s i n loca l emissions
. Exhaus t from a deliverytruc k idling nea r a monito r mayresul t i n a highread

ing whic happear s totall yinconsisten t wit hothe r C O value s recorde d tha t day
. However , thi s reading shoul d no t b e exclude d fromth e exposur e analysi s sinc e i t represent s a n exposur e situ

atio n whic hmayoccu r frequentl ythroughou t the stud yarea . Con

sequently , w e decide d t o retai n flagge d dat a unles s theyappeare d t o b e th e obviou s resul t o f instrumen t malfunctio n o r transcriptio n error . A s discusse d below , fewo f th e flagge d dat a fel l int o thes e categories
. Tabl e 4- 2 list s dat a anomalie s flagge d b yon e o r mor e o f th e screening methods
. O f th e anomalie s detected , mos t wer e flagge d b yth e gap tes t o r visua l inspection
. N o value s wer e flagge d b y th e highvalu e test , th e spik e test , o r th e consecutiv e hou r test . Eigh t dat a anomalie s wer e identifie d b yvisua l inspection
. I n tw o cases , Chicag o sit e 145680001G0 1 an d St . Loui s sit e 261040001G01 , long string s o f value s equa l t o 0. 1 ppmo r zer o wer e found
. W e assume d i n bot hcase s tha t thes e value s wer e incorrectl yentere d i n plac e o f missin g value s an d remove d them fromth e data
. Th e othe r si xanomalie s involve d unusuall yhigh values
. Analysi s showe d tha t th e flagge d highvalue s occurre d simultaneousl ya t th e two Chicag o site s an d a t the two Philadelphi a sites
. W e considere d thi s sufficien t corroboratio n t o retai n thes e values
. W e als o retaine d th e value s flagge d b yvisua l inspectio n a t site s 260200002G0 1 an d 264280064H0 1 i n St . Louis
. I n th e firs t case , fou r larg e value s (20.8 , 26.3 , 26.1 , an d 26. 6 ppm ) wer e pre cede d an

d followe d b

yvalue s o f 3. 1 ppm . Thi s episod e wa s unusua l

4- 7

### TABL E 4-2 . ANOMALIE S FLAGGE DB YDATA SCREENING

i 0 0 Stud

y are a Chicag o

Lo s Angele s Philadelphi a

St . Loui s SAROA Dcod e 140780002G0 1 145680001G0 1

05390000110 1
397140021H0 1 397140022H0 1 397140026H0 1 260200002G0 1 261040001G0 1 264280064H0 1 

### N

T S R S C



### C C

S I C I CR.C C S R S C C C Dat e 12-29-7 9 12-29-7 9 2-7 9

2-07-7 7 2-17-7 7 6-7 8 1-25-7 8 1-25-7 8 6-7 8 7-24-7 8 12-7 8 4-09-7 8 Anomal y

9 value s 2

l 1 0 pp m 9 value s _

> 1 0 pp m longstringo f value s nea r zer o larg e valu e larg e valu e larg e ga p 6 value s >

_1 0 pp m 1 2 value s >

_ 1 0 pp m larg e ga p 4 value s > 2 0 pp

m longstringo f value s nea r zer o 2 value s > 1 5 pp

m 

### Ga p

X

X X X X

X Screenin gprocedur e Adjacen t hou r



### X Dixo n rati o

X X



### X Visua l inspect . X X X

X X

X X XP.5 2



### enought o caus e th e dayt o b e als o flagge d b yth e gap tes t usin g ; 50t han d 95t hpercentile s an d th e adjacen t hou r test . However , j 

### the daywa s no t flagge d whe n th e gap tes t wa s repeate d usin g th e 50t han d 99. 9 percentiles
. I n th e othe r case , two larg e value s [ (15. 2 an

d 16. 5 ppm ) wer e precede d an d followe d b

ysmalle r values , j Thes e dat a wer e als o flagge d b yth e 50/9 5 gap tes t bu t no t b yth e 50/99. 9 gap test . Th e 50/9 5 gap tes t als o flagge d dat a a t sit e 397140021H0 1 i n [ Philadelphi a an

d a t sit e 260200002G0 1 i n St . Louis
. Sinc e thes e j dat a wer e no t flagge d b yan yothe r test , including th e 50/99. 9 | gap test , theywer e accepted
. i Thre e day s o f dat a wer e flagge d b yth e Dixo n Rati o test . j Becaus e analysi s o f thes e dat a indicate d tha t th e assumptio n o f normalit ywa s no t valid , w e repeate d th e Dixo n Rati o tes t usin g th e logarithm s o f th e recorde d value s a s recommende d b yNelson , e t al. 3 

### Thi s time n o value s wer e flagge d b yth e test . W e con - i elude d ther e wa s n o probabl e caus e unde r a n assumptio n o f log

normalit yfo r rejectin g th e data
. I n summary , w e investigate d 1 2 case s o f dat a flagge d b y variou s screening procedures
. W e retaine d th e anomalie s i n j al l bu t th e tw o case s wher e visua l inspectio n had identifie d long string s o f value s equa l t o 0. 1 ppmo r zero . Thes e value s wer e remove d fromth e dat a sets . Th e nex t sectio n describe s th e methodologyuse d t o fil l i n thes e an d othe r missin g values
. 4. 3 SIMULATIONO F MISSINGVALUE S I NHOURL YAVERAG E C O DAT ASET S NE Mrequire s ai r qualit ydat a set s wit hvalue s fo r every hou r o f th e year . Sinc e absolutel ycomplet e dat a set s wer e no t available , gap s wer e fille d i n usin g a time serie s mode l develope d b yJohnso n an

d Wijnberg. 1 

### *

4- 9P.5 3



### 4.3. 1 Th e Tim e Serie s Mode l Acomplet e yea r o f hourl yaverag e dat a take s th e formo f a time serie s x, , x_ , ... , x. , ... , xwher e n = 8760
. W e ca n fi t

l & t

_n 

### thi s serie s exactl yb yth e mode l 438 0 x . = x+ I

R.cos(co. t + 9. ) (4-1 ) z

### j= l J . J 3 

### wher e xi s th e arithmeti c mea n o f th e series , R . an d 9
. ar e amplitud e an

d phas e angl e value s determine d byFourie r analysis , an d O J 

### • = 2TTJ/8760
. 

### Omissio n o f on e o r mor e o f th e 438 0 Fourie r cosin e term s wil l yiel d a n approximat e fit
. Becaus e Fourie r cosin e function s ar e orthogona l and becaus e th e contributio n o f eac hcosin e functio n t o th e representatio n o f th e origina l tim e serie s i s proportiona l t o it s amplitud e R. , w e ca n provid e a leas t square s fi t t o th e origina l time serie s wit hmcosin e term s b y usin g th e cosin e term s wit hth e mlarges t amplitudes
. W e denot e eac htermo f thi s estimate d time serie s a s x . wher e t 

### « _m x . = x+ _

R.co s (w. t + 6. ) (4-2 ) r 

### i= l x

### ' 1


### an d R. , co. , an

d 9
. ar e th e parameter s o f th e Fourie r termhavin g th e it hlarges t amplitude
. Fo r convenience , w e wil l refe r t o th e mFourie r term s i n Equatio n 4- 2 a s th e essentia l cyclica l compo nen t (ECC)
. Th e difference s betwee n th e x . serie s an d th e xserie s compris e the d
. series , i.e. , d 

### t = x 

### t " X 

### t ' (4


### ~ 3 ) 

### W e ca n defin e ho wwel l th e x . serie s represent s th e x . serie s b yth e goodnes s o f fi t statisti c

4-1 0P.5 4

0

### / 438 0 -, I R

- / I Rr

(4-4 ) V j= i 3

. 2 A s mincreases , r increase s an d th e goodnes s o f fi t improves
. 2 Not e tha t r = 1 whe n m= 4380
. I f th e x . serie s exhibit s autocorrelation , th e d
. serie s i s likel yt o exhibi t autocorrelation
. On e mean s o f characterizin g a serie s whic hexhibit s autocorrelatio n i s t o us e a n AR(p ) proces s (i.e. , a n autoregressiv e proces s o f orde r p)
. I n thi s case , eac h d
. termca n b e expresse d a s

d t 

### = a t 

### + <j 

### , 1 

### d t



### _1 

### + <D 2 

### d t



### _ 2 

### +..."• + * p 

### d t



### _ p 

### (4-5 )
wher e a . i s a normall ydistribute d randomvariat e wit hmea n 0 an d c 

### 2 varianc e a . CX 

### Estimate s o f <J>

, , <J>, , ... , <J

> ca n b e obtaine d b yfirs t esti

matin g eac hautocorrelatio n p . , usin g the relationshi p p . = r . wher e c 

### k

r v

### = - £ k = 1 , 2 , ... , p (4-6 )
an d / 876 0 / c . = (1/8760 ) Z

(d
. - d ) (d
. , - d)
. (4-7 ) K k+ - t t-J C 

### Fromthes e estimates , th e Yule-Walke r estimate s o f th e autoregres

siv e parameter s ca n b e obtained. 5 

### Autocorrelatio n o f th e d
. serie s wil l decreas e a s m increase s sinc e a n increasing portio n o f th e xf c 

### serie s autocorrelatio n i s explaine d b

yth e cosin e functions
. W e assume d tha t mos t o f th e autocorrelatio n i n the dat a correspondin g t o k >

_3 woul d b e con taine d i n th e EC C w e selecte d an d tha t a n AR(2 ) proces s woul d suffic e t o characteriz e th e d
. series
. I n thi s case ,

r . ( 1 - r 5 

### ) 4> i = — j , (4-8 ) 1 

### " r 

### l
4-1 1P.5 5



### r - r 2 

### r 2 

### r ,

. , = —^ , (4-9 )

1 

### " r 

### l an d

a 

### a = c 

### 0 ( 1 

### " *l r 

### l " *2 r 

### 2 ) # 

### (4-10 ) Thi s AR(2 ) proces s represent s a stationarytime serie s i f i t meet s certai n condition s describe d b yBo xan

d Jenkins. s 

### Atheoretica l AR(2 ) proces s wil l hav e non-zer o value s o f p . fo r k > 2 tha t decreas e graduall yaccordin g t o th e relationshi p

p 

### k = 

### *l p 

### k- l + 

### *2 p 

### k- 2 k > 0 (4-11 ) unti l a poin t i s reache d wher e th e distributio n o f r , i s approxi

matel ynorma l wit hmea n zer o and standar d erro r

a (r k 

### ) = ^ | ( 1 + 2p. 2 

### + 2p 2 2 

### )
. (4-12 )
Th e value s o f p . an d p - ar e estimate d b yr , and r- . N o mor e tha n 5 % o f th e value s o f r , fo r larg e value s o f k shoul d deviat e from zer o b ymor e tha n tw o standar d errors. 7 

### I f w e ca n selec t an EC C suc htha t the autocorrelation s i n th e d
. serie s correspondin g t o k > 2 ar e consisten t wit hEquation s 4-1 1 an d 4-12 , the n a n AR(2 ) proces s shoul d suffic e t o character

iz e the.d , series
. T o selec t thi s ECC , w e ca n star t b ydeterminin g th e d
. serie s tha t correspond s t o m= 1
. W e the n calculat e r , fo r value s o f k tha t ar e likel yt o b e significant
. Thes e includ e k = 3 , 4 , 6 , 8 , 12 , 24 , and 16 8 fo r typica l ai r qualit ydata
. I f th e r , value s ar e no t consisten t wit hEquation s 4-1 1 an d 4-12 , w e determin e th e d
. fo r m= 2 and repea t th e analysis
. W e continu e increasing munti l th e r , value s fo r k > 2 mee t ou r criteria
. A t thi s stage , w e shoul d hav e a combinatio n o f EC C an d AR(2 ) proces s tha t wil l adequatel ycharacteriz e the data
.

4-1 24.3. 2 Initia l Treatmen t o f Missin g Value s

Fourie r analysi s canno t b e applie d t o a tim e serie s i f on e o r mor e value s ar e missing
. I f ai r qualit ydat a t o b e analyze d ar e incomplete , som e metho d o f estimatin g missin g value s mus t b e use d prio r t o analysis
. Bloomfield 8 recommend s replacin g eac h missin g observatio n bya linea r combinatio n o f it s neighbor s i f mos t o f th e missin g value s ten d t o occu r i n small , isolate d groups . I f a ga p containin g b- l missin g value s occur s betwee n value s xan d x. , eac hmissin g valu e x . ca n b e estimate d by linea r interpolatio n a s

x t = x a + E ( t " a)(x a + b" x a } ' (4 " 1 3 )

However , linea r interpolatio n ma yno t yiel d reasonabl e estimate s o f missin g one-hou r value s fo r larg e gaps , especiall yi f the yar e bounde d b yextrem e values
. I n thes e cases , th e arithmeti c mea n (x ) ma yb e a bette r estimat e o f eac hmissin g value
. Inspectio n o f dat a set s t o b e use d i n th e C O populatio n exposur e analysi s suggeste d tha t th e arithmeti c mea n shoul d b e use d t o fil l i n gap s wheneve r ga p lengt hexceede d 7 2 hour s and/o r on e o f th e boundar y value s exceede d th e arithmeti c mea n bymor e tha n tw o standar d deviations
. I n othe r cases , linea r interpolatio n produce d reason abl e results
. 4.3. 3 Procedur e fo r Simulatin g Missin g Value s Th e tim e serie s mode l describe d abov e wa s th e basi s fo r th e followin g procedur e fo r simulatin g missin g values
. (1 ) Th e mea n an d standar d deviatio n o f eac hdat a se t wer e calculated
. (2 ) Gap s wit hlength s exceedin g 7 2 hour s and/o r wit hbound

ar yvalue s exceedin g th e arithmeti c mea n bymor e tha n tw o standar d deviation s wer e identified
. Thes e gap s wer e fille d i n wit hth e arithmeti c mean . (3 ) Linea r interpolatio n wa s use d t o fil l i n th e remainin g gaps . 4-1 3P.5 7

(4 ) Fourie r analysi s wa s applie d t o th e augmente d tim e serie s create d i n step s (2 ) an d (3)
. (5 ) A n EC C wa s constructe d whic hcontaine d th e smalles t numbe r o f cosin e term s require d t o produc e a d serie s consisten t wit hEquation s 4-1 1 an d 4-12
. (6 ) Th e d
. serie s wa s represente d b ya n AR(2 ) proces s b y t • _ usin g Equation s 4-8 , 4-9 , an d 4-1 0 t o determin e <f>, ,

_r\ 1 (j ) - , an d c. (7 ) A n a . serie s wa s forme d b ydividin g eac hter mi n a N(0,1 ) rando mserie s b ya. Fo r consistency , th e sam e cl rando m serie s wa s use d i n eac hcase . (8 ) Missin g d
. value s wer e simulate d usin g th e relationshi p 

# K - *A-i +

# ^ t 

# - 2 +

# v(4



# - i4 )

(9 ) Missin g x . value s wer e fille d i n usin g th e mode l

r\ mA x . = x + Z R.cos(o). t + 9. ) + d
. (4-15 ) t i= 1 1 1 i t
t o creat e th e fina l augmente d dat a set . Not e tha t th e fina l simulatio n (Equatio n 4-15 ) use s informatio n concernin g th e cyclical , autoregressive , an d stochasti c propertie s o f th e tim e serie s whic har e omitte d i n th e initia l estimate s mad e i n step s (2 ) an d (3)
. Figur e 4- 1 show s a dat a se t whic hi s missin g 175 0 values
. Figur e 4- 2 show s th e augmente d dat a se t afte r th e initia l simu

latio n o f missin g value s [step s (1 ) throug h(3) ]
. Figur e 4- 3 show s th e fina l augmente d dat a se t wit hmissin g term s fille d i n byaddin g a n appropriat e AR(2 ) proces s t o th e mos t significan t Fourie r cosin e function s [step s (4 ) throug h(9) ]
. Thi s two-ste p proces s simulate s missin g term s whic har e consisten t wit hbot h th e cyclica l an d th e rando mcharacte r o f th e know n values
.

4-1 4o o 

### S i

o o 10 .

I M t n



## --f—r—frrrrr. —n r.~;— 1 :rr MI R

### np « 

### mi JU N JU LAU G SE P 

### S I LOUI S CO I-HOU R - SUOURBfi N COIUIERCIfi L Figur e 4-1 . Hourl y

averag e 197 8 carbo nmonoxid e dat a reporte db y monitorin gsit e 261040001G0 1 inSt . Louis .o o • o N

O O * 10 .

I c n



## . r W R fiPR IM
. JU N JU LAU G SE P OC I 

### S I LOUI S C

O I-HOU R -SUBURBfi N COMERCM L Figur e 4-2 . Hourl y

averag e 197 8 carbo nmonoxid e dat a fo r monitorin gsit e 261040001G0 1 inSt . Loui s afte r initia l simulatio no f missin gvalues .

### o

o

I



# S I LOUI S C OI-HOUR- SUBURBAN COHHERCIfl L Figur e 4-3 . Hourl y

averag e 197 8 carbo nmonoxid e dat a fo r monitorin gsit e 261040001G0 1 i nSt . Loui s afte r fina l simulatio no f missin gvalues .P.6 1



### 4. 4 REFERENCE S 1
. Screenin g Procedure s fo r Ambien t Ai r Qualit yData , publicatio n no . EPA-450/2-78-037 , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N.C , Jul y1978
. 2
. RoyA . Paul , R . B . Faoro , W . F . Hunt , "Screening S0 2 

### dat a anomalie s from

fou r tes t cities, " Technica l Conferenc e Transactions , America n Societ yfo r Qualit yControl , Milwaukee , Wisconsin , 1981
. 3
. A . C . Nelson , D . W . Armentrout , an d T . R . Johnson , Validatio n o f Ai r Monitorin g Data , publicatio n no . EPA-600/4-80-030 , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N.C , Jun e 1980
. 4
. Te d Johnso n and Luk e Wijnberg , "Time serie s analysi s o f hourl yaverag e ai r qualit ydata, " pape r no . 81-33.5 , pre sente d a t th e 74t hAnnua l Meetin g o f th e Ai r Pollutio n Contro l Association , Philadelphia , Pennsylvania , Jun e 21-26 , 1981
. 5
. G.E.P . Bo xan d G.M . Jenkins , Time Serie s Analysis : Fore

castin g an

d Control , Holden-Day , San Francisco , 1976 , p . 55
. 6
. Bo xan

d Jenkins , p . 58
. 7
. Bo xand Jenkins , pp . 3 5 an d 59
. 8
. Pete r Bloomfield , Fourie r Analysi s o f Tim e Series : An Intro

duction , John Wile yan d Sons , Ne wYork , 1976 , p . 245
.

4-1 8P.6 2



### SECTIO N5 SIMULATIO

NO F AI R QUALITYEXPECTE D AT FIXE D MONITORIN GSIT E UNDE R ALTERNATIVE CARBONMONOXID E STANDARD S
Th e augmente d dat a set s describe d i n Sectio n 4. 3 wer e assume d t o represen t the curren t statu s o f ai r qualit ya t a representativ e monito r i n eac hneighborhoo d typ e (NT)
. T o represen t ai r qualit y expecte d unde r the curren t NAAQ S fo r C O an d unde r propose d C O standards , thes e dat a set s wer e adjuste d using a modifie d for mo f the EPArollbac k model
. 5. 1 TH E ROLLBAC K MODE L Eac haugmente d dat a se t i s a time serie s containing 876 0 hourl yvalues , i.e. ,

x x 

### , x 2 

### , ... , x fc 

### , ... , Xg 76Q 

### . W e assume d tha t y. , the differenc e betwee n eac hx . an d an assume d constan t background leve l x. , woul d increas e o r decreas e i n propor tio n t o the change s i n emission s dictate d b ya give n ai r qualit y standard , a s lon

g a s x . > x , . I f x f c 

### < x , , w e assume d x . woul d no t be affecte d b

ychange s i n emissions
. W e furthe r assume d tha t al l emission s woul d chang e i n proportio n t o the chang e i n emission s re quire d t o bring the mos t pollute d NT i n the stud yare a int o compliance
. Ai r qualit yi n eac hNT wa s characterize d b yai r qualit y indicator s (AQI's ) whic hvarie d according t o th e for mo f the ai r qualit ystandard
. W e assume d the mos t pollute d NT t o b e the on e wit hthe larges t AQ I wit hrespec t t o the standard being considered
. T o simulat e th e ai r qualit yexpecte d i n eac hNT unde r a standard , w e create d an adjuste d dat a se t

r , X f c , ... , Xg 7 6 0



### 5- 1P.6 3



### wher e
x t 

### ' = py t 

### + x b

### (5-1 )
an d p i s a rollbac k factor
. Consisten t wit hth e assumption s above , value s o f p wer e calculate d accordin g t o th e formula s

x- x , p = —- i f y . > 0 (5-2 )

x 

### max ' x 

### b fc



### an d p = 1 i f y t 

### < 0 , (5-3 ) wher e xi s th e highes t concentratio n permitte d b yth e standar d fo r th e state d averagin g time an d xi s th e correspondin g AQ I fo r th e mos t pollute d NT . Th e rollbac k mode l assume s rea sonabl e estimate s o f x. an d x . ar e available ; Section s 5. 2 an c ma xa 5. 3 describ e ho wthes e estimate s wer e developed
. 5. 2 AI R QUALIT YINDICATOR S Us e o f th e rollbac k mode l t o adjus t ai r qualit ydat a require s parameter s fo r characterizin g dat a whic har e relate d t o the for m o f eac hstandar d unde r consideration
. A t th e time o f th e C O pop ulatio n exposur e analyses , fou r type s o f parameter s wer e consid

ere d fo r propose d standards : th e dail ymaximu m1-hour valu e ex pecte d t o b e exceede d onc e pe r year , th e dail ymaximu m1-hour valu e expecte d t o b e exceede d fiv e times , th e dail ymaximu m8

- hou r running averag e expecte d t o b e exceede d once , an d th e dail y maximu m8-hour running averag e expecte d t o b e exceede d fiv e times
. Reasonabl e estimate s o f th e 1-hour parameter s ca n b e mad e b yfitting a cumulativ e distributio n [F(x) ] t o th e dail ymaximu m value s o f a n augmente d dat a se t an d the n calculatin g th e value s b , , c c 

### an

d b , _, c

c 

### suc htha t 1,36 5 5,36 5

F 

### < £ 

### v,n > " X

### "
_< 5 

### -" >

5- 2P.6 4



### wher e vi s th e numbe r o f permitte d exceedance s an d n i s th e numbe r o f possibl e dail ymaximumvalues
. Similarly , reasonabl e estimate s o f th e 8-hour parameter s ca n b e mad e b yfitting a cumulativ e distributio n t o th e dail ymaximu m8-hour running average s o f an augmente d dat a se t an d agai n calculatin g b , ,, , an d b r 

### ,,.,- . I n 1 , JO D D,jo b 

### statistica l theory , b , i s known a s th e characteristi c larges t valu e an

d b c 

### i s known a s th e characteristi c fift hlarges t 5, n value
. * Selectio n o f a n appropriat e cumulativ e distributio n t o fi t th e dat a i s importan t i n determinin g a reasonabl e characteristi c larges t value
. Two distribution s whic hofte n provid e clos e fit s t o ambien t ai r qualit ydat a ar e th e Weibul l an d the lognormal. 2 

### Th e Weibul l distributio n i s define d a s

F(x ) = 1 - ex

p [-(|) k 

### ] (5-5 ) wher e 6 i s th e scal e paramete r an d k i s th e shape-parameter
. Th e '• lognorma l distributio n i s define d a s



### 1 T w V2 TJ -c o wher e F(x ) =./=

- / ex p (-t 2 

### /2 ) d t

(5-6 )

w

## = m ; - ^ (5 

## . 7 ) 2 

### an d l n xi s distribute d normall ywit hmea n u an d varianc e a . FromEquation s 5- 4 an d 5-5 , th e characteristi c vt hlarges t valu e o f th e Weibul l distributio n ca n b e estimate d a s

V n - « (l n

### v" )1 A(5 

### " 8 ) 

### i f goo d estimate s o f 6 an d k ar e available
. Similarly , th e charac

teristi c vt hlarges t valu e o f th e lognorma l distributio n ca n b e estimate d a s

\,r

. " ex 

### P { 

### » + 

### ° z 

### v,n > (5 

### " 9 ) 

### i i f goo d estimate s o f u an d aar e available
. Th e valu e o f zv , n i s determine d fromth e norma l distributio n suc htha t the are a unde r the standar d norma l curv e from z t o °

° i s v/n
. Approxi

v , n mat e value s fo r z , 36 

### - an d z - 3g 5 

### ar e 2.777 4 an d 2.2058
. 5- 3P.6 5



### Th e result s o f fitting distribution s t o a larg e numbe r o f ambien t ai r qualit ydat a set s sugges t tha t the characteristi c vt h larges t valu e can b e bette r estimate d i f the uppe r tai l o f th e dat a i s emphasize d i n th e fit
. PEDC o Environmenta l ha s use d two method s t o fi t distribution s t o dat a censore d o n the lef t (i.e. , dat a fromwhic hlowvalue s hav e bee n excluded) : the metho d o f leas t square s an

d the metho d o f maximu m likelihood
. 5.2. 1 Fitting Distribution s b ythe Metho d o f Leas t Square s Th e leas t square s metho d require s tha t the equatio n defining the distributio n unde r consideratio n b e expresse d a s a linea r relationshi p o f the for my= a z + b
. Equation s 5- 5 an d 5- 6 can b e rewritte n i n linea r for m using the following identitie s wher e xi s the mt hranke d valu e i n ascending order , m— Distributio n y

_a

_z

_b lognorma l I n x „ a z „ _ . \i mm, n Weibul l l n x m

### i ln[ln ( "t 1 

### J ] l n 6 mKn+i- m Thes e identitie s followGumbel' s recommendation 3 

### tha t F ( x) = -m



### - r mn+ ± whe n fitting distribution s t o empirica l data
. Value s o f z fo r

^ *m, n th e lognorma l distributio n ar e determine d suc htha t the are a unde r the standard norma l curv e fro m-° ° t o z i s m/(n+l)
.

m , n Alinea r regressio n analysi s o f dat a transforme d b ythes e identitie s yield s a regressio n lin e wit han equatio n i n the for m o f y= a z + b
. Parameter s o f the corresponding distributio n can b e determine d fro

mthe value s o f a an d busing the following equations :

Weibul l distributio n 6 = ex p b(5-10 ) k = r (5-11 ) a Lognorma l distributio n '

. = b(5-12 )
a = a (5-13 ) 5- 4P.6 6



### 5.2. 2 Fittin g Distribution s b ythe Metho d o f Maximu mLikelihoo d I n an earlie r analysis' * o f populatio n exposur e t o NO- , the leas t square s metho d describe d i n Sectio n 5.2. 1 wa s the sol e metho d use d t o fi t distribution s t o ai r qualit ydata
. Th e metho d o f maximu

mlikelihoo d wa s no t use d becaus e n o procedur e wa s the n availabl e fo r applying i t t o the uppe r tai l o f a dat a set . During th e P Mexposur e analysis, 5 

### Loui s Wijnber g o f PEDC o Environmenta l (extending th e wor k o f Cohen 6/7 

### ) develope d the following maximum likelihoo d procedur e whic hca n fi t Weibul l an d lognorma l distribur

tion s t o an

yportio n o f the uppe r tai l o f a dat a set . Th e n value s i n an augmente d dat a se t ar e ranke d from smalles t t o larges t t o yiel d an ordere d serie s

X i x 

### m ' . - , __ 2 , .. m
_„ n 

### wher e xindicate s th e mt hranke d value
. W e ar e intereste d i n ob^

- m— taining maximu

mlikelihoo d estimate s (MLE's ) o f the parameter s 9
. an d 9

- o f a two-paramete r distributio n F(x;9,,9 2 

### ) fitting the n , - n-c+ 1 value s tha t equa l o r excee d x. Letting f(x;9.,9_ ) denot e th e densit yfunctio n o f a two-paramete r distributio n an d F( x) b e the valu e o f the cumulativ e distributio n a t x, c c
L = n ! (n-n f 

### ) ! n



## n m= c f(x m 

### ;9 1 

### ,9 2 

### ) F(x c 

### ) n-n . (5-14 )
i s th e likelihoo d functio n o f interest
. MLE' s o f 9 , an d 9
. ar e determine d b

ysimultaneousl ysolving the likelihoo d equation s 9 39
. •(lo g L ) = 0 (5-15 )

an d 

### gf-do g L ) = 0 , (5-16 )

I n the cas e o f the Weibul l distribution , the likelihoo d equation s ar e

5- 5

### an

d i i nx

_ . 5 ' nx

- * , 

### ^ +

### ^_ E 

### c ln( 

### ^ ' •= ; z( 

### 3r' ln( 

### ^ ' = 0 f m= c c f m= c c c P.6 7

(5-17 )

1 1 " X TT , n_n . £ + ±_y(—) + - ? n f m= c x c n f (ex ^ " 1 } = 0 , (5-18 )
wher e



# . = <-J ) . (5-19 ) Whe n fittin g th e lognorma l distribution , th e likelihoo d equation s are :
( y- . ) - (n-n f )a<j>(z c ) n <s *( z ) t c = 0 (5-20 )



### an d
2 —2 2 s z + ( y- v)

- C T 1 + (n-n f ) a <J > (z c ) '
n f «(z c ) = 0
wher e

- 1 n y= —_

_y, f m= c 

### n 2 1 " —2 s =

## H I_,£<**-* > • r m= c (5-21 )

/ (5-22 )

(5-23 )
"(5-24 )
(5-25 )

_ > denote s th e standar d norma l distribution , an d <i > i s th e standar d norma l densit yfunction
. Th e likelihoo d equation s wer e solve d b yusin g th e leas t squar e procedur e describe d i n Sectio n 5.2. 1 t o mak e initia l estimate s o f th e parameter s an d the n improvin g thes e estimate s usin g a n itera

tiv e proces s (th e Secan t method ) unti l a n optima l solutio n wa s reached
. 5- 6 Y m= I n m

. - y « 

### c m '

- u 

### aP.6 8



### Th e metho d o f maximu m likelihoo d ha s severa l advantage s ove r th e metho d o f leas t squares . I n particular , maximu mlikelihoo d estimate s (MLE's ) o f paramete r value s hav e minimu mvarianc e an

d theyasymptoticall yapproac ha norma l distributio n abou t the "true " paramete r valu e a s th e numbe r o f observation s increases
. I t i s als o possibl e t o construc t confidenc e interval s fo r MLE's . Param

ete r estimate s develope d b yth e leas t square s metho d hav e non e o f thes e properties
. Consequently , w e decide d t o us e maximu mlikeli

hoo d t o fi t Weibul l an d lognorma l distribution s t o th e C O data
. 5.2. 3 Determinin g Goodness-of-Fi t Followin g th e recommendation s o f Stephens 8 

### , an d Gree n an

d Hegazy, 9 

### w e investigate d th e us e o f th e Cramer-vo n Mise s ( W) an d 2 Anderson-Darlin g ( A) statistic s t o determin e goodnes s o f fit
. Thes e statistic s ar e define d b yth e expression s W 2 

### = l/12 n + i Z [F(x)-(2m-l)/2n] 2 

### (5-26 )

m= i an d
A 2 

### = - I Z (2m-l ) | l n F (x J + l n [1- F (xn+1 

### _. m 

### ) ] [ - n . (5-27 )

m= l Th e nul l hypothesi s (H Q 

### ) i s tha t th e sampl e come s froma populatio n wit hdistributio n functio n F(x)
. H Q 

### i s rejecte d a t a give n sig

nificanc e leve l i f a goodness-of-fi t statisti c exceed s a critica l valu e correspondin g t o tha t significanc e level
. I n ou r analysis , w e wer e intereste d i n whic ho f two distribu

tion s (Weibul l an

d lognormal ) bette r fit s a specifie d portio n o f 2 2 a sampl e dat a set . Unfortunately , th e Wan d Astatistic s o f a Weibul l distributio n fi t t o dat a canno t b e directl ycompare d wit h 2 2 th e Wan

d Ao f a lognorma l fi t t o th e same data
. Th e corres ponding significanc e level s ca n b e compared , bu t table s whic hlis t significanc e level s fo r censore d dat a o r fo r Weibul l distribution s 2 2 ar e no t currentl yavailable
. Consequently , Wan d Aca n onl yb e use d t o characteriz e th e fi t o f a lognorma l distributio n t o a n uncensore d dat a set . 5- 7P.6 9



### W e als o investigate d variou s statistic s base d o n th e absolut e difference s betwee n th e sampl e dat a se t an d th e fitte d distribution
. Th e mt habsolut e differenc e i s

£



### _ , = 

### l x



### - ~ x 

### „ l m= c , c+1 , ... , n (5-28 ) mmm r\ 

### wher e x_ , i s th e mt hranke d value , xi s th e estimat e o f x m—mm determine d b

yth e parameter s o f th e fitte d distribution , an d c i s th e rank o f th e smalles t dat a valu e use d i n the fit
. I n th e cas e o f a fitte d Weibul l distributio n wit hparameter s 5 an d k , 

## »_ - « t ln( 

## H^" 1 A


## - < 5 

## " 29 

## > Similarly ,

/ \ y \



### xm

### = ex p ( y+ a z m

### ) (5-30 ) mm, n fo r a fitte d lognorma l distributio n wit hparameter s yan d a. Th e statistic s considere d were :

ma xdif f = ma xe , (5-31 )

mea n dif f = ^ ^Z
_m 

### , (5-32 ) m= c 1 n

### 2 mea n diff** 2 = n

### _* +1 

### Z e , (5-33 ) m= c

A. 

### ma xreldif f = ma x[2 e /( x+ x)] , an d (5-34 ) mm m
mea n reldif f = -^^ r Z [2 c / (x m

### + x)]
. (5-35 ) m—c+ i

_mm m m= c Th e close r an

yon e o f thes e statistic s i s t o zero , th e bette r th e distributio n fit s th e data
. Th e brackete d termi n Equation s 5-3 4 an d 5-3 5 i s terme d th e relativ e difference ; i t i s th e absolut e differenc e divide d b yth e mea n o f th e observe d an d estimate d values
. 5- 3P.7 0



### W e initiall yevaluate d thes e statistic s a s alternative s t o 2 the R statisti c use d fo r characterizin g goodness-of-fi t fo r th e leas t square s method
. Tabl e 5- 1 summarize s the result s o f fitting Weibul l an

d lognorma l distribution s t o 197 8 C O dat a fromSt . Loui s sit e 261040001G01
. Fit s wer e mad e t o th e uppe r 50% , 20% , 5% , an d 1 % o f th e dat a b

yth e leas t square s method
. I n eac ho f th e fou r cases , al l si xstatistic s indicat e the same distributio n a s th e bes t fit
. Th e Weibul l distributio n provide s a bette r fi t i n the 5 % case ; th e lognorma l distributio n i s superio r i n th e othe r thre e cases . Accordin g t o mos t o f th e statistics , th e two bes t fit s ar e lognormal/50 % an

d Weibull/5%
. Th e estimate d characteristi c high , b, i s clos e t o th e recorde d maximu mvalu e o f 14. 9 ppmfo r bot h n fits
. Th e two wors t fit s ar e Weibull/50 % an d Weibull/20% ; i n bot h instances , bi s significantl ydifferen t from th e recorde d maximu m value
. W e ultimatel yselecte d mea n reldif f a s ou r goodness-of-fi t statistic
. Thi s statisti c i s particularl yrobus t (i.e. , no t sig

nificantl yaffecte d b youtliers ) an

d weight s eac hvalu e use d i n the fi t equally
. Ma xdiff , mea n diff**2 , an d ma xreldif f can b e significantl yaffecte d b youtliers
. Ma xdiff , mea n diff , an d mea n diff** 2 weigh t highe r value s mor e heavil ytha n lowe r values
. Weibul l an

d lognorma l distribution s wer e firs t fi t t o th e uppe r 5 0 percen t o f th e dail ymaximu m value s i n eac haugmente d dat a se t (Table s 5- 2 an d 5-3)
. Evaluatio n o f th e result s indi

cate d tha t th e close r fitting distributio n di d no t alway s yiel d a clos e fi t t o th e fiv e larges t values
. Repeating th e analysi s using th e uppe r 2 0 percen t o f th e dail ymaximu m value s in^ac h augmente d dat a se t produce d simila r reldif f statistic s an d superio r fit s t o th e five larges t value s (Table s 5- 4 an d 5-5)
. Consequently , w e decide d t o us e th e uppe r 2 0 percen t o f th e augmente d dat a se t fo r al l fits
. Th e genera l procedur e use d fo r determinin g characteristi c larges t an d fift hlarges t value s i s describe d below
. (1 ) Maximu

mdail y1-hour an

d 8-hour running averag e value s i n eac haugmente d dat a se t wer e ranke d fromlowes t t o highest
. 5- 9TABL E 5-1 . RESULT S O F FITTIN GWEIBUL L ANDLOGNORMAL DISTRIBUTION S TO197 8 CODATA

(ppm ) FROM

ST . LOUIS , MO aB

YLEAS T SQUARE S METHOD .

I Statisti c

R 2 Ma xdif f Mea n dif f Mea n diff** 2 Ma xreldif f Mea n reldif f 6 k

_A

.

0
S t b n Uppe r

Weibul l 0.97 9 4.60 8 0.13 8 0.09 1 0.3 8 0.029

. 3.11 5 1.82 9

-

- 10.40 1 •50

% lognorma l 0.99 8 1.57 4 0.04 3 0.00 9 0.1 2 0.00 8

-

- 0.98 2 0.46 0 14.54 0 Dat a fi tby

Uppe r20 % Weibul l 0.98 0 2.81 8 0.15 0 0.05 5 0.2 2 0.02 6 2.69 2 1.43 2

-

- 12.56 5 lognorma l

0.99 5 0.95 5 0.07 4 0.01 0 0.0 7 0.01 3

-

- 0.93 9 0.48 6 15.36 6 distributio n

UP F Weibul l 0.99 7 1.02 6 0.06 3 0.00 9 0.0 7 0.00 8 2.08 9 1.12 3

- • '

- 14.89 0 >e r5

% lognorma l 0.99 5 •1.41 5 0.08 4 0.02 0 0.0 9 0.01 0

-

- 0.87 5 0.52 0 16.31 5 Up

p Weibul l 0.98 7 1.09 0 0.10 9 0.03 4 0.0 8 0.01 0 2.16 0 1.14 7

-

- 14.78 3 >e r1 % lognorma l 0.99 0 0.94 6 0.09 6 0.02 6 0.0 7 0.00 9

-

- 1.05 5 0.45 3 15.22 6

Recorde dmaximu

m value : 14. 9 ppm .P.7 2

TABL E 5-2 . RESULT S O F FITTIN GWEIBUL L ANDLOGNORMA L DISTRIBUTION S B

Y MAXIMU M LIKELIHOO DPROCEDUR E T OUPPE R5 0 PERCEN T O F DAILYMAXIMU

M l-HOU RCODAT A

Stud yare a Chicag o

Lo s Angele s

Philadelphi a

St . Loui s I r •*••__________=
_



### N T C R C C C I S R S C SI C R C C C I S R S C S I C R C C C I S R S C SI C R C C C I S R S C S I Weibul l

Mea n reldif f 0.034 7 0.024 1 0.019 7 0.033 1 0.040 6 0.017 9 0.042 5 0.032 1 0.031 5 0.028 2 0.030 5 0.031 5 0.089 7 0.089 7 0.093 2 0.085 0 0.085 0 0.050 5 0.051 9 0.018 5 0.033 1 0.121 4 0.043 3 0.033 1 Characteristi c

values , pp

m
b l,36 5 10. 0 23. 5 15. 7 11. 6 11. 7 10. 0 14. 6 29. 0 26. 3 20. 0 21. 8 26. 3 16. 6 16. 6 

### 8. 9 11. 5 11. 5 12. 2 

### 8. 8 12. 7 17. 6 16. 4 13. 0 17. 6

. •,—,_..• , , ,_.... „ b 5,36 5



### 8. 4 20. 0 13. 5 

### 9. 2 9. 5 8. 3 12. 1 23. 1 21. 2 16. 3 17. 2 21. 2 13. 4 13. 4 

### 7. 4 8. 6 8. 6 10. 2 

### 7. 3 11. 4 14. 7 12. 9 11. 0 14. 7 Loqnorma l

Mea n reldif f 0.018 6 0.012 1 0.011 2 0.015 3 0.015 3 0.025 4 0.053 5 0.035 1 0.048 5 0.038 8 0.043 5 0.048 5 0.059 8 0.059 8 0.067 8 0.077 7 0.077 7 0.047 2 0.033 8 0.011 8 0.014 7 0.075 8 0.021 4 0.014 7 Characteristi c

values , pp

m
b l,36 5 11. 2 26. 4 17. 4 13. 5 13. 1 11. 6 17. 0 35. 0 31. 6 23. 6 26. 9 31. 6 17. 3 17. 3 

### 9. 0 13. 3 13. 3 13. 9 10. 0 13. 4 19. 9 17. 4 14. 3 19. 9 b 5,36 5 

### 8. 7 20. 9 14. 1 

### 9. 6 9. 8 8. 7 12. 8 24. 9 22. 8 17. 4 18. 7 22. 8 13. 0 13. 0 

### 7. 1 8. 9 8. 9 10. 7 

### 7. 6 11. 5 15. 2 12. 6 11. 3 15. 2

5-1 1P.7 3



### TABL E 5-3 . RESULT S OF FITTIN GWEIBUL LAN

DLOGNORMA

LDISTRIBUTION S B

Y MAXIMU M LIKELIHOODPROCEDURE TOUPPER5 0 PERCENT OF DAILYMAXIMU

M 8-HOU RRUNNIN GAVERAGE C

ODAT A

Stud yarea Chicago

Lo s Angele s

Philadelphi a

St . Loui s 

### N

T C R C C CI S R S C SI C R C C CI S R S C S I C R C C C I S R S C S I C R C C CI S R S C SI W

Mea n reldif f 0.038 3 0.011 0 0.021 1 0.058 8 0.070 2 0.060 9
0.020 8 0.029 0 0.025 1 0.027 8 0.023 1 0.025 1
0.095 4 0.095 4 0.068 4 0.050 9 0.050 9 0.035 9
0.051 2 0.008 2 0.057 0 0.090 1 0.039 4 0.057 0 eibul l

Characteristi c values , pp

m A b l,36 5 

### 6. 2 14. 6 10. 4 

### 7. 8 8. 0 6. 8 9. 2 21. 5 19. 5 15. 1 16. 3 19. 5
11. 4 11. 4 

### 6. 4 6. 8 6. 8 9. 1 5. 3 10. 4 12. 0 10. 1 

### 9. 9 12. 0 As

b 5,36 5 

### 5. 4 12. 7 

### 9. 1 6. 2 6. 4 5. 5 7. 8 16. 7 15. 8 12. 3 12. 9 15. 8 

### 9. 3 9. 3 5. 3 5. 2 5. 2 7. 6 4. 5 9. 5 10. 1 

### 8. 4 8. 5 10. 1 

### Lo

q

Mea n reldif f 0.017 8 0.015 6 0.011 2 0.024 7 0.036 2 0.031 0
0.039 3 0.051 8 0.038 3 0.021 9 0.024 8 0.038 3
0.052 1 0.052 1 0.034 0 0.031 0 0.031 0 0.017 2
0.027 1 0.013 8 0.031 4 0.051 9 0.021 8 0.031 4 norma l

Characteristi c values , pp

m A* b l,36 5 

### 6. 8 16. 3 11. 4 

### 8. 8 8. 7 7. 5
10. 8 27. 0 23. 0 17. 8 19. 8 23. 0
11. 9 11. 9 

### 6. 6 8. 1 8. 1 10. 2 

### 5. 8 11. 2 13. 1 10. 5 10. 9 13. 1 A,

b 5,36 5 

### 5. 5 13. 3 

### 9. 4 6. 3 6. 4 5. 6 8. 3 18. 4 16. 9 13. 1 14. 0 16. 9 

### 9. 0 9. 0 5. 1 5. 5 5. 5 7. 8 4. 6 9. 8 10. 2 

### 8. 2 8. 8 10. 2



### 5-1 2TABL E 5-4 . RESULT S O F FITTIN GWEIBUL L AN

DLOGNORMA

L DISTRIBUTION S B

Y MAXIMU M LIKELIHOODPROCEDURE TOUPPER2 0 PERCENT OF DAILYMAXIMU

M 1-HOU RC ODAT A

Stud yare a Chicag o

Lo s Angele s

Philadelphi a

St . Loui s 

### N

T C R C C C I S R S C S I C R C C C I S R S C SI C R C C C I S R S C SI C R C C C I S R S C SI Mea n reldif f 0.016 5 0.011 6 0.013 9 0.031 7 0.038 6 0.023 1
0.036 0 0.028 9 0.025 2 0.027 8 0.028 2 0.025 2
0.078 2 0.078 2 0.084 3 0.068 8 /0.068 8 0.043 9
0.023 4 0.024 9 0.035 3 0.080 2 0.022 5 0.035 3 Weibul l

Characteristi c values , pp

m As b l,36 5 10. 7 24. 9 16. 3 12. 5 12. 9 10. 2
14. 1 29. 3 - 25. 0 19. 6 21. 0 25. 0
19. 0 19. 0 

### 9. 9 12. 2 12. 2 12. 8 

### 9. 8 13. 2 19. 0 21. 1 14. 5 19. 0 As.

b 5,36 5 

### 8. 7 20. 7 13. 9 

### 9. 6 10. 1 

### 8. 3
11. 8 23. 3 20. 6 16. 1 16. 8 20. 6
14. 3 14. 3 

### 7. 8 8. 9 8. 9 10. 5 

### 7. 8 11. 6 15. 3 14. 6 11. 7 15. 3 Loqnorma l

Mea n reldif f 0.019 6 0.016 4 0.012 6 0.021 0 0.025 0 0.017 7
0.043 2 0.028 8 0.023 0 0.030 0 0.031 6 0.023 0
0.060 7 0.060 7 0.067 2 0.071 8 0.071 8 0.039 0
0.032 7 0.016 9 0.026 3 0.060 8 0.018 9 0.026 3 Characteristi c

values , pp

m
b l,36 5 11. 4 26. 4 17. 2 13. 3 13. 6 10. 8
14. 9 31. 4 26. 2 20. 8 22. 3 26. 2
19. 2 19. 2 

### 9. 7 13. 2 13. 2 13. 4
10. 6 13. 4 20. 1 22. 8 15. 4 20. 1 A

b 5,36 5 

### 8. 8 20. 9 13. 9 

### 9. 6 10. 0 

### 8. 4
12.0 ' 23. 5 20. 6 16. 2 16. 9 20. 6
13. 8 13. 8 

### 7. 4

. 8. 9 

### 8. 9 10. 5 

### 7. 9 11. 5 15. 3 14. 6 11. 8 15. 3

5-1 3I t o rt -
r - o c -_l

. t o

C O C O C O C O O C O H n s M n J O

o o o o o o C D O C D O O C D c o r o o o oo»- » 4 * r o r o r o r o o o M
. MSIOtO I

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t—> >—> C D V O V O O V O 4 * v o o r o v o t n o o

O O C D C D O O C D O C D O O O r o r o as

r o o r o 4 * i1 c n 4 * - o v o OIOOIOOI M

»—».- •i—•»-..- ' •t>H M
. oa i MUIOIMM H

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O O O O o o o o o o o o t o 4=» 4 * c n -* o ~ o O t o o o r o t n t n •- » ^- J ^ J C O ~« J ^ J

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o o o o o o o o o o o o o o r o r o o o r o i- > v o 4 > t n v o v o ^ J M MUMm o

•—•!— •i—»•— » r o v o o » t n v o o o o 4 * c n c n 4 ^ •- •o o

>— ••— •i— •i— •i— • c n c o r o t n c n ^ j o o •- * t n o o t-

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r o i— * »- •r o r o C D o o c n o r- » v o o o o c n o o e n c o

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c r> c n C O c n t n <

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r o 3 * o >

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__

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_ zm c
_ c oo _P » J > CZ

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^ 1P.7 6

(2 ) Th e uppe r 2 0 percen t o f th e dail ymaximu mvalue s wer e fi t b yWeibul l an d lognorma l distribution s usin g th e maximu m

likelihoo d metho d describe d above
. (3 ) Th e reldif f statistic s o f th e tw o fit s wer e compare d an d th e parameter s o f th e bette r fittin g distributio n (i.e. , th e on e wit hth e smalle r reldif f value ) wer e use d t o determin e th e characteristi c larges t an d fift h larges t values
. Tabl e 5- 6 list s characteristi c value s develope d usin g thi s pro cedure
. Appendi xB discusse s th e relationshi p betwee n thes e value s an d th e expecte d concentratio n (EC ) value s develope d by EP Afo r th e fou r studyareas .
5. 3 BACKGROUN D CONCENTRATION S NE Mrequire s a city-specifi c averag e backgroun d leve l i n orde r t o calculat e th e rollbac k facto r applie d t o ambien t pollu

tan t concentration s i n eac hstud yarea . Thi s backgroun d valu e shoul d represen t th e averag e hourl yconcentratio n o f a give n pollutan t bein g transporte d int o th e urba n area , a valu e unaffecte d b yan ycontro l strategie s impose d upo n th e urba n area . . Th e moni

torin g site s selecte d t o determin e C O backgroun d shoul d ideall y b e locate d sufficientl yupwin d fro mth e urba n are a i n a nonlow

lyin g location , withi n n o les s tha n fiv e degree s o f alignmen t wit hextende d straigh t highwa ysegments . Also , eac hsit e shoul d b e i n a n are a wit hsufficien t ventilatio n s o tha t ai r i s no t likel yt o stagnate . Site s establishe d t o monito r regiona l con centration s ar e preferre d t o thos e establishe d t o monito r loca l concentrations
. PEDC o identifie d monitorin g site s whic hsatisfie d ' thes e criteri a throug ha n evaluatio n o f (1 ) regiona l offic e an d loca l agenc yrecommendations , (2 ) loca l win d profiles , an d (3 ) loca l lan d use . I t shoul d b e note d tha t th e C O backgroun d con centratio n bein g transporte d int o a n urbanize d are a ma yi n fac t b e highe r o n occasio n tha n som e o f th e reporte d value s withi n th e area . Thi s phenomeno n i s du e t o dispersio n an d dilutio n an d i s dependen t upo n th e sitin g objective s an d spatia l distributio n o f C O monitor s acros s th e stud yarea . !
5-1 5P.7 7



### TABL E 5-6
. AI RQUALITYINDICATOR S FO RCO DAT A

Stud y are a Chicag o

Lo s Angele s

Philadelphi a

St . Loui s 

### N

T C R C C C I S R S C S I C R C C C I S R S C S I C R C C C I S R S C S I C R C C C I S R S C S I Dail y

maximu m 1-hour avera c Char . larqes t 10. 7 24. 9 17. 2 13. 3 13. 6 10. 8
14. 1 31. 4 26. 2 19. 6 21. 0 26. 2
19. 2 19. 2 

### 9. 7 12. 2 12. 2 13. 4 

### 9. 8 13. 4 20. 1 22. 8 15. 4 20. 1 e s (ppm )

Char . 5thlarqes t 

### 8. 7 20. 7 13. 9 

### 9. 6 10. 0 

### 8. 4
11. 8 23. 5 20. 6 16. 1 16. 8 20. 6
13. 8 13. 8 

### 7. 4 8. 9 8. 9 10. 5 

### 7. 8 11. 5 15. 3 14. 6 11. 8 15. 3 Dail y maximu m 8-hour runningaveraqe s (ppm ) Char . larqes t 

### 7. 2 15. 6 10. 8 

### 9. 5 10. 0 

### 8. 3 8. 8 20. 1 20. 3 15. 5 16. 6 20. 3
14. 3 14. 3 

### 7. 2 7. 9 7. 9 10. 4 

### 6. 1 10. 7 14. 7 12. 5 11. 5 14. 7 Char .

5thlarqes t 

### 5. 7 12. 9 

### 9. 3 6. 6 6. 9 6. 0 7. 6 16. 1 15. 7 12. 5 13. 1 15. 7 

### 9. 9 9. 9 5. 3 5. 5 5. 5 7. 9 4. 8 9. 5 10. 9 

### 9. 0 9. 0 10. 9



### 5-1 6P.7 8



### Contac t wit hthe loca l EPARegiona l Offic e resulte d i n iden

tificatio n o f th e Chicag o Height s sit e (SAROA D code : 141240001G01 ) a s an appropriat e background sit e fo r the Chicag o stud yarea . Th e sit e i s locate d a t a highschoo l sufficientl yfa r fro marea s wit h hightraffi c concentrations
. Arura l sit e nea r the urban are a o f St . Loui s (SAROA D code : 264300006G01 ) wa s selecte d a s the indicato r fo r background C O level s fo r tha t stud yarea . C O level s measure d a t thi s sit e ar e simila r t o thos e reporte d b ya sit e predominantl yupwind o f the metropolita n area . A s a resul t o f diurna l wind cycling cause d b yland-se a breezes , eac hstatio n i n the Sout hCoas t Ai r Basi n i s occasionall y upwin d an d downwind o f the cente r citycore . Consequently , pre dominan t wind directio n wa s no t considere d a vali d criterio n fo r identifying a background sit e fo r the Lo s Angele s area . Arural

agricultura l sit e fairl yremove d fro murban influenc e (SAROA D code : 055160001101 ) wa s selected
. Th e Philadelphi a loca l agenc yrecommende d a sit e i n Northwes t Philadelphi a (SAROA D code : 397140014H01 ) a s the mos t appropriat e indicato r fo r averag e background concentrations
. Th e averag e hourl yconcentratio n wa s calculate d fo r a recen t yea r a t eac hsit e t o estimat e annua l averag e backgroun d fo r the corresponding stud

yarea . Thes e value s ar e liste d i n Tabl e 5-7
.
TABL E 5-7
. ESTIMATE

D ANNUA L AVERAG E BACKGROUN

D LEVEL S

Studyare a Chicag o Lo s Angele s Philadelphi a St . Loui s Yea r 197 9 197 7 197 8 197 8 C O backgroundconcentratio n

mq/m 3 1. 5 2. 0 1. 1 2. 6 ppm 1

1.3 1 1.7 5 0.9 6 2.2 7 

### Converte d at ST P usin g 1 pp m= 114 5 ug/m

3



### 5-1 7P.7 9



### 5. 4 REFERENCE S 1
. E . J . Gumbel , Statistic s o f Extremes , Columbi a Universit y Press , Ne wYork , 1958 , p . 82
. 2
. T . Johnson , " Acompariso n o f th e two-paramete r Weibul l an d lognorma l distribution s fitte d t o ambien t ozon e data, " Proc . o f Specialt yConferenc e o n Qualit yAssuranc e i n Ai r Pollutio n Measurement , Ai r Pollutio n Contro l Association , 1979
. 3
. Op . cit. , Gumbel , p . 34
. 4
. T . Johnso n an d R . Paul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Nitroge n Dioxide , prepare d b yPEDCo'Envir

onmental , Inc. , fo r Strategie s an d Ai r Standard s Division , Offic e o f Ai r Qualit yPlannin g an d Standards , U.S . Environ

menta l Protectio n Agency , Researc hTriangl e Park , N.C . 27711 , Augus t 1981
. 5
. Te d Johnso n an d RoyPaul , Th e NAAQ S Exposur e Mode l (NEM ) an d It s Applicatio n t o Particulat e Matter , prepare d b yPEDC o Environmental , Inc. , fo r Strategie s an d Ai r Standard s Division , Offic e o f Ai r Qualit yPlannin g an d Standards , U.S . Environ

menta l Protectio n Agency , Researc hTriangl e Park , N . C . 27711 , Augus t 1981
. 6
. A . C . Cohen , Jr. , "Simplifie d estimator s fo r th e norma l dis

tributio n whe n sample s ar e singl ycensore d o r truncated, " Technometrics , Vol
. 1 , No . 3 , Augus t 1959
. 7
. A . C . Cohen , Jr. , "Maximu mlikelihoo d estimatio n i n th e Weibul l distributio n base d o n complet e an d o n censore d samples, " Technometrics , Vol
. 7 , No . 4 , Novembe r 1965
. 8
. M . A . Stephens , "EDF statistic s fo r goodnes s o f fi t an d some "comparisons, " Journa l o f th e America n Statistica l Association , Vol
. 69 , No . 347 , Septembe r 1974
. 9
. J . R . Gree n an d Y . A . S . Hegazy , "Powerfu l modified-ED F goodness-of-fit-tests, " Journa l o f the America n Statistica l Association , Vol
. 71 , No . 353 , Marc h1976
.

5-1 8P.8 0



### SECTIO N6 SIMULATIO

NO F CARBONMONOXID E LEVEL S I NTH E MICROENVIRONMENT

Abasi c assumptio n o f NE Mi s tha t eac hmembe r o f the stud y are a populatio n ca n b e assigne d during eac hhou r o f the da yt o on e o f five microenvironments : indoor s (wor k o r school) , indoor s (hom e o r other) , insid e a transportatio n vehicle , outdoor s nea r a roadway , o r othe r outdoo r locations
. I n applying NE Mt o CO , w e initiall yassume d tha t ai r qualit yi n eac hmicroenvironmen t (x

_. ) o f a give n neighborhoo d typ e coul d b e estimate d b ythe expressio n
x

_. = a m

### + bx . ' (6-1 ) m , t m , t m t 

### wher e a . i s the pollutan t concentratio n generate d b ya particu

la r sourc e i n the microenvironment , x" i s the monitor-derive d ai r qualit yestimate d fo r the neighborhoo d type , an d bi s a multi

plicativ e factor
. Consequently , estimate s o f a^, an d b(denoted

„ /

s ^ m , t m 

### a

_. an d b) appropriat e fo r C O wer e neede d fo r eac hmicroenviron

m , t m ment . W e assume d tha t a . wil l varywit hmicroenvironment , C O m , t source , an

d time o f day ; an

d tha t bwil l varyonl ywit hmicro

environment
. Equatio n 6- 1 wa s late r revise d t o accoun t fo r ob

serve d lag s betwee n indoo r an d outdoo r CO . PEDC o reviewe d 7 5 report s wit hkeyword s o r abstract s sug gesting theycontaine d informatio n usefu l i n estimating a . an d b—jointl yreferre d t o a s microenvironmen t factor s (MF's)
. The mJ 

### revie windicate d tha t 2 6 o f thes e report s containe d dat a appli

cabl e t o ou r analysis
. Thes e report s ar e categorize d b ymicro

environmen t i n Tabl e 6-1
. I n the following discussion , result s o f thes e studie s ar e use d t o estimat e MF' s and , i n some cases , t o develop alternative s t o Equatio n 6-1
. 6- 1P.8 1



### TABL E 6-1 . STUDIE S CONSIDEREDI N DEVELOPIN

G C OMICROENVIRONMENT FACTOR S
Microenvironmen t Indoors : wor ko r schoo l

•*!•••* '

Indoors : home o r othe r

Transportatio nvehicl e

Roadsid e Study . Harke 1 Penkal a andOliveira 2 Moschandreas , e t al. 3 Yocum , e t al . * Genera l Electric 5 Derham , e t al. 6 Godin , e t al. 7 Thompson , e t al. 8

Yocum , e t al. 1 * Moschandreas , e t al. 9 Cote , e t al. 1 1 Bridg e an

dCorn 1 2 Sterlin gandKobayashi 1 3 Penkal a andOliveira 2 Repac e an

dLowrey 1 6 Spengler , e t al. 1 7 Sterlin gandSterling 1 8 Spengler , e t al. 2 0 Godin , e t al. 7 Ellio t andRowe 2 1 Thompson , e t al. 8

Ot t an dWil l its 2 2 Ziskind , e t al. 2 3 Colwil l andHickman 21 * Wallace 2 5 Cortese 2 8 Bric e andRoesler 2 7 Peterse nandSabersky 2 8 Harke , e t al. 1
Wilso nandSchweiss 2 9 Wilso nandSchweiss 3 0 Jabara , e t al. 3 1



### 6- 2P.8 2



### 6. 1 WORK-SCHOO L MICROENVIRONMENT Smoking ha s bee n identifie d b ysevera l studie s a s affectin g C O level s i n enclose d workin g areas . Th e contributio n o f smoking doe s no t appea r t o b e verysignificant , however
. C O wa s monitore d fo r 1 8 day s b

yHarke 1 

### i n tw o offic e buildings , on e air-conditioned , th e othe r not . Hark e foun d tha t n o significan t increas e i n C O occurre d afte r employee s starte d t o smoke
. I n anothe r experiment , Hark e found tha t C O di d no t excee d 1 0 ppmi n a n unventilate d offic e room(3 0 m) whe n a n occupan t smoke d a t a rat e o f 2 cigar

ette s pe r hour
. Background an d outdoo r C O level s ar e no t mentione d i n eithe r study
. Usin g tes t chambe r data , Penkal a an d Oliveira 2 

### estimat e tha t C O i n a 40 0 f t roomoccupie d b yon e smoke r consumin g 3 1.2 5 cigarette s pe r hou r wil l averag e 18. 6 mg/ mpe r hou r a t 0 ai r change s pe r hour
. A t recommende d ventilatio n rate s (2. 1 t o 7. 5 ai r change s pe r hour) , C O shoul d averag e 1. 2 t o 3. 6 mg/ m. Moschandreas , e t al., 3 

### studie d C O i n two offic e building s i n Boston . Theyhypothesize d tha t indoo r source s o f C O ar e largel y dampe d b

yth e diffusiv e effec t o f th e ai r handlin g systems . Elevate d C O concentration s relate d t o smoking wer e no t observed
. Yocum , e t al., 1 

### * sugges t tha t daytim e indoor-outdoo r ratio s abov e 1.0 0 observe d i n two offic e building s i n Hartford , CT , ar e th e resul t o f smoking b yoccupant s an

d visitor s bu t d o no t provid e usefu l dat a fo r estimating a . . m , t Th e repor t b

yPenkal a an

d Oliveir a i s th e mos t usefu l o f thes e fou r studies
. Th e followin g excerp t describe s thei r mode l an d discusse s thei r assumptions
.

Assum e a smoke r and a nonsmoke r occupyth e same offic e wit ha tota l volum e o f 40 0 f t . Ventilatio n rate s i n force d 3 ventilation s system s ar e usuall ybetwee n 7 an d 2 5 f t o f fres hai r pe r minut e pe r roomoccupant . Thes e ventilatio n rate s ar e equivalen t t o 2.1-7. 5 ai r change s pe r hour , an d ca n b e attaine d b

ynorma l leakag e around window s an d doors
. Atypica l smoke r consume s on e pac k o f 2 0 cigarette s pe r day(1 6 wakin g hours)
. Eac hcigarett e i s smoke d i n
6- 3_____ _



### abou t 1 0 minutes , creatin g a highconcentratio n o f C O an d SP Mi n th e room , an d the n th e ventilatio n systeman d othe r remova l mechanism s (as measure d i n thi s study ) lowe r thos e concentration s somewha t durin g a res t perio d (4 0 minutes ) befor e the nex t cigarett e i s lit
. Th e concentration s ca n b e time-average d b yconsiderin g th e roomt o b e i n a cycl e consistin g o f a rapi d concentratio n ris e an d a slowe r ex ponentia l decay
. Th e decayrat e depend s upo n th e ventilatio n rat e an d th e measure d ga s remova l rate . Bot hca n b e repre sente d b

yth e equivalen t ai r change s pe r hour , an d converte d t o a time constant , x , representin g th e minute s pe r equiva

len t ai r change
. The n C 2 = C-J-1/T ] 

### C

- i s concentratio n a t time t C , i s a n initia l concentratio n xi s th e numbe r o f minute s pe r equivalen t air,chang e t i s th e averag e tim e o f on e cigarett e smok e plu s following res t perio d Not e tha t (C , - C- ) i s th e concentratio n adde d b ysmoking a cigarette
. Acycl e end s wit hth e rooma t concentratio n C

- an d i s raise d t o a ne wconcentratio n C , throughsmoking a cigarette
. Combinin g th e equation s allow s computin g C , an d C

- fo r an

y equivalen t ai r chang e rate . Th e averag e concentratio n C , ca n b e foun

d b yintegratio n ove r a smoking perio d plu s res t period. 2 

### Th e 40 0 f t roomvolum e i s base d o n a ASHRA E recommendatio n o f 20 0 f t pe r offic e buildin g occupant . Repac e an d Lowrey 1 5 

### estimat e tha t one-thir d o f adult s smoke
. Theyals o stat e tha t the recommende d occupanc ydensit yfo r general.offic e spac e i s 1 0 person s pe r 100 0 squar e feet
. Assumin g a n 8-foo t ceiling , w e ca n estimat e tha t ther e i s on e smoke r pe r 240 0 f t . Sinc e Penkal a an d Oliveir a assume ther e i s on e smoke r pe r 40 0 f t , thei r esti

mate s ca n b e multiplie d b y400/240 0 t o yiel d the C O level s expecte d 6- 4P.8 4



### i nanoffic ewit hon esmoker pe r 2400f t
. Bot hset s o f

estimate s ar eliste di nTabl e6-2

.

TABL E '6-2
. ESTIMATE S OFC O CONCENTRATION S I N A N OFFIC E WIT H SMOKER S

a i rchanges/hou r 

### 0 1 2. 1 7. 5 mea n C O (mq/ m ) 40 0 ft 0 

### pe

r smoke r 240 0 ft J 

### pe

r smoke r 3.1 0 1.0 3 0.6 0 0.2 0
Base d o n thes e results , reasonabl e bound s fo r a . durin g workin g 3 o . hour s woul d b e 0.2 0 mg/ m (0.1 7 ppm ) an

d 0. 6 mg/m J 

### (0.5 2 ppm) ; a

3 reasonabl e bes t estimat e fo r a . woul d b e 0.3 5 mg/ m (0.3 0 ppm) , th e geometri c mea n o f th e bounds
. Th e relationshi p b„ , = (x m- a «.)/ x•« . 

### mm , t m , t a , t (6-2 ) where
. x , . represent s ambien t C O level s reporte d b ya fixe d monitor , a , t ca n b e use d t o estimat e b
. i f goo d dat a fo r determinin g x. , x. *. m? 

### m , t a , t an d a . ar e available
. Tw o studies—Moschandreas , e t al., 3 

### an d m , t data
. Yocum , e t al. , . . an d x _ m , t a , t Non e o f thes e studie s lis t value s Genera l Electric 5 

### —provid e x provid e x,/ x. values ,

m , t a , t directl yrelatin g t o a . . Genera l Electri c measure d C O insid e an d outsid e o f tw o building s i n Ne wYork
. On e buildin g wa s an ai r right s buildin g abov e th e Tran s Manhatta n Expressway ; th e othe r wa s a mor e conventiona l highris e structur e o n on e sid e o f a stree t canyo n i n midtown Manhattan
. Th e following excerp t i s take n fromthei r conclusions
.

Concentration s indoor s a t th e buildin g bas e varywit h outdoo r concentrations
. Indoo r concentration s la g change s i n outdoo r C O levels
. I t i s suspecte d tha t thi s time delay i s a variabl e tha t i s a functio n o f bot hwind condition s a s see n a t th e buildin g an d the directio n o f chang e i n outdoo r concentrations
. 6- 5P.8 5



### Averag e concentration s insid e an d outsid e th e building s reduc e exponentiall ywit hheigh t abov e ground level
. Th e rat e o f chang e wit hheigh t i s essentiall yconstan t outdoor s fo r bot hheatin g an d non-heatin g seasons . However , indoor s th e decayi n averag e concentration s wit hheigh t i s greate r durin g th e non-heatin g seaso n tha n durin g th e heatin g season . Thi s variatio n i s th e resul t o f change s i n th e roo f wind angl e fromth e non-heatin g t o th e heatin g season . Indoo r concentration s normall yar e lowe r tha n outdoo r concentration s a t al l height s abov e th e roadwaywhe n outdoo r concentration s ar e high
. Conversely , indoo r concentration s ar e highe r tha n outdoo r concentration s whe n outdoo r concen tration s ar e low. 5 

### Becaus e th e air-right s buildin g i s atypica l o f urba n wor k places , dat a fo r th e stree t canyo n buildin g shoul d receiv e primary attention
. Thi s buildin g wa s no t air-conditioned ; ventilation , especiall ydurin g th e summe r months , wa s achieve d b yopenin g windows
. Tabl e 6- 3 list s averag e weekdayC O concentration s a t 9 fee t abov e stree t level , thir d floor , fift hfloor , 11t hfloor , an d 19t hfloor
.
TABL E 6-3
. WEEKDA

YC O MEASUREMENT

S A T STREE T CANYO NSITE 5



### seaso n heatin g

non-heatin

g locatio

n 9 feet 3r d floo r 5t hfloo r 11t hfloo r 19t hfloo r 9 feet 3r d floo r 5t hfloo r 11t hfloo r 19t hfloor
. averag e C outsid e 11. 2 

### 9. 9 7. 7 6. 6 5. 4 11. 2 10. 3 

### 8. 1 4. 8 4. 2 0 (ppm )

insid e


### 9. 5 7. 8 6. 9 6. 8

• 

### 8. 2 7. 1 4. 7 3. 8

6- 6P.8 6

Insid e C Oconcentration s ar e generall y th e sam e a s outsid e C O concentration s a t th e sam e buildin gheight . C Odecrease s wit h heigh t s o tha t th e rati o o f insid e C Ot o C O9 fee t abov e street leve l varie s fro m 0.8 5 a t th e thir dfloo r t o 0.6 1 a t th e 19t h floo r durin gth e heatin gseason . I nth e non-heatin gseason , th e rati o range s fro m 0.7 3 a t th e thir dfloo r t o 0.3 4 a t th e 19t h floor . Th e contributio no f indoo r source s t o indoo r C Oi s unknow n bu t i s probabl y

smal l i nproportio nt o th e ambien t C Olevels . Moschandreas , e t al., 3 measure dC Oinsid e an doutsid e o f tw o offic e building s i nBoston . Thei r result s ar e liste di nTabl e 6-4 .
TABL E 6-4 . C

OCONCENTRATIONS (ppm ) AT TW OOFFIC E SITE S RECORDED B YMOSCHANDREAS , ET AL. 3

buildin g
ne w old meanindoor

3.1 8 2.1 6 ma

xindoor 11.3 5 14.3 6 mea n outdoor/indoor 1.0 2 0.8 8

Not e the y

reporte doutdoor/indoo r ratio s rathe r tha nindoor/outdoo r ratios . Figur e 3 i nMoschandreas , e t al. , show s indoo r C Otrack in goutdoo r C Oa t th e ne w building . Tabl e 6- 5 list s indoor-outdoo r ratio s fo r tw o air-conditione d offic e building s i nHartford , CT , determine db y Yocum , e t al. 1 *
TABLE 6-5 . IND00R-0UTD00 RC ORATIO S DETERMINEDFO RTW OOFFICE BUILDING S B

YYOCUM , ET AL. * Buildin g 10 0 CP

25 0 CP Seaso

n Summer Fal l Winte r Suitme r Fal l Winte r Daytim

e rati o 1.3 1 1.3 2 1.1 3 1.0 5 0.9 6 0.7 6 Nightim e rati o 1.0 0 1.2 5 1.2 1 1.0 2 1.0 4 ' 0.9 6

CP : Constitutio

nPlaz a 

### 6- 7P.8 7



### Insid e C O wa s measure d o n th e second floo r a t 10 0 C P an d the thir d floo r a t 25 0 CP . Th e author s sugges t tha t the start-u p o f buildin g ventilatio n durin g rus hhou r i s th e primarycaus e o f summe r an

d fal l daytim e ratio s greate r tha n 1.0 0 a t 10 0 CP . The yfurthe r sugges t smoking ma yhav e elevate d ratio s i n th e winter
. Derham , e t al., 6 

### monitore d C O insid e an d outsid e a buildin g i n Lo s Angeles
. The yfoun d tha t indoo r level s o f C O reflec t directl yth e level s outdoor s bu t wit ha phas e la g tha t ca n b e explaine d b

ymean s o f a simpl e analytica l mode l whic haccount s fo r ventilation ' rate s bu t neglect s an ychemica l reactions
. The y d o no t provid e simultaneou s indoor/outdoo r reading s an d smoking i s no t discusse d a s a possibl e C O source . Godin , e t al. , measure d C O level s insid e an d outsid e a down

tow n offic e i n Toront o wit hth e window s closed
. The ysummariz e thei r finding s a s follows :

A t 15 0 Colleg e St. , abou t a mil e fromth e cit ycenter , outdoo r value s wer e 2. 7 + 1. 8 ppm , whil e th e correspondin g value s fo r th e firs t an d thir d floor s were , respectively , 2. 2 + 1. 3 ppm

an d 2. 8 + 1. 5 ppm . Value s i n talle r downtown building s apparentl ydepende d o n the leve l o f ai r intak e fo r th e floo r i n question ; a t th e Toront o Dominio n Centre , th e sidewal k concentratio n wa s 6. 4 ppm , figure s fo r th e firs t and thir d floor s wer e 4. 6 and 4. 0 ppm , respectively , bu t th e 54t hfloo r (witha muc hhighe r ai r intake ) ha s a leve l o f onl y2. 4 ppm. 7 

### Godin , e t al. , conclud e tha t indoo r C O concentration s mirro r outdoo r concentrations , wit ha la g o f on e t o two hours
. Thes e studie s sugges t tha t a reasonabl e mode l fo r hourl y averag e C O i n th e workplac e i s

*_,(t ) = a m



### . + 

### T^^..(t ) + 

### x-(t-1) ]
. (6-3 ) mm , t
_c c Th e indoo r C O a t time t i s equa l t o the indoo r generate d C O a t time t plu s btime s th e averag e o f the outdoo r C O a t time t an d 6- 8P.8 8

a t tim e t-1
. Thi s mode l assume s tha t buildin g ventilatio n dampen s variation s i n indoo r C O an d cause s a sligh t la g betwee n indoo r an d outdoo r concentrations
. Areasonabl e "best " estimat e o f bfo r m building s o f 3 storie s o r les s i s 0.85 , th e rati o o f thir d floo r C O t o outsid e groun d floo r C O i n th e Genera l Electri c study
. A reasonabl e rang e fo r bi s 0.60'(unairconditione d highrise ) t o 1.0 5 (ventilatio n syste mo f 25 0 CP)
. Th e microenvironmen t unde r consideratio n include s school s a s wel l a s wor k places
. Onl yon e study—Thompson , e t al. 8 —measure d indoo r an d outdoo r C O level s a t a school
. Accurac yo f thei r C O analyzer , +1. 0 ppm , prevent s a critica l compariso n o f th e lo w value s whic hwer e measured
. Sinc e NE Mtreat s indoor s wor k an d indoor s schoo l a s th e sam e microenvironment , w e use d th e mode l alread ydevelope d fo r indoor s a t wor k fo r th e combine d work-schoo l microenvironment
. 6. 2 HOME-OTHE R MICROENVIRONMEN T Th e valu e o f bfo r home s ca n b e estimate d b ycomparin g indoo r an d outdoo r C O level s o f home s wit hn o indoo r C O sources . Yocum , e t al., 1 * measure d indoo r an d outdoo r C O a t tw o residence s i n Hartford , CT . Neithe r hom e ha d a ga s stov e o r habitua l smoker
. Averag e indoor/outdoo r ratio s ar e liste d i n Tabl e 6-6
.

TABL E 6-6
. AVERAG

E IND00R/0UTD00 R C

O RATIO S RECORDE D B

Y YOCUM , ET AL. " Residenc e Blinn.St
.

Carol ! St . Seaso n Summe r Fal l Winte r
Summer Fal l Winte r Tim

e o f da y 

### Da y Night 

### Da y Night 

### Da y Night 

### Da y Night 

### Da y Night 

### Da y Night Rati o

1.0 2 1.0 7 1.0 3 1.0 8 1.0 7 1.0 8 1.0 4 1.0 2 1.0 3 1.0 8 0.9 6 1.0 8



### 6- 9P.8 9



### Not e tha t al l ratio s ar e clos e t o unity
. Yocum , e t al. , d o no t provid e dat a usefu l ir i determinin g i f indoo r C O lag s outdoo r CO . Figur e 4 fromMoschandreas , e t al., 9 

### suggest s a la g o f on e hou r i n a conventiona l residenc e i n Baltimore
. Th e followin g i s a n excerp t fromthei r study
. Indoo r concentratio n peak s o f C O ten d t o la g behind outdoo r C O peaks
. Du e t o th e C O emissions , thi s behavio r ma yb e shortene d i n house s wit hindoo r sources . Th e observe d larg e fluctuation s o f th e hourl yC O concentration s displaya loca l structur e withou t a genera l pattern . How

ever , examinatio n o f th e C O dat a bas e fromsevera l weekday s lead s t o identificatio n o f a typica l patter n wit hrespec t t o 3-haverages . Typically , th e time period s 0800-100 0 and 1900-210 0 exhibi t th e highes t observe d C O levels
. Thes e 3-hindoo r peak s correspond t o outdoo r peak s cause d b y automobil e traffi c durin g the typica l urba n rus hhour s (0600-080 0 an

d 1700-1900)
. Th e associatio n o f rush-hou r traffi c an

d typica l indoo r highleve l period s reflec t the time la g monitore d earlier
. Figur e 4 illustrate s the indoo r an

d outdoo r variatio n o f C O concentration s fo r a typica l day , i n a dwelling wit hindoo r C O sources . Th e indoo r pea k a t hour s 140 0 t o 160 0 i s no t a typicall yobserve d elevatio n o f th e indoo r concentrations. 9 

### Thes e result s sugges t tha t Equatio n 6- 3 i s applicabl e t o th e home microenvironmen t a s wel l a s th e wor k microenvironment
. Base d solel yo n th e result s o f Yocu me t al. , a preliminaryestimat e o f bwoul d b e 1.00
. However , analysi s b yFeagans 1 0 

### indicate s tha t 1.0 0 i s probabl yto o high
. Feagan s suggest s 0.8 5 a s a mor e appropriat e bes t estimat e o f band 0.7 0 t o 1.1 0 a s a reasonabl e

* % mA 

### rang e fo r b
. Appropriat e value s o f a , fo r differen t indoo r

mm , t source s ar e develope d below
. C O source s i n th e home includ e smoking , ga s stoves , ga s furnaces , coa l furnaces , an d attache d garages . C O fromthes e source s combine d wit hC O fro moutsid e hav e resulte d i n indoo r level s exceeding the C O NAAQS . 6-1 0P.9 0



### Thre e studies—Cote , e t al., 1 1 

### Moschandreas , e t al., 9 

### an d Bridg e an

d Corn 12 

### —mentio n smoking a s a n indoo r C O sourc e i n th e home
. Cote , e t al. , monitore d indoo r an d outdoo r C O i n fou r home s i n Hartford , CT . Unfortunately , th e home s wit hsmoker s als o had ga s appliance s s o tha t th e contributio n o f smoking t o indoo r C O canno t b e determine d separately
. Moschandreas , e t al. , monitore d C O level s i n 1 5 homes
. Person s living i n thes e house s wer e polle d a s t o smoking habits
. Unfortunately , the repor t b y Moschandreas , e t al. , provide s onl ya fe wsampl e day s o f C O dat a an d n o smoking data
. Bridg e an d Cor n measure d C O a t two experi

menta l "parties. " Sterling an d Kobayash i provid e th e following summaryo f thi s study
. I n on e 512 0 f t roomcontainin g 5 0 people , 2 5 peopl e con sume d 5 0 cigarette s an d seve n cigar s i n 1* 5 hours
. Wit ha roomai r exchang e rat e o f seve n time s pe r hour , C O average d 7 ppmdurin g th e cours e o f th e party . During the secon d experimen t i n a 375 0 f t roomcontainin g 7 3 people , 3 6 smoker s consume d 6 3 cigarette s an d 1 0 cigar s i n 1*

5 hour s an d th e averag e C O conten t wa s 9 ppm. x3 

### Thes e result s sugges t tha t 7 ppm i s a wors t cas e a valu e fo r smoking tha t woul d no t b e exceede d i n th e typica l home excep t durin g occasiona l socia l functions
. Th e thre e studie s describe d abov e ar e no t usefu l i n deter

minin g a typica l a fo r smoking
. However , wit hsuitabl e assump tion s w e ca n us e th e mode l develope d b yPenkal a an

d Oliveir a t o estimat e a i f w e hav e goo d estimate s o f ai r exchang e rates ,

i n§ u 

### Tabl e 6- 7 list s ai r exchang e rate s determine d b yMoschandreas , e t al. , fo r residence s o f variou s kinds
.

6-1 1P.9 1

TABLE 6-7
. AI R EXCHANG E RATE S DETERMINED B Y MOSCHANDREAS , ET AL. 9
locatio n Washingto

n Baltimor e
Denve r Chicago Pittsbur g residenc e type experimenta l conventiona l experimenta l conventiona l conventiona l conventiona l experimenta l mobil e 1 mobil e 2 low-ris e 1 low-ris e 2 low-ris e 3 high-ris e 1 high-ris e 2 high-ris e 3 exchanqes/ h

0. 5 - 1. 0 0. 2 - 0. 8 0. 5 - 1. 2 0. 6 - 2. 0 0. 8 - 1. 0 0. 6 - 1. 0 0. 1 - 0. 3 0. 4 - 1. 0 0. 3 - 1. 1 0. 3 - 0. 8 0. 7 - 1. 4 1. 6 - 1. 7 0. 9 - 1. 4 0. 9 - 1. 4 0. 9 - 1. 2

Ai r exchang e rate s rang e fro m0. 1 t o 2.0
. Th e mea n o f th e mid

point s o f th e 1 5 range s liste d i n Tabl e 6- 7 i s 0.9
. Th e mea n o f th e midpoint s o f th e particula r residenc e type s ar e liste d below
. residenc e type experimenta l conventiona l mobil e low-ris e high-ris e exchanqes/ h 0. 6 0. 9 0. 7 1. 1 1. 1
Thes e result s sugges t a typica l ventilatio n rat e fo r a nonexperi

menta l hom e o f on e exchang e pe r hour
. Penkal a an d Oliveir a estimat e tha t on e smoke r pe r 40 0 f t i n a n enclose d spac e wil l ad d 6. 2 mg/ m (5. 4 ppm ) t o indoo r C O i f ther e i s on e ai r exchang e pe r hour
. Ac

cordin g t o U.S . Censu s data, 11 * th e averag e numbe r o f room s i n a livin g uni t i s 5.1
. Assumin g th e typica l fiv e roo mhous e ha s a floo r are a o f 130 0 squar e fee t an d a ceilin g 8 fee t high , w e ca n estimat e tha t th e typica l livin g uni t ha s a volum e o f 10,40 0 f t . 6-1 2P.9 2



### Housing dat a indicat e tha t the averag e living uni t ha s 2. 1 adults. 1 5 

### Repac e an

d Lowrey 1 5 

### estimat e tha t on e thir d o f adult s smoke
. Sinc e some teenager s smoke , th e averag e living uni t ha s a t leas t 3 3 0. 7 smoker s pe r 10,40 0 f t o r 0.02 7 smoker s pe r 40 0 f t . Smoker

generate d C O woul d b e a t leas t (0.027)(5. 4 ppm ) = 0.1 5 ppm . A hous e wit h10,40 0 f t an d two smoker s woul d hav e a smoker-generate d C O concentratio n o f 0.4 2 ppm . Thes e level s ar e negligible
. I n fact , th e numbe r o f smoker s mus t b e increase d t o five pe r 10,40 0 f t fo r th e smoker-generate d C O concentratio n t o excee d 1.0 0 ppm . I n a sampl e o f 6 9 homes , Spengler , e t al., 1 7 

### found 3 2 percen t had on e smoke r an

d 1 3 percen t ha d tw o o r mor e smokers
. From thes e dat a w e ca n estimat e th e averag e hous e wit hsmoker s ha s 3 3 abou t 1. 3 smoker s pe r 10,40 0 f t o r 0.0 5 smoke r pe r 40 0 f t . Smoker-generate d C O concentratio n i n suc ha hous e woul d b e abou t 0. 3 ppm . Consequently , w e use d 0. 3 ppma s ou r bes t estimat e o f A 

### a_ , . fo r smoking household s from 7 a.m . t o 9 a.m . and from 5 p.m . m, t * c 

### t o 1 1 p.m . Asmalle r a . , 0. 2 ppm , wa s considere d appropriat e il l / C A. 

### from9 a.m . t o 5 p.m . W e assume d a__ , . = 0 from1 1 p.m . t o 7 a.m . m, t I n th e C O exposur e analysi s w e ar e particularl yintereste d i n kitche n an

d living roomC O level s generate d b yga s stoves . Pea k home C O exposur e i s expecte d t o occu r i n the kitche n durin g an d immediatel yafte r mea l preparation
. W e assume tha t typica l home C O exposur e i s bette r represente d b yC O level s i n th e living room . Dat a usefu l i n estimatin g a fo r ga s stove s ar e provide d b ysevera l studie s performe d b yResearc hCorporatio n o f Ne w England
. Yocum , e t al., 1 

### * measure d C O i n two house s wit hga s stove s an

d ga s furnaces
. Theyfoun d tha t "the heating systemhad no measurabl e effec t o n th e indoo r o r outdoo r C O levels ; however , the ga s fire d stove s i n eac hhous e ha d a significan t influenc e o n indoo r C O levels. " Figur e 4 i n Yocum , e t al. , show s kitche n level s i n hous e G- 1 exceedin g outsid e level s b y3 ppm durin g mea l prepara ^ tion ; living roomlevel s exceede d outsid e level s b yabou t 1. 5 ppm . I n hous e G-2 , kitche n and famil yroomlevel s durin g mea l prepara tio n exceede d outdoo r level s b y3. 0 t o 4. 5 ppman d 1. 0 t o 1. 5 ppm , 6-1 3P.9 3



### respectively
. I n a late r stud yb yCote , e t al., 1 1 

### indoo r an d out

doo r C O level s wer e measure d a t fou r home s i n Hartford , CT . 2 Hous e 1 i s a 2,00 0 f t split-leve l wit hwell-ventilate d kitche n occupie d b

ya marrie d coupl e an d two children
. Th e wif e smoke s a pac k a day
. Yocum , e t al. , foun d tha t a n attache d garag e mad e a significan t contributio n t o indoo r C O a t thi s house
. Hous e 2 i s

2 a 150 0 f t two-storyhom e wit hwell-ventilate d kitchen
. A singl e adul t live s ther e wh o seldom use s th e stove . Hous e 3 i s a 2 1,00 0 f t apartmen t wit ha small , unventilate d kitchen
. Anon smoking coupl e an

d thei r 2 childre n liv e there
. Hous e 4 als o ha s 2 tw o adult s and tw o children
. I t i s a 150 0 f t ranch-styl e hous e wit hkitche n ope n t o othe r area s o f th e house
. Tabl e 6- 8 list s th e seasona l mean s o f dail yaverag e C O concentration s measure d i n variou s area s o f the fou r houses
. Averag e kitche n an d living roomC O value s i n hous e 1 excee d outsid e C O b y101 0 yg/ m(0.8 8 ppm ) an d 59 0 yg/ m(0.5 2 ppm) , respectively
. Th e contributio n o f th e attache d garag e i s difficul t t o quantify
. Dat a from hous e 2 ar e probabl yatypica l becaus e o f th e infrequen t stov e use . House s 3 an d 4 ar e no t a s wel l ventilate d a s hous e 1 an d ma yb e mor e appropriat e fo r determinin g typica l a values
. Averag e kitche n 3 C O exceed s averag e outsid e C O b y304 0 yg/ m(2.6 6 ppm ) an d b y 3 3 412 0 yg/ m(3.6 0 ppm ) i n hous e 3 an d b y659 0 yg/ m(5.7 6 ppm ) i n hous e 4
. Averag e living room C O exceed s averag e outsid e C O b y 3 3 98 0 yg/ m(0.8 6 ppm ) an d 169 0 yg/ m(1.4 8 ppm ) i n hous e 3 an d b y 578 0 yg/ m(5.0 5 ppm ) i n hous e 4
. Close r examinatio n o f 2-hour C O value s include d i n th e repor t reveal s tha t th e difference

betwee n insid e (kitche n an d living room ) an

d outsid e C O level s i s usuall ygreates t from 160 0 t o 180 0 ( 4 p.m . t o 6 p.m. ) an d i s usuall ysmalles t from40 0 t o 60 0 ( 4 a.m . t o 6 a.m.)
. Typica l mealtim e C O level s seemt o occu r betwee n th e hour s 120 0 an d 140 0 (noo n an d 2 p.m.)
. Tabl e 6- 9 list s averag e difference s betwee n insid e an

d outsid e C O level s durin g thes e 2-hour period s fo r house s 1 , 3 , an

d 4
.

6-1 4P.9 4

TABL E 6-8
. INDOOR/OUTDOOR CO DAT ARECORDE D B

YCOTE , E T AL. 1 1

Hous e 

### 1

2 3

4 Seaso n Spring-summe r Fall-winte r Fall-winte r Spring-summe r Spring-summe r Fall-winte r Fall-winte r Fall-winte r Mea nda i

Stov e
419 0 479 0 300 0 431 0 782 0 713 0 907 0 l yaveraq e Kitche n 449 0 352 0 421 0

- 642 0 662 0 900 0 C O concentration ,

Livin g Room 407 0 323 0
308 0 321 0 507 0
819 0 Bedroo m

417 0 383 0 290 0 268 0 550 0

. - yg/m 3

Outsid e 348 0 167 0 231 0 294 0 223 0 338 0 250 0 241 0 Avg .

stov e usag e (min ) 19 8 10 6 ? 

### 4 3 3 7 6 6 11 5 

### 20 1

Sterling an

d Sterling 1 8 

### studie d th e rat e o f C O buildu p an d dissipatio n i n kitchens , dinin g rooms , an d living room s o f nin e home s i n Burnaby , Britis hColumbia
. Kitche n level s o f C O i n hous e 1 increase d from 6 ppm t o 3 6 ppmi n 3 0 minutes , dependin g o n th e numbe r o f burner s on .
Burners o

n 1 2 3 4 C

O increase , pp mpe r minute 0. 2 0.6 3 0.7 3 1.2 0
Rate s o f increas e fo r th e othe r eigh t home s varie d from0. 7 t o 3. 3 (numbe r o f burner s o n wa s no t specified)
. Th e averag e rat e o f C O increas e fo r the nin e home s wa s abou t 2 ppm . Operatin g a stov e a t thi s rat e fo r 3 0 minute s woul d yiel d an hourl yaverag e o f 3 0 ppm

i f C O decaye d immediately
. Sterling an d Sterling foun d tha t C O decaye d veryslowl yi n th e tes t home s an d tha t i t diffuse d rapidl ythroughou t th e houses
. An increas e i n kitche n C O o f 3 0 ppmdurin g mea l preparatio n i s probabl yatypica l sinc e i t i s base d o n th e us e o f thre e t o four burner s continuall yfo r 3 0 minutes
. Non e o f th e studie s b y Researc hCorporatio n o f Ne wEngland sugges t meal-tim e C O level s 6-1 5TABL E 6-9 . AVERAG E DIFFERENCE S BETWEEN KITCHEN , LIVINGROOM , ANDOUTSID E COCONCENTRATION S

Hous e 

### 1

3

4 Seaso n Spring/summe r
Fall/winte r
Spring/summe r
Fall/winte r

Fa11/winte r Time o f

day 4- 6 12-1 4 16-1 8 4- 6 12-1 4 16-1 8 4- 6 12-1 4 16-1 8 4- 6 12-1 4 16-1 8 4- 6 12-1 4 16-18

- Differenc e i nC O

Kitchen-outsid e 62 4 (ll) a 110 9 (12 ) 174 2 (12 ) 194 1 (11 ) 224 7 (12 ) 338 0 (14 )

-

328 4 (21 ) 337 2 (23 ) 362 2 (22 ) 270 4 (9 ) 712 3 (7 ) 12,42 4 (9 ) 3

concentration , yq/ m Livinqroom-outsid e 38 5 (11 ) 74 3 (12 ) 83 2 (13 ) 123 6 (5 ) 115 4 (6 ) 210 5 (8 ) 84 4 (16 ) 106 2 (16 ) 91 5 (16 ) 175 7 (9)
. 218 9 (12 ) 104 5 (10 ) 225 6 (9 ) 617 7 (7 ) 11,32 8 (9 )

Number s i

nparenthese s indicat e numbe r o f day s wit hdata .

6-1 6

### thi s high
. I f th e dat a provide d b yYocu man d Cot e ar e assume d t o b e mor e typical , a reasonabl e mode l fo r kitche n a .i n ga s

~ m , t stov e home s woul d b e a__ , . = 4. 0 ppmdurin g meal-tim e hours , an d

_m , t 

### a . = 2. 5 ppm

othe r times
. Reasonabl e living roomestimate s m , t A^ 

### woul d b e a

_, = 2. 0 ppmdurin g meal-tim e hour s an d a . = 1. 0 ppm m, t cc3 

### m, t rr 

### othe r times
. Meal-tim e hour s woul d b e define d a s th e 2-hour period s 60 0 t o 800 , 110 0 t o 1300 , an d 170 0 t o 1900
. Althoug hth e home-othe r microenvironmen t include s nonresi

dentia l location s suc ha s shopping malls , a singl e se t o f a ,
_an d m , v bvalue s i s use d fo r the combine d microenvironment
. Spengler 1 9 

### m cite s wor k b

yChapi n whic hsuggest s tha t 9 2 percen t o f people' s time characterize d a s spen t i n home-othe r microenvironment s i s spen t i n th e home
. Consequently , usin g th e indoo r hom e value s fo r the combine d microenvironmen t shoul d no t significantl ybia s exposur e estimates
. W e ca n assume tha t a cohor t i s a t hom e wheneve r it s activit ypatter n place s them i n the home-othe r micro-

- environmen t durin g a meal-tim e hour
. Using th e ga s stov e esti

mate s fo r a_ , . i n thes e situation s i s reasonable
. A t othe r time s

m , t o f the day , home-othe r coul d indicat e visit s t o a library , courthouse , shopping center , sport s arena , o r doctor' s office
. Th e principa l C O sourc e i n thes e enclose d area s i s probabl y' cigarett e smoke , althoughSpengler , e t al., 2 0 

### hav e foun d tha t ic e cleanin g machine s a t hocke yrink s ca n produc e one-hou r C O level s exceedin g 3 5 ppm . Godin , e t al., 7 

### reporte d tha t C O i n a theate r foye r wher e smoking wa s permitte d exceede d C O i n th e auditoriu m b y2 ppm . Ellio t an d Rowe 2 0 

### foun

d a n averag e C O concentratio n o f 2 5 ppmi n a sport s aren a (no t ai r conditioned ) wher e smoking wa s permitted
. C O level s o f 9 ppmwer e recorde d i n tw o othe r arena s wit hposte d "N

o Smoking " signs
. Averag e C O durin g period s o f nonactivit ywa s 3 ppmi n al l thre e arenas . Thompson , e t al., 8 

### recorde d averag e daytim e C O level s i n a hospital , YMCApool , departmen t store , an d shopping mal l (se e Tabl e 6-10)
.

6-1 7P.9 7



### TABL E 6-10 . AVERAG E COLEVEL S I N VARIOU S STRUCTURES 3


### Kin do f structur e communit y

hospita l YMCA poo l departmen t stor e shoppingmal l CO , pp m Ou t 2. 1 0. 5 6. 4 2. 7 I

n 1. 7 1. 0 3. 3 3. 1

Thompson , e t al. , stat e tha t th e inaccurac yo f thei r analyzer , +1. 0 ppm , prevente d critica l compariso n o f mos t o f th e rathe r lowvalue s obtaine d wit hth e possibl e exceptio n o f th e C O level s measure d a t th e departmen t store . Thompson , e t al. , sugges t th e following explanatio n fo r th e relativel ylo windoor/outdoo r ratio
. Becaus e aut o exhaus t emission s nea r th e buildin g woul d b e minima l a t night , a mas s o f ai r wit ha minima l leve l o f C O woul d accumulat e durin g th e night
. I f daytim e ventilatio n rate s ar e low , th e insid e ai r woul d fai l t o com e t o equilibriu mwit hout

sid e CO . Non e o f thes e studie s provid e dependabl e dat a o n typica l C O level s i n th e "other " microenvironment
. Consequently , w e use d th e factor s determine d fo r "home " a s th e factor s fo r th e combine d home-othe r microenvironment
. 6. 3 TRANSPORTATIONVEHICL E MICROENVIRONMENT Th e mos t commonl yuse d transportatio n vehicl e i n th e fou r stud yarea s i s th e automobile
. Th e principa l interna l source s o f C O i n automobile s are'probabl ycigarett e smoking an d leak yexhausts
. I n th e absenc e o f thes e sources , availabl e dat a indicat e tha t averag e interio r C O i s equa l t o o r les s tha n averag e exterio r CO , althoughexterio r C O show s greate r fluctuations
. Ot t an d Willits 2 2 

### conclude d tha t th e averag e valu e o f the interio r C O concentra

tio n i s approximatel yequa l t o th e averag e valu e o f th e exterio r C O concentratio n i f th e averagin g time , T , wa s muc hgreate r than the time constan t T . Theyestimat e x = 4. 5 minute s fo r a tes t
6-1 8P.9 8



### vehicl e movin g o n residentia l sid e street s a t 2 0 mp hwit hwindow s closed
. Sinc e T decrease s a s spee d increase s o r window s ar e open , w e ca n assum e T>> xfo r mos t movin g vehicles
. Ziskind , e t al., 2 3 

### studie d buses , cabs , an d polic e car s i n Denve r an

d Boston . Theyfoun d tha t interio r concentration s "ris e an d fal l wit hexterio r concentrations , ye t ar e almos t alway s lower. " The yhypothesiz e tha t th e relativel ysmal l differenc e betwee n interio r an d exterio r level s provide s to o smal l a drivin g forc e fo r diffusio n o f C O int o th e vehicle
. Furthermore , ther e i s insufficien t time fo r th e tw o concentration s t o equilibriate , sinc e th e externa l sourc e i s constantl ychangin g a s long a s th e vehicl e keep s moving
. Ziskind , e t al. , found tha t al l vehicle s i n thei r stud

yhavin g interio r concentration s i n exces s o f exter

io r concentration s ha d bot hexhaus t systemleak s an d pathway s throught o th e passenge r area . Sinc e mos t o f the vehicle s whic h wer e monitore d continuousl yi n thei r stud ywer e selecte d becaus e o f highinterio r C O levels , thei r result s canno t b e applie d t o th e genera l vehicl e population
. Colwil l an

d Hickman 2 

### * measure d interio r an d exterio r C O level s o f 1 1 ne wcar s drive n around a 3 5 k mrout e i n London
. The yrepor t inside/outsid e ratio s o f 0.3 5 t o 0.7 5 wit ha mea n rati o o f 0.55
. Althoug htheydi d no t relat e insid e C O level s t o stationarymonito r readings , Colwil l an d Hickma n stat e tha t occupant s o f vehicle s movin g i n heav ytraffi c ar e expose d t o C O • level s highe r tha n thos e recorde d a t curbside
. Severa l studie s provid e dat a whic hrelat e interio r C O level s t o fixe d monitorin g dat a directly
. Whe n Ziskind , e t al. , compare d persona l sample r dat a wit hfixe d sit e data , theyfoun d tha t tota l exposure s exceede d fixe d sit e concentration s b yan averag e o f 13. 9 ppm . An averag e rati o wa s no t determined
. Ziskind , e t al. , als o lis t averag e interio r C O a s measure d b y continuou s monitor s i n 9 vehicle s ( 8 buse s an d 1 cab ) an

d th e averag e C O level s a t correspondin g fixe d sites
. Interior/fixe d sit e ratio s varyfrom1. 0 t o abov e 7. 0 wit ha media n o f 2.7
. Ziskind , e t al. , ar e uncertai n ho wmuc ho f the differenc e betwee n 6-1 9P.9 9



### interio r an

d fixe d sit e C O "wa s du e t o vehicl e self-contaminatio n an d ho wmuc hwa s du e t o th e inheren t lac k o f representativenes s o f th e fixe d sit e monitorin g statio n readings. " However , the y mak e th e following inconsisten t statemen t i n thei r sectio n list

ing overal l stud

yconclusions : Typicall yth e C O leve l measure d insid e o r immediatel yout

sid e th e vehicl e significantl yexceede d th e valu e recorde d b yth e neares t fixe d sit e monitorin g station
. Vehicl e self-contaminatio n doe s no t appea r t o be
. th e caus e o f thi s disparity
. Rather , i t i s postulate d tha t th e proximit yo f th e vehicl e t o th e emissio n source s account s fo r th e dif

ferenc e betwee n vehicl e an d fixe d sit e monito r concentra

tions
. 2 3 

### Wallace 2 5 

### measure d C O level s i n car s an d buse s o n 3 7 run s (2 7 b ybus , 1 0 b

ycar ) around Washington , D.C . . Mea n bu s C O wa s 11. 7 ppm , excludin g on e outlier ; mea n ca r C O wa s 13. 8 ppm . Thes e value s ar e thre e t o fou r time s highe r tha n mea n C O measure d simu

taneousl ya t a stationarymonito r a t 42 7 Ne wJerse yAvenue , N.W . However , Wallac e foun d n o significan t relationshi p betwee n ambien t concentration s an

d interio r vehicula r concentrations
. Hi s result s sugges t tha t factor s associate d wit hparticula r vehicles—powe r source , design , an d maintenance—ma yeffec t interio r C O level s mor e tha n exterio r C O levels
. Adoctora l thesi s b yCortese 2 6 

### provide s mor e definitiv e re sults
. I n thi s study , populatio n exposur e t o C O wa s measure d b yequippin g volunteer s living an d workin g i n the metropolita n Bosto n are a wit hportabl e C O monitors
. Th e monitore d cohor t consiste d o f 6 6 nonsmokin g volunteer s wh o carrie d a portabl e monito r fo r 3 t o 5 day s durin g commutin g an d workin g activities
. Participants * commutin g mod e an d route , residentia l and occupa tiona l location , exposur e t o cigarett e smoke , an d dail yactivitie s wer e documented
. Volunteer s wer e chose n from population s withou t significan t occupationa l exposure s t o C O s o tha t measure d expos ure s resulte d fromambien t ai r contamination
. Populatio n
6-2 0P. 1



### exposur e data , a s measure d faypersona l monitoring , wer e compare d t o C O concentration s measure d a t 6 fixe d locatio n monitorin g station s operate d b yth e Massachusett s Burea u o f Ai r Qualit y Control
. Tw o o f th e fixe d locatio n monitorin g station s ar e locate d i n downtown Boston . Thes e urba n station s approac h Federa l siting criteri a fo r monitorin g maximu m1-hour exposur e t o CO . Th e othe r fou r station s ar e locate d i n suburba n areas . Thes e station s approac hfedera l siting criteri a fo r monitorin g 8-hour averag e C O exposur e bu t ar e no t locate d clos e enought o heavil ytravele d roadway s t o monito r maximu m1-hour exposure . Th e following conclusion s wer e drawn b yCortese . o Measurement s a t 6 fixe d location s i n metropolita n Bosto n underestimate d mea n 1-hour C O exposur e durin g commuting b

ya facto r o f 1. 8 t o 2.0
. o Measurement s a t th e tw o urba n monitorin g stations , whos e characteristic s approac hFedera l criteri a fo r monitorin g maximu

m1-hour exposures , underestimate d th e mea n 1-hour C O exposur e durin g commutin g b ya facto r o f 1.4
. Becaus e Bosto n pedestrian s ca n b e close r t o automobil e traffi c tha n th e tw o urba n stations , measurement s fromth e station s woul d als o underestimat e pedestria n exposur e t o CO . o Measurement s a t th e fou r suburba n monitorin g station s underestimate d mea n 1-hour C O exposur e durin g commutin g b ya facto r o f 2.1
. Thi s resul t i s significan t becaus e a larg e portio n o f th e averag e commutin g tri p i n thi s stud yoccurre d i n suburba n areas . o Analysi s o f th e highes t 5-7 % o f th e persona l exposur e an d fixe d locatio n measurements , whic har e o f greates t publi c healt himportance , indicate d tha t fixe d locatio n measurement s wer e bette r estimate s o f the highe r commut

ing exposure s than o f th e entir e rang e o f commutin g exposures . Nevertheless , th e mea n 1-hour persona l

6-2 1P. 2



### exposur e concentratio n wa s 1. 6 time s the mea n concen tratio n a t al l fixe d station s an d 1. 3 time s th e mea n concentratio n a t urba n stations
. 1 0 t o 15 % o f th e differenc e betwee n commutin g exposure s an d th e concentration s measure d b yfixe d locatio n moni

tor s wa s attribute d t o a n observe d reductio n i n C O concentration s wit hincrease d sampling heigh t betwee n persona l monitor s a t o r nea r breathin g zon e (5. 5 feet ) an d fixe d locatio n monitor s a t a heigh t o f 1 5 feet
. Th e remainde r o f th e differenc e wa s attribute d to--

- commuter s bein g close r t o C O emissio n source s tha n fixe d locatio n monitors
. No consisten t relationshi p wa s observe d betwee n persona l exposur e durin g commutin g an d fixe d locatio n measure ment s ove r th e entir e rang e o f value s encountered
. Thi s resul t mad e i t impossibl e t o develo p a predictiv e relationshi p betwee n persona l exposur e an d fixe d loca

tio n measurements' . Mod e o f trave l (automobile , mas s transit , spli t mode , i.e. , par t auto , par t transit ) an d rout e o f trave l wer e th e significan t factor s influencing persona l exposur e t o C O durin g commuting
. Cigarett e smok e i s the onl y othe r significan t sourc e o f C O t o whic ha commute r may b e exposed
. Tota l trave l b

yautomobil e resulte d i n a mea n C O expo sur e nearl ytwic e tha t o f rai l mas s transi t commutin g an d approximatel y1. 6 time s tha t o f spli t mod e commuting
. Automobil e commutin g o n 4-lane , heavil ytravele d arteria l road s resulte d i n a mea n C O exposur e approxi

matel y1. 4 time s th e mea n exposur e durin g automobil e commuting o n othe r type s o f roads
. Wind speed , wind direction , season , an d automobil e ag e di d no t influenc e commute r populatio n exposur e t o CO. 2 6



### 6-2 2P. 3



### Pertinen t dat a fromthe Cortes e stud yar e summarize d i n Tabl e 6-11
. Thes e result s sugges t 1. 4 <

_b<

_2. 1 fo r unspecifie d Bosto n trans- , portatio n vehicle s durin g commutin g hours
. Ziskind' s media n rati o o f 2. 7 mayb e th e resul t o f usin g some vehicle s known t o hav e leak

yexhaust s an

d no t using an

yrai l transit
.


### TABL E6-11 . RATIO S O F MEA N PERSONALCOEXPOSURE S T OMEA N CO CONCENTRATION S A T FIXE DMONITORS 2 6

mod e o f trave l al l vehicle s al l vehicle s al l vehicle s fixe dmonitor s

6 urba nsite s 2 urba nsite s meetin g EPAcriteri a 4 suburba nsite s mea npersona l exposur e mea nmonito r C O 1. 8 t o 2. 0 1. 4 2. 1



### An earlie r stud

yb yBric e an

d Roesler 2 7 

### compare d C O i n moto r vehicle s movin g i n moderate , t o heav ytraffi c wit hconcurren t con centration s measure d a t CAM P site s i n si xcities
. Tabl e 6-1 2 list s result s o f th e study
. Th e mea n o f th e fiv e ratio s i s 3.5 ; th e media n i s 2.4
. Ratio s o f vehicle s movin g i n ligh t t o moderat e traffi c woul d probabl yb e lower
. Mos t CAM P site s wer e locate d i n downtown areas ; probe s wer e usuall ypositione d 1 5 fee t of f th e street . Bric e an d Roesle r stat e tha t th e lo wrati o i n Chicag o correspond s t o a highaverag e concentratio n o f C O a t the CAM P site , whic hi s attribute d t o th e clos e proximit yo f tha t sit e t o high-densit ytraffi c routes . In-vehicl e dat a fo r Cincinnat i i s heavil yweighte d towar d downtown stree t canyons . Th e averag e rati o fo r majo r arterie s i n Cincinnat i i s 4.8
. Peterse n and Sabersky 2 8 

### measure d C O insid e a ca r drivin g a rout e i n Lo s Angele s tha t include d a busines s district , a resi

dentia l district , a par t o f a generall yuncrowde d freeway , an d a par t o f a congeste d freeway
. During a 50-minut e driv e fro m1:5 2 p.m . t o 2:4 2 durin g the summer , averag e C O varie d from 1 5 t o 2 0 ppm . Th e maximu

mreading reporte d b yAPC D fo r th e daywa s 8 pp m
6-2 3P. 4



### an d mayno t hav e occurre d concurrently
. Consequently , th e rati o o f interio r C O t o fixe d sit e C O i s a t leas t 1.9
. Thes e dat a ar e to o limite d t o mak e an yfirmestimate s o f bfo r Lo s Angeles , however
.
TABL

E 6-12
. RATIO

S O F C O I NMOTO R VEHICLES CONCURREN

T T O C O A T CAM P STATIONS 2 7



### Cit y Chicag o Cincinnat i Denve r St . Loui s Washington , D.C . Interio r CO / CAM P C O 

### 1. 3 6. 8 2. 4 2. 1 4. 7

Th e abov e studie s sugges t tha t bfo r th e transportatio n microenvironmen t shoul d fal l betwee n 1. 3 and 4.7
. I n the NE M analysis , w e use d 2.1 , th e uppe r rang e o f Cortese' s estimates , sinc e i t incorporate s movemen t b ymoto r vehicle s an d trains
. W e assume d reasonabl e bound s fo r b

_woul d b e 1.4 , th e smalles t rati o m i n Tabl e 6-11 , and- T 

### 3.5 , th e "mea n of.th e ratio s i n Tabl e 6-12
. Ther e ar e fe wdat a o n typica l level s o f C O fromcigarett e smok e i n transportatio n vehicles
. Ziskind , e t al., 2 3 

### repor t tha t chi-squar e analysi s o f taxica bdat a showe d tha t C O level s wer e no t significantl yhighe r whe n driver s and/o r passenger s smoked
. However , Harke , e t al., 1 

### measure d C O level s o f 3 0 ppmi n an un ventilate d ca r wit ha n outsid e windspee d o f 5 0 km/hou r whe n 9 cigarette s wer e smoke d intermittently
. C O level s average d 5 t o 6 ppmi n a well-ventilate d ca r wit hthre e peopl e smoking contin

uously
. Unfortunately , Hark e doe s no t giv e outsid e C O levels
. Informatio n o n th e percentag e o f automobile s tha t contai n smoker s an

d the averag e cigarette^generate d C O level s o n buse s an d train s i s unavailable
. Consequently , w e le t a + . = 0 fo r m , t 

### smoking an

d assume d tha t ou r estimat e b= 2. 1 incorporate s some o f th e smoker-generate d C O t o whic hcommuter s i n Cortese' s stud y 6-2 4P. 5



### wer e exposed
. W e mad e th e same assumptio n concerning C O from leak yexhausts , sinc e some o f Cortese' s subject s probabl ycommute d i n car s wit hleaking exhaus t systems . 6. 4 ROADSID E MICROENVIRONMENT Person s walkin g nea r roadway s ar e usuall yclose r t o th e automobile s tha t produc e C O tha n th e neares t fixe d C O monitor
. Consequently , fixe d monitor s usuall yunderestimat e roadsid e C O levels
. I f w e assume a

_+ . = 0 , the n b

_mus t excee d unit yfo r reasonabl e estimate s o f roadsid e levels
. Tw o studie s b

yWilso n an

d Schweiss 29 

### ' 3 

### ° provid e dat a usefu l i n estimating b
. I n 1977 , Wilso n an d Schweis s measure d 8-hour m (1 0 a m- 6 pm ) C O value s a t 3 3 site s i n th e centra l busines s distric t an

d 7 site s i n nearb yarea s o f Boise , Idaho , durin g Novembe r an

d December , th e seaso n whe n highC O level s frequentl y occur . Thes e value s wer e compare d t o 8-hour value s recorde d a t th e onl ycontinuou s C O monito r i n Boise
. Th e fixe d sit e wa s locate d i n th e cente r o f the downtown busines s district
. Mos t o f th e 4 0 stud

ysite s wer e nea r roadway s (but no t "hotspot " locations)
. Sampl e probe s wer e mounte d 3. 5 meter s abov e th e ground
. Roadside / fixe d monito r ratio s range d from0. 3 t o 1.5
. Th e mea n rati o wa s 0.92 ; th e media n rati o wa s 0.90
. Thes e result s sugges t tha t the fixe d statio n mayhav e bee n purposel ysite d i n a n are a o f Bois e wit hparticularl yhighC O levels
. Wilso n and Schweis s conducte d a simila r stud yi n Seattle , collecting dat a from3 6 outsid e sampler s an d 4 fixed-sit e moni

tors . Tabl e 6-1 3 summarize s thei r results
. I n thi s case , road

side/fixe d monito r ratio s rang e from0.6 9 t o 2.2 2 an d averag e abou t 1.15
. Jabara , e t al., 3 1 

### measure d the occupationa l exposur e o f Denve r traffi c officer s t o C O durin g eigh t hou r wor k shift s an d compare d th e result s t o ambien t level s a t fixe d sit e monitors
. Th e rati o o f mea n dosimete r reading t o mea n fixe d sit e reading wa s 21.7/6. 4 = 3.39
. Sinc e traffi c officer s wor k i n area s o f 6-2 5 !P. 6

TABL E6-13

. RATIO S O FMEA NC O CONCENTRATION S A

T EXPERIMENTALSITE S AN D ATFIXE D SITES 3 0

Fixedsit e Pik e St . Universit y

St . Jame s St . Fir e station Smejco r St .
mea n Stud y sit e CO/fixe dsit e CO Neares t stud y sit e 0.6 9 1.0 7 0.8 9 2.2 2 0.9 8 1.1 6 2n

dneares t stud y sit e 1.0 3 1.1 0 1.2 5 1.2 6 1.0 9 1.1 5


### congeste dtraffic , thi s rati o i s probabl y hig hfo r th etypica l pedestrian

. Amor

ereasonabl eestimat eo f b woul db e1.2 , a s m suggeste d byth e Seattl e dat a o f Wilso n an d Schweiss
. W e assume d tha t bshoul d fal l betwee n 0. 7 an d 2.3 , an d use d b= 1. 2 a s ou r mm bes t estimate
.
6. 5 OTHE R OUTDOO R LOCATION S W e assume d tha t C O level s a t outdoo r location s awa yfro m road s coul d b e approximatel yrepresente d b yx' , th e monitor

derive d C O concentration , wit hn o la g tim e o r additiv e factor
. Consequently , w e use d Equatio n 6- 1 t o estimat e C O level s i n thi s microenvironment
. Followin g th e recommendation s o f Feagans, 1 0
w e assume d a . = 0 an d tha t a reasonabl e rang e fo r b , woul d b e

m , t m 0.9 0 t o 1.00
. Feagans ' bes t estimat e fo r bwa s 0.95
. m 6. 6 SUMMAR Y Table s 6-1 4 an d 6-1 5 summariz e th e estimate s o f a . an d b m , t m fo r C O accordin g t o microenvironment , room , C O source , an d tim e o f day
. Equatio n 6- 3 wa s use d t o estimat e C O level s i n th e work-schoo l an d home-othe r microenvironments
. Equatio n 6- 1 wa s use d t o estimat e C O level s i n th e othe r thre e microenvironments
. 6-2 6P. 7



### vBL E 6-14 . ESTIMATE S O

F ADDITIV

E MICROENVIRONMENTA

L FACTORS (a

m t 

### )

Microenvironmen t Indoors : wor ko r schoo l
Indoors : home o r othe r

Transportatio n vehicl e Roadsid e Othe r outdoo r location s Pollutan t sourc e
non e smoking
non e smoking

ga s stove

non e

none

non e Roo

m 

### al l

al l

kitchen

living roo m



### N A
N A
N A Hour s ending al l al l al l 8,9,18-2 3 10-1 7 7,8,12,13,18 , 1 9 1-6,9-11 , 14-17,20-2 4 7,8,12,13,18 , 1 9 1-6,9-11 , 14-17,20-2 4 

### al l
al l
al l Estimate dva l



### lo w 0 0. 2 0 0. 1 

### 0. 1
1. 0
0. 5
0. 7
0. 3 0
0
0 bes t 0 0. 3 0 0. 3 

### 0. 2
4. 0
2. 0
2. 5
1. 0 0
0
0 ue (ppm ) hiq h 0 0. 5 0 0. 5 . 

### 0. 5

11. 0


### 3. 0

10. 0


### 2. 0 0
0
0

6-2 7P. 8

TABLE 6-15 . ESTIMATE S O F MULTIPLICATIV

E MICROENVIRONMENTA

L FACTO R( b) ' m
Microenvironmen t Indoors : wor ko r schoo l Indoors : hom

e o r othe r Transportatio nvehicl e Roadsid e Othe r outdoo r location s Estimatedvalu e 

### lo w 0.6 0 0.7 0 1.4 0 0.7 0 0.9 0 bes t

0.8 5 0.8 5 2.1 0 1.2 0 0.9 5 hig

h 1.0 5 1.1 0 3.5 0 2.3 0 1.0 0

6-2 8P. 9



### 6. 7 REFERENCE S 1
. H . P . Harke , "The proble mo f passiv e smoking
. I . Th e influenc e o f smoking o n th e C O concentratio n o f offic e rooms, " Internationa l Archive s Arbeitsmedizin , Vol
. 33 , 1974 , pp . 199-204
. 2
. S . J . Penkal a an d G . D e Oliviera , "The simultaneou s analysi s o f carbo n monoxid e an d suspende d particulat e matte r produce d b ycigarett e smoking, " Environmenta l Research , Vol
. 9 , 1975 , pp . 99-114
. 3
. D . J . Moschandreas , J . Zabransky , Jr. , and D . J . Pelton , "Indoo r ai r qualit ycharacteristic s o f the offic e environ

ment, " Pape r no . 80-61.2 , presente d a t th e 73rd Annua l Meetin g o f th e Ai r Pollutio n Contro l Association , Montreal , Quebec , Jun e 22-27 , 1980
. 4
. J . Yocom , e t al. , AStud yo f Indoor-Outdoo r Ai r Pollutan t Relationships
. Volum e I an d II , Publicatio n numbe r APTD-0592 , Researc hCorporatio n o f Ne wEngland , Hartford , Connecticut , May1970
. 5
. Genera l Electri c Company , Indoor-Outdoo r Carbo n Monoxid e Pollutio n Study , Publicatio n numbe r EPA-R4-73-020 , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolina , Decembe r 1972
. 6
. R . L . Derham , G . Peterson , R . H . Sabersky , an d F . H . Shair , "O n th e relatio n betwee n th e indoo r an d outdoo r concentra

tion s o f nitroge n oxides, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 24 , No . 2 (Februar y1974) , pp . 158-161
. 7
. G . Godin , G . Wright , an d R . J . Shepard , "Urban exposur e t o carbo n monoxide, " Archive s o f Environmenta l Health , Vol
. 25 , 1972 , pp . 305-313
. 8
. C . R . Thompson , E . G . Hensel , an d G . Kats , "Outdoor-indoo r level s o f si xai r pollutants, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 23 , No . 1 0 (Octobe r 1973)
. pp . 881-886
. 9
. D . J . Moschandreas , J . Stark , J . E . McFadden , an d S . S . Morse , Indoo r Ai r Pollutio n i n th e Residentia l Environment , Vol
. I . Dat a Collection , Analysis , an d Interpretation , ' Publicatio n numbe r EPA-600/7-78-229a , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolina , Decembe r 1978
.

6-2 9P.1 0



### 10
. Persona l communicatio n t o Te d Johnson , PEDC o Environmental , fromThoma s B . Feagans , Strategie s an d Ai r Standard s Divi

sion , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolin a 27711 , Decembe r 1981
. 11
. W . A . Cote , W . A . Wad e III , an d J . E . Yocum , AStud yo f Indoo r Ai r Quality , Publicatio n No . EPA-650/4-74-042 , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolina , Septembe r 1974
. 12
. D . P . Bridg e an d M . Corn , "Contribution s t o th e assessmen t o f non-smoker s t o ai r pollutio n fromcigarett e an d ciga r smok e i n occupie d spaces, " Environmenta l Research , Vol
. 5 , 1972 , pp . 215-220
. : 

### 13
. T . D . Sterling an d D . M . Kobayashi , "Exposur e t o Pollutant s i n Enclose d Living Spaces, " Environmenta l Research , Vol
. 13 , pp . 1-35
. 14
. U.S . Censu s data
. 15
. U.S . Housing data
. 16
. J . S . Repac e an d A . H . Lowrey , "Indoo r ai r pollution , tobacc o smoke , an

d publi c health, " Science , Vol
. 208 , May2 , 1980
. 17
. John D . Spengler , e t al. , Summaryo f Ai r Pollutio n Measure

ment s , Ai r Qualit yAssessmen t Group , Harvar d Schoo l o f Publi c Health , Boston , Massachusetts
. 18
. T . D . Sterling an d E . Sterling , "Carbo n monoxid e level s i n kitchen s an

d home s wit hga s cookers, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 29 , No . 3 (March1979) , pp . 238-241
. 19
. J . D . Spengler , B . G . Ferris , Jr. , an d D . W . Dockery , "Sulfu r dioxid e an

d nitroge n dioxid e level s insid e an d outsid e home s an

d implication s o n healt heffect s research, " Environmenta l Scienc e an d Technology , Vol
. 13 , No . 1 0 (Octobe r 1979) , pp . 1276-1280
. 20
. J . D . Spengler , K . R . Stone , and F . W . Lilley , "Highcarbo n monoxid e level s measure d i n enclose d skating rinks, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 28 , No . 8 (Augus t 1978) , pp . 776-779
. 21
. L . P . Ellio t an d D . R . Rowe , "Ai r qualit yduring publi c gatherings, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 25 , No . 6 (June 1975) , pp . 635-636
.

6-3 0P.1 1



### 22
. w . Ot t an

d N . Willits , "Modeling th e dynami c respons e o f an automobil e fo r ai r pollutio n exposur e studies, " Environmetrie s 81 , Summarie s o f Conferenc e Presentations , 1981 , pp . 104-105
. 23
. R . A . Ziskind , M . B . Rogozen , I . Rosner , an d T . Carlin , Carbo n Monoxid e Intrusio n i n Sustained-Us e Vehicles , Publicatio n numbe r SAI-068-80-535 , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolina , Novembe r 15 , 1979
. 24
. D . M . Colwil l an d A . J . Hickman , "Exposur e o f driver s t o carbo n monoxide, " pape r no . 79-59.3 , 72n d Annua l Meetin g o f th e Ai r Pollutio n Contro l Association , Cincinnati , Ohio , Jun e 24-29 , 1979
. 25
. Lanc e Wallace , "Us e o f persona l monito r t o measur e commute r exposur e t o carbo n monoxid e i n vehicl e passenge r compartments, " pape r no . 79-59.2 , 72n d Annua l Meetin g o f the Ai r Pollutio n Contro l Association , Cincinnati , Ohio , Jun e 24-29 , 1979
. 26
. A . D . Cortese , Abilit yo f Fixe d Monitorin g Station s t o Represen t Persona l Carbo n Monoxid e Exposure , thesi s sub

mitte d t o th e Facult yo f th e Harvar d Schoo l o f Publi c Health , Boston , Massachusetts , Apri l 1976
. 27
. R . M . Bric e an d J . F . Roesler , "The exposur e t o carbo n mon oxid e o f occupant s o f vehicle s movin g i n heav ytraffic, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 16 , No . 1 1 (Novembe r 1966) , pp . 597-600
. 28
. G . A . Peterso n an d R . H . Sabersky , "Measurement s o f pollu

tant s insid e a n automobile, " Journa l o f th e Ai r Pollutio n Contro l Association , Vol
. 25 , No . 1 0 (Octobe r 1975) , pp . 1028-1032
. 29
. C . B . Wilso n an d J . W . Schweiss , Par t 1
. Carbo n Monoxid e Stud y- Boise , Idaho , Novembe r 2 5 - Decembe r 22 , 1977 , Publicatio n numbe r EPA-910/9-78-055a , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolina , Septembe r 1975
. 30
. C . B . Wilso n an d J . W . Schweiss , Carbo n Monoxid e Study , Seattle , Washington , Octobe r 6 - Novembe r 2 , 1977 , publicatio n no . EPA910/9-78-054 , U.S . Environmenta l Protectio n Agency , Regio n X , Seattle , Washington , Decembe r 1978
. 31
. J . W . Jabara , T . J . Keefe , H . J . Beaulieu , an d R . M . Buchon , "Carbo n monoxide : dosimetryi n occupationa l exposure s i n Denver , Colorado, " Archive s o f Environmenta l Health , Vol
. 35 , No . 4 (July/Augus t 1980)
.
6-3 1

### SECTIO N7 EXPOSUR E ESTIMATE S FOR ADULT S WIT H CARDIOVASCULA

R DISEAS E INFOU

R URBA NAREA S
Th e compute r outpu t o f NE Mprovide s estimate s o f populatio n exposur e fo r variou s measure s o f exposur e an d averaging times
. I n the cas e o f CO , NE Mals o estimate s carboxyhemoglobi n (COHb ) levels , an importan t indicato r o f the physiologica l effect s o f C O o n the expose d population
. I n thi s sectio n the result s o f NE M analyse s o f C O exposur e i n the four stud yarea s unde r variou s ai r qualit yassumption s ar e summarized
. Extrapolation s o f thes e re sult s t o the natio n ar e presente d i n Sectio n 8
. Th e exposur e estimate s presente d i n thi s repor t ar e fo r adult s wit hcardiovascula r disease
. Adult s ar e define d t o b e thos e a t leas t 1 8 year s old
. Adult s wit hperiphera l vascula r diseas e ar e include d i n the subpopulatio n considere d t o hav e cardiovascula r disease
. Base d o n th e currentl yavailabl e evidence , thi s subpopulatio n i s judge d t o b e the mos t sensitive grou p o f person s wit hrespec t t o CO-induce d advers e healt heffects
. Estimate s fo r thre e alternativ e standard s ar e presente d i n Sectio n 7.1
. Acompariso n o f mal e an d femal e estimate s i s mad e i n Sectio n 7.2
. Th e impac t o n the exposur e estimate s o f omitting indoo r source s fro

mthe analyse s i s discusse d i n Sectio n 7.3
. A brie f discussio n concerning th e uncertaint yabou t the accuracyo f the estimate s i s provide d i n Sectio n 7.4
. 7. 1 "BES T ESTIMATE " RESULT S Table s 7- 1 through7-2 7 contai n selecte d printout s o f a NE M analysi s o f exposur e o f adult s wit hcardiovascula r diseas e t o C O i n the four stud yarea s unde r variou s ai r qualit yassumptions
. Eac htabl e i s identifie d a s t o CO/COHbindicato r an d ai r qualit y standard being simulated
. C O exposur e estimate s ar e provide d fo r bot h1

- an

d 8-hou r averag e C O concentrations
. I n eac hcase , the

7- 1P.1 3



### TABL E 7-1
. ESTIMATE S O F OCCURRENCE S FO R ADULT S WITH CARDIOVASCULA R DISEAS E O F 1-HOU R C O EXPOSURE S ABOV E SELECTE D CONCENTRATIO N 

### VALUE S ASSUMIN

G9 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 CONCENTRATION 1 1 EXCEEDE D1 1 (PPM ) I

1 60. 0 1 1 55. 0 1 1 50. 0 1 1 45. 0 1 1 40. 0 1 1 35. 0 1 1 30. 0 1 1 25. 0 I 1 20. 0 I
t 15. 0 1 1 12. 0 I 1 9. 0 1 1 7. 0 1 1 0. 0 1

1 MAX . CONCENTRATION 1 1 ENCOUNTER S A T MAX . I CHICAG OI

1,25 0 1 25.30 0 1 223.00 0 1 828.00 0 1 3.080.00 0 1 10.600.00 0 1 1,070.000,00 0 1

25. 6 1 52 3 I LO S ANGELE S

5,79 0 145,00 0 1,310,00 0 4,930,00 0 22,100,00 0 2,670,000.00 0

21. 6 5.79 0 PHILADELPHI A

-

1,28 0

1,28 0 3,80 0 22,90 0 141,00 0 389,00 0 1,140,00 0 4,120,00 0 1,020,000,00 0

36. 0 1,27 0 S T LOUI S 1

70 9 1 6,91 0 1 13,50 0 i 39,20 0 1 216,00 0 1 878,00 0 1 2,880,00 0 1 416,000,00 0 1

32. 0 I 70 7 I



### 7- 2P.1 4



### TABL E 7-2 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOHAV

E 1-HOU RC OEXPOSURE S ABOVE SELECTE DCONCENTRATIO N VALUE S ASSUMIN

G 9 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 CONCENTRATIO

N 1 1 i 1 | 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A1 S

TLOUIS 1 1 (PPM) 1 I I | |

1 60. 0 1 I I I 1 1 55. 0 I I 1 I | 1 50. 0 1 1 1 I I 1 45. 0 1 1 1 1 I 1 40. 0 1 1 1 1 I 1 35. 0 1 1 I 1,27 0 1 1 1 30. 0 1 I I 1,27 0 1 707 I 1 25. 0 I 1,25 0 I I 3.80 0 1 6.20 0 1 1 20. 0 1 11,40 0 1 ' 5,79 0 1 21,60 0 1 7,27 0 1 1 15. 0 1 22,30 0 1 62,20 0 1 36,80 0 1 19,50 0 1 1 12. 0 I 54,900 - 1 188,00 0 1 69,30 0 1 28,80 0 1 1 9. 0 I 109,00 0 I 256,00 0 1 85,40 0 1 36,60 0 1 1 7. 0 1 121,00 0 1 304,00 0 1 110,00 0 1 44,80 0 1 1 0. 0 I 122,00 0 1 305,00 0 1 116,00 0 1 47,50 0 1

1 MAX
. CONCENTRATIO

N 1 25. 6 1 21. 6 1 36. 0 1 32. 0 1 1 PEOPL E A TMAXIMU

M 1 52 3 1 5,79 0 1 1,27 0 1 707 1



### 7- 3P.1 5



### TABL E 7-3
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WHOS E MAXIMU M 1-HOU RC O EXPOSUR E OCCUR S I NSELECTE D CONCENTRATIONRANGE S ASSUMING9 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 CONCENTRATIO

N 1 RANGE 1 (PPM )

1 60. 0 1 55. 0 1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0 < < < < < <
<
<
<
<
<
<
<
< c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = 100. 0 60. 0 55. 0 50. 0 45. 0 40. 0 35. 0 30. 0 25. 0 20. 0 15. 0 12. 0 9. 0 7. 0

1 MAX . CONCENTRATIO

N 1 PEOPL E A

T MAXIMU

M CHICAG O

1,25 0 10.10 0 10.90 0 32,60 0 54,50 0 11,70 0 49 4

25. 6 52 3 LOS ANGELE S

5,79 0 56,40 0 126,00 0 68,00 0 47,60 0 1,36 0

21. 6 5,79 0 PHILADELPHI A

1,28 0

2,52 0 17,90 0 15,10 0 32,50 0 16.00 0 25,10 0 5,91 0

36. 0 1,27 0 S T LOUI S 1

70 9 I 5,49 0 1 1,07 0 1 12,20 0 1 9,24 0 1 7,86 0 1 8,16 0 1 2,73 0 1

32. 0 1 70 7 1



### 7- 4

### TABL E 7-4 . ESTIMATE S OF OCCURRENCE S FO RADULT S WITHCARDIOVASCULA RDISEAS E OF 8-HOU RC OEXPOSURE S ABOV

E SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 9 PPM/ 1 EXE

XSTANDARDI S ATTAINE D P.1 6

I CONCENTRATIO

N 1 I I 1 | 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A1 S

TLOUIS 1 1 (PPM) 1 1 1 1 1

1 60. 0 1 1 I I | 1 55. 0 1 1 1 1 1 1 50. 0 I I 1 | I 1 45. 0 1 1 1 1 1 1 40. 0 1 1 1 1 1 1 35. 0 1 1 1 | I 1 30. 0 1 I I I 1 1 25. 0 1 I I 1 1 1 20. 0 1 1 - 1 1 I 1 15. 0 1 1 / 1 I 1 1 12. 0 1 12 2 1 1 24,60 0 1 1 1 9. 0 1 107,00 0 I 153,00 0 1 322,00 0 1 66,50 0 1 1 7. 0 1 2.070.00 0 1 2,170,00 0 1 1,030,00 0 1 429,00 0 1 1 0. 0 1 1,070,000,00 0 1 2,670,000,00 0 1 1,020,000,00 0 1 416,000,00 0 1

1 MAX
. CONCENTRATIO

N 1 12. 0 1 10. 6 1 14. 0 1 11. 5 1 1 ENCOUNTER

S A TMAX
. 1 5 4 1 4,46 0 1 2 9 1 1 1 1



### 7- 5P.1 7



### TABL E 7-5 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOHAV

E 8-HOU RC OEXPOSURE S ABOVE SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 9 PPM/ 1 EXE

XSTANDARDI S ATTAINED

1 CONCENTRATIO

N1 1 1 1 1 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A IST LOUI S 1 1 (PPM

) II I1 1

1 60. 01 II I1 1 55. 01 III I 1 50. 01 1 1 1 1 1 45. 0II| | | 1 40. 01 1 1 1 1 1 35. 01 1 1 1 1 1 30. 0II II| 1 25. 01 I I1 1 1 20. 01 1 1 1 1 1 15. 01 1 1 1 1 1 12. 01 12 01 1 11,90 01 I 1 9. 01 5,26 0 I5,79 01 34,30 01 13,30 01 1 7. 01 67,20 01 147,00 01 48,30 01 24,20 01 1 0. 01 122,00 0I305,00 01 116,00 01 47,50 01

1 MAX . CONCENTRATIO

N1 12. 01 10. 6 1 14. 01 11. 5 1 1 PEOPL E A T MAXIMU

M1 5 4 1 4,46 0 1 2 9 1 1 1 1



### 7- 6P.1 8



### TABL E 7-6 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E WHOS E MAXIMU M 8-HOU RC OEXPOSURE OCCUR S I

N SELECTEDCONCENTRATIO

N RANGE S ASSUMIN

G 9 PPM/ 1 EXE

XSTANDAR

DI S ATTAINED

1 CONCENTRATIO

N1 1 1 1 I 1 RANG

E 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 ST LOUI S 1 1 (PPM

) 1 III I

1 60. 0< C <= 100. 01 II I1 1 55. 0< C <

= 60. 01 1 1 | < 1 1 50. 0< C <

= 55. 01 1 1 1 I 1 45. 0< C <

= 50. 01 1 1 II 1 40. 0< C < - 45. 0I I1 II 1 35. 0< C <= 40. 01 1 1 II 1 30. 0< C <

= 35. 01 I I1 1 1 25. 0< C <

= 30. 0II II| 1 20. 0< C <= 25. 01 1 - 1 I| 1 15. 0< C <

= 20. 01 1 1 1 I 1 12. 0< C <

= 15. 01 12 21 1 11.90 01 1 1 9. 0< C <

= 12. 01 5.14 0I5,79 01 22,40 01 13,30 01 1 7. 0< C <

= 9. 0I61,90 0I141,00 01 14,00 01 10,90 01 1 0. 0< C <= 7. 0I54,40 01 158,00 01 68,00 01 23,30 01

1 MAX . CONCENTRATIO

N1 12. 01 10. 6 1 14. 01 11. 5 1 1 PEOPL E A T MAXIMU

M1 5 4 I4,46 0I2 9 1 1 1 1



### 7- 7P.1 9



### TABL E 7-7 . ESTIMATE S OF OCCURRENCE S FO RADULT S WITHCARDIOVASCULA RDISEAS E OF COH bLEVEL S EXCEEDIN

GSELECTEDVALUE S ASSUMIN G 9 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 COH

B LEVEL 1 1 1 1 1 1 EXCEEOE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A1 S

TLOUIS 1 1 (PERCENT

) 1 1 1 1 1

1 3.7 0 1 1 I I 1 1 3.5 0 1 I I 1 1 1 3.3 0 1 1 1 1 1 1 3.1 0 1 1 1 I I 1 3.0 0 1 I I I I 1 2.9 0 1 1 1 1 1 1 2.7 0 1 I I 1 1 1 2.5 0 1 1 1 1 1 1 2.3 0 1 1 1 7 1 1 1 1 2.1 0 1 1 I 1,49 0 1 1 1 2.0 0 1 1 1 5,15 0 1 2 1 1 1 1.5 0 1 78,30 0 1 115,00 0 1 236,00 0 1 53,40 0 1 1 1.0 0 1 8,600,00 0 1 19,800,00 0 1 2,540,00 0 1 2,000,00 0 1 1 0.0 0 1 1,070,000,00 0 I 2,670,000,00 0 1 1,020,000,00 0 1 416,000,00 0 1

1 MAX
. COH B CONC
. 1 1.9 2 1 1.8 7 1 2.3 1 1 2.0 2 1 1 ENCOUNTER

S A TMAX
. I 5 4 1 70 1 1 1 5 1 5 1



### 7- 8P.2 0



### TABL E 7-8 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOEXPERIENC E COH bLEVEL S EXCEEDIN

GSELECTE DVALUE S ASSUMIN G 9 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 COH

B LEVE L 1 1 1 II 1 EXCEEOE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 S

T LOUI S 1 1 (PERCENT

) 1 1 1 I|

1 3.7 0III I1 1 3.5 01 1 I| | 1 3.3 01 1 1 1 I 1 3.1 01 1 1 1 1 1 3.0 01 1 1 1 I 1 2.9 0 I II| | 1 2.7 01 I I1 I 1 2.5 0 1 1 1 1 I 1 2.3 0 1 1 I3 5 1 1 1 2.1 0 1 II68 5 1 I 1 2.0 0 1 II2,73 01 2 1 1 1 1.5 01 9,68 01 5,79 01 34,30 01 15,70 01 1 1.0 01 99,00 0I253,00 01 86,20 01 34,00 01 1 0.0 01 122,00 0| 305,00 01 116,00 01 47,50 01

1 MAX . COH B CONC . 1 1.9 21 1.8 71 2.3 1 1 2.0 21 1 PEOPL E A T MAXIMU

M1 5 4 1 70 1 1 1 5 1 5 1



### 7- 9P.2 1 ,



### TABL E 7-9
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WHOS E MAXIMU M COHbLEVE L OCCUR S I

NSELECTE D RANGE S ASSUMING 9 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 COH

B LEVE L 1 1 1 1 1 1 RANG

E 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 ST LOUI S 1 1 (PERCENT

) 1 1 1 1 1

1 3.7 0< C <

= 10.0 01 1 I I1 1 3.5 0< C <

= 3.7 01 | I| | 1 3.3 0< C <= 3.5 01 1 1 1 I 1 3.1 0< C <

= 3.3 01 1 1 II 1 3.0 0< C <= 3.1 01 1 1 1 1 I2.9 0 < C <

= 3.0 01 1 1 1 1 1 2.7 0 < C <

= 2.9 0 1 I II| 1 2.5 0 < C <= 2.7 01 I I1 1 1 2.3 0 < C <

= 2.5 0 1 1 1 3 6 1 1 1 2.1 0< C <

= 2.3 01 1 I65 1 1 1 1 2.0 0 < C <= 2.1 0 I I1 2,04 01 2 1 1 1 1.5 0< C <= 2.0 0 1 9,68 01 5,79 01 31,60 01 15,70 01 I1.0 0< C <= 1.5 01 89,30 01 248,00 01 51,90 01 18,30 01 1 0.0 0< C <= 1.0 0I22,60 01 52,00 01 30.20 01 13,50 01

1 MAX . COH B CONC . 1 1.9 21 1.8 71 2.3 1 1 2.0 21 1 PEOPL E A T MAXIMU

M1 5 4 1 70 1 1 1 5 1 5 1



### 7-1 0P.2 2



### TABL E 7-10 . ESTIMATE S OF OCCURRENCE S FO RADULT S WITHCARDIOVASCULA RDISEAS E OF 1-HOU RC OEXPOSURE S ABOV

E SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 1 2 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 CONCENTRATION 1 1 EXCEEDE D1 1 (PPM ) I

1 60. 0 1 1 55. 0 1 1 50. 0 1 1 45. 0 I 1 40. 0 1 1 35. 0 1 1 30. 0 1 1 25. 0 1 1 20. 0 1 1 15. 0 1 1 12. 0 1 1 9. 0 I 1 7. 0 1 1 0. 0 1

1 MAX . CONCENTRATION 1 1 ENCOUNTER S AT MAX . 1 2 9 2 5 1,07 0 CHICAG O

11.20 0 50,50 0 223,00 0 987,00 0 ,640,00 0 ,320,00 0 ,700,00 0 ,000,00 0

34. 6 52 3 LO S ANGELE S

17,40 0 145,00 0 1.310,00 0 4,840,00 0 13,900,00 0 55,800,00 0 2,670,000.00 0

29. 1 5,79 0 PHILADELPHI A

1,28 0 1,28 0 1,28 0 3,80 0 33,10 0 141,00 0 397,00 0 1,070,00 0 3,700,00 0 8,990,00 0 1,020,000,00 0

49. 0 1,27 0 S T LOUI S 1

70 9 1 6,91 0 1 6,91 0 1 24,00 0 1 36,10 0 1 248,00 0 1 628,00 0 1 2,000,00 0 1 5,430,00 0 1 416,000,00 0 1

44. 0 1 70 7 1



### 7-1 1

.P.23



### TABL E 7-11 . ESTIMATE S O F ADULT S WIT HCARDIOVASCULA RDISEAS E WHOHAV

E 1-HOU RC OEXPOSURE S ABOV

E SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 1 2 PPM/ 1 EXE

XSTANDAR

DI S ATTAINED

1 CONCENTRATIO

N 1 EXCEEOE

O 1 (PPM )

1 60. 0 1 55. 0 1 50. 0 1 ^ 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATIO

N 1 PEOPL E A T MAXIMU

M CHICAG O

•

11,20 0 11,40 0 22,30 0 59,20 0 108,00 0 119,00 0 122,00 0 122,00 0

34. 6 52 3 LOS ANGELE S

5,79 0 62,20 0 188,00 0 256,00 0 296,00 0 305,00 0 305,00 0

29. 1 5,79 0 PHILADELPHI A

1,27 0 1,27 0 1,27 0 3,80 0 23,00 0 36,80 0 69,30 0 85,40 0 109,00 0 116,00 0 116,00 0

49. 0 1,27 0 S T LOUI S 1

70 7 1 6,20 0 1 6,20 0 I 16,10 0 1 19,90 0 1 28,80 0 1 32,40 0 1 43,70 0 1 47,50 0 1 47,50 0 1

44. 0 1 70 7 1



### 7-1 2P.2 4



### TABL E 7-12 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E WHOS E MAXIMU M 1-HOU RC OEXPOSURE OCCUR S I

N SELECTEDCONCENTRATIO

N RANGE S ASSUMIN

G 1 2 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 CONCENTRATIO

N 1 1 1 1 | 1 RANG

E 1 CHICAG O1 LOS ANGELE S 1 PHILADELPHI A 1 S T LOUI S 1 1 (PPM ) 1 1 1 1 1

1 60. 0 < C < = 100. 0 I I I I | 1 55. 0 < C < = 60. 0 1 I I | I 1 50. 0 < C < = 55. 0 1 1 I | ' 1 1 45. 0 < C < = 50. 0 1 1 1 1,28 0 1 1 1 40. 0 < C < = 45. 0 1 1 1 1 70 9 1 1 35. 0 < C < = 40. 0 1 1 1 j 5,49 0 1 1 30. 0 < C < = 35. 0 1 11,20 0 1 1 2,52 0 1 1 1 25. 0 < C < = 30. 0 1 18 2 1 5,79 0 1 19,20 0 1 9,90 0 1 1 20. 0 < C < = 25. 0 1 10,90 0 1 - 56,40 0 1 13,80 0 1 3,84 0 1 1 15. 0 < C < = 20. 0 I 36,90 0 1 126,00 0 1 32,50 0 1 8,83 0 1 1 12. 0 < C < = 15. 0 1 48,70 0 1 68,00 0 1 16,00 0 1 3,59 0 1 1 9. 0 < C < = 12. 0 1 11,00 0 I 39,50 0 1 23,20 0 1 11,30 0 1 1 7. 0 < C < = 9. 0 1 2,67 0 1 8,79 0 1 7,85 0 1 3,77 0 1 1 0. 0 < C < = 7. 0 I 6 8 1 71 4 1 1 3 8 1

1 MAX . CONCENTRATIO

N 1 34. 6 1 29. 1 1 49. 0 1 44. 0 1 1 PEOPL E A T MAXIMU

M 1 52 3 1 5,79 0 1 1,27 0 1 70 7 1



### 7-1 3P.2 5P.2 6



### TABL E 7-14
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WH O HAVE 8-HOU RC O EXPOSURE S ABOVE SELECTE D CONCENTRATIONVALUE S ASSUMING

1 2 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 CONCENTRATIO N 1 1 1 1 1 1 EXCEEDED 1 CHICAG O 1 LO S ANGELE

S 1 PHILADELPHI A1 S TLOUI S 1 1 (PPM ) 1 1 1 I |

1 60. 0 1 1 I I 1 1 55. 0 1 1 | | | 1 50. 0 I I 1 I | 1 45. 0 I I I | | 1 40. 0 1 1 1 1 1 1 35. 0 1 1 1 1 I 1 30. 0 1 I I | | 1 25. 0 1 1 1 1 1 1 20. 0 I I I | | 1 15. 0 1 1,90 0 I I 17,30 0 I 2 7 1 1 12. 0 I 5,26 0 I 5,79 0 1 33,50 0 1 8,80 0 1 1 9. 0 1 67,30 0 I 95,60 0 1 44,30 0 1 23,70 0 1 1 7. 0 1 93,30 0 1 252,00 0 1 104,00 0 1 29,00 0 1 1 0. 0 I 122,00 0 I 305,00 0 1 116,00 0 1 47,50 0 1

1 MAX
. CONCENTRATIO N 1 16. 0 1 13. 6 1 18. 5 1 15. 0 1 1 PEOPLE A

TMAXIMU M 1 5 4 1 4,46 0 1 2 9 1 1 1 |



### 7-1 5E^2_
.

TABL E 7-15

. ESTIMATE S O F ADULTS WIT H CARDIOVASCULA R DISEAS E WHOS E MAXIMU M 8-HOU R C

O EXPOSUR E OCCUR

S I N SELECTE D CONCENTRATIO N RANGES ASSUMIN G 1 2 PPM/ 1 EXEXSTANDAR D I S ATTAINE D

1 CONCENTRATIO

N1 1 1 1 1 1 RANG

E 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 ST LOUI S 1 1 (PPM

) 1 1 1 1 1

1 60. 0< C <= 100. 01 1 I I1 1 55. 0< C <= 60. 01 I1 I I 1 50. 0< C <= 55. 01 II I1 1 45. 0< C <

= 50. 01 III I 1 40. 0< C <= 45. 01 1 1 1 1 1 35. 0< C <= 40. 01 1 1 I1 1 30. 0< C < - 35. 01 I II1 1 25. 0< C <

= 30. 01 I I1 1 1 20. 0< C < = 25. 01 1 1 1 1 1 15. 0< C <= 20. 01 1,91 01 1 17,30 01 2 9 1 1 12. 0< C <= 15. 01 3,36 01 5,79 01 16,20 01 8,77 01 1 9. 0< C <

= 12. 01 62,00 01 89,80 01 10,80 01 14,90 01 1 7. 0< C <= 9. 01 26.10 01 156,00 01 59,60 01 5,31 01 1 0. 0< C <= 7. 0I28,30 0i53.50 01 12.40 01 18,50 01

1 MAX . CONCENTRATIO

N1 16. 01 13. 6 1 18. 5 1 15. 01 1 PEOPL E A T MAXIMU

M1 5 4 I4,46 01 2 9 1 1 1 1



### 7-1 6P.2 8

TABL E 7-16 . ESTIMATE S O FOCCURRENCE S FO R ADULT S WIT H CARDIOVASCULA R DISEAS E

O FCOHb
. LEVEL S EXCEEDIN G SELECTE D VALUE S ASSUMIN G

1 2 PPM/ 1 EXEXSTANDAR D I S ATTAINE D

1 COHB LEVE L 1 EXCEEDED 1 (PERCENT)

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 3.0 0 1 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.0 0 1 1.5 0 1 1.0 0 1 0.0 0

1 MAX
. COHB CONC
. 1 ENCOUNTER

S A TMAX
. 

### j CHICAG O 1

13 4 1 2.46 0 1 16.60 0 1 39.70 0 1 1.240.00 0 1 32.700.00 0 1 1,070.000.00 0 1

2.5 2 1 2 4 1 LO

S ANGELE

S

5,19 0 18,20 0 35,90 0 927,00 0 75,600,00 0 2,670,000,00 0

2.3 8 1,56 0 PHILADELPHI A

7 1 32 9 1,84 0 8,85 0 42,30 0 114,00 0 163,00 0 861,00 0 7,140,00 0 1,020,000,00 0

3.0 3 1 5 STLOUI S 1

18 7 I 3,98 0 1 16,40 0 I 31,50 0 I 243.00 0 I 5.490,00 0 I 416,000,00 0 1

2.5 9 I 5 1



### 7-1 7P.2 9



### TABL E 7-17 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOEXPERIENC E COH bLEVEL S EXCEEDIN

GSELECTEDVALUE S ASSUMIN G 1 2 PPM/ 1 EXE

XSTANDAR

DI S ATTAINE D

1 COH B LEVE L 1 EXCEEOE O 1 (PERCENT )

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 3.0 0 1 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.0 0 1 1.5 0 1 1.0 0 1 0.0 0

1 MAX . COH B CONC . 1 PEOPL E AT MAXIMU M CHICAG O

7 8 1,25 0 3,77 0 8,91 0 60,00 0 120,00 0 122,00 0

2.5 2 2 4 LO S ANGELE S

2,47 0 5,09 0 5,79 0 65,40 0 300,00 0 305,00 0

2.3 8 1,56 0 PHILADELPHI A

3 5 15 6 77 6 4,67 0 17,10 0 29,40 0 32,10 0 36,80 0 114,00 0 116,00 0

3.0 3 1 5 S T LOUI S 1

18 6 1 2.78 0 1 7,50 0 1 12,60 0 1 24,30 0 1 43,10 0 1 47,50 0 1

2.5 9 1 5 1



### 7-1 8P.3 0



### TABL E 7-18 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOS E MAXIMU M COH bLEVEL OCCUR S I

N SELECTEDRANGE S ASSUMIN G 1 2 PPM/ 1 EXE

XSTANDAR

DI S ATTAINED

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 3.0 0 1 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.0 0 1 1.5 0 1 1.0 0 1 0.0 0 COH B LEVE L

RANG E (PERCENT )

<
<
<
<
<
< <
<
<
<
<
<
<
<

1 MAX . 1 PEOPL E C < =

C < = C < = c < = c < = c < = c <- c < = c < = c < = c < = c < = c < = c < = 10.0 0

3.7 0 3.5 0 3.3 0 3.1 0 3.0 0 2.9 0 2.7 0 2.5 0 2.3 0 2.1 0 2.0 0 l.S O 1.0 0

COH B CONC . AT MAXIMU

M CHICAG O

7 9 1,18 0 2.51 0 5.15 0 51.10 0 59,60 0 1,93 0

2.5 2 2 4 LO S ANGELE S

2,47 0 2,62 0 70 0 59,60 0 234,00 0 5,66 0

2.3 8 1,56 0 PHILADELPHI A

3 6

- ~ 12 1 62 1 3,89 0 12,40 0 12,30 0 2,73 0 4,68 0 77,50 0 2,05 0

3.0 3 1 5 S T LOUI S

18 7 2,59 0 4,72 0 5,13 0 11,70 0 18,80 0 4,46 0

2.5 9 5



### 7-1 9P.31



### TABL E 7-19
. ESTIMATE S O F OCCURRENCE S FORADULT S WIT H CARDIOVASCULA RDISEAS E O F 1-HOU RC O EXPOSURE S ABOVE SELECTE D CONCENTRATIONVALUE S ASSUMING

1 5 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 CONCENTRATION 1 1 EXCEEDE D1 1 (PPM ) 1

1 60. 0 1 1 55. 0 1 1 50. 0 1 1 45. 0 1 1 40. 0 1 1 35. 0 1 1 30. 0 1 1 25. 0 1 1 20. 0 1 1 15. 0 I 1 12. 0 1 1 9. 0 I 1 7. 0 I 1 0. 0 I

1 MAX . CONCENTRATION 1 1 ENCOUNTER S A T MAX . I CHICAG O

11,20 0 21,90 0 63,30 0 212,00 0 667,00 0 2,520,00 0 6,190,00 0 19,800,00 0 49,800,00 0 1,070,000,00 0

43. 6 52 3 LO S ANGELE S

5,79 0 23,20 0 145,00 0 849,00 0 3,440,00 0 8,030,00 0 31,500,00 0 109,000,00 0 2,670,000,00 0

37. 0 5,79 0 PHILADELPHI A

1,28 0 1,28 0 1,28 0 1,28 0 3,80 0 22,90 0 55,00 0 141,00 0 277,00 0 1,050,00 0 2,090,00 0 5,750,00 0 13,300,00 0 1,020,000,00 0

61. 5 1,27 0 S T LOUI S 1

70 9 1 70 9 1 1,42 0 1 6,91 0 1 13,50 0 I 24,10 0 1 32,80 0 1 181,00 0 1 513,00 0 I 1,130,00 0 I 3,270,00 0 1 9,220,00 0 1 416,000,00 0 1

56. 1 1 70 7 1



### 7-2 0P.3 2



### TABL E 7-20 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E WHOHAV

E 1-HOU RC OEXPOSURE S ABOV

E SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 1 5 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 CONCENTRATION 1 EXCEEDE D 1 (PPM )

1 60. 0 1 55. 0 1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 PEOPL E A T MAXIMU M CHICAG O

11,20 0 11,20 0 19,20 0 22,30 0 53,20 0 108,00 0 118,00 0 122,00 0 122,00 0 122,00 0

43. 6 52 3 LO S ANGELE S

5,79 0 5,79 0 62,20 0 167,00 0 256,00 0 287,00 0 305,00 0 305,00 0 305,00 0

37. 0 5,79 0 PHILADELPHI A

1,27 0 1,27 0 1,27 0 1,27 0 3,80 0 21,60 0 26,50 0 36,80 0 50,40 0 85,40 0 93,60 0 116,00 0 116,00 0 116,00 0

61. 5 1,27 0 S T LOUI S 1

70 7 I 70 7 1 70 7 I 6,20 0 1 7,27 0 1 16,30 0 I 18,60 0 1 26,30 0 1 32,30 0 1 40,00 0 1 46,60 0 1 47,50 0 1 47,50 0 1

56. 1 1 70 7 I



### 7-2 1P.3 3



### TABL E 7-21
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WHOS E MAXIMU M 1-HOU RC O EXPOSUR E OCCUR S INSELECTE D CONCENTRATIONRANGE S ASSUMING

1 5 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 CONCENTRATION 1 RANG E 1 . (PPM )

1 60. 0 1 55. 0 1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0 < C < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = 100. 0

60. 0 55. 0 50. 0 45. 0 40. 0 35. 0 30. 0 25. 0 20. 0 15. 0 12. 0 9. 0 7. 0

1 MAX . CONCENTRATION 1 PEOPL E A T MAXIMU M CHICAG O

11,20 0

8,02 0 3,05 0 30,90 0 54,60 0 10,40 0 3,35 0 6 8

43. 6 52 3 LO S ANGELE S

5,79 0

56,40 0 105,00 0 89,10 0 30,50 0 17,70 0 71 4

37. 0 5,79 0 PHILADELPHI A

1,28 0

2,52 0 17,90 0 4,88 0 10,30 0 13,60 0 35,00 0 8,27 0 22,70 0

61. 5 1,27 0 S T LOUI S I

70 9 I

5,49 0 1 1,07 0 1 8,99 0 1 2,38 0 I 7,67 0 I 6,01 0 1 7,64 0 1 6,66 0 1 88 0 1

56. 1 1 70 7 |



### 7-2 2P.3 4



### TABL E 7-22 . ESTIMATE S OF OCCURRENCE S FO RADULT S WITHCARDIOVASCULA RDISEAS E OF 8-HOU RC OEXPOSURE S ABOVE SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 1 5 PPM/ 1 EXE

XSTANDAR

DI S ATTAINED

1 CONCENTRATION 1 EXCEEDE D I (PPM )

1 60. 0 1 55. 0 1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 ENCOUNTER S A T MAX . CHICAG O1

12 2 1 53,50 0 I 939,00 0 1 7.390,00 0 I 29,100,00 0 1 1,070,000,00 0 1

20. 0 1 12 0 1 LO S ANGELE S

55,90 0 647,00 0 8,150,00 0 43,200,00 0 2,670,000.00 0

17. 0 4,46 0 PHILADELPHI A 1

12,60 0 I 243,00 0 1 704,00 0 1 2,000,00 0 1 5,940,00 0 1 1,020,000,00 0 1

23. 0 1 2 9 1 S T LOUI S 1

38,90 0 I 186,00 0 I 1,020,00 0 1 3,670,00 0 1 416,000,00 0 1

18. 5 1 1 1 1



### 7-2 3P.3 5



### TABL E 7-23 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOHAV

E 8-HOU RC OEXPOSURE S ABOV

E SELECTEDCONCENTRATIO N VALUE S ASSUMIN

G 1 5 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 CONCENTRATIO

N 1 I I 1 | 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHIA1 S TLOUIS 1 1 (PPM) 1 1, 1 1 I 1 ' II I I |
1 60. 0 1 1 1 I I 1 55. 0 1 1 1 | I 1 50. 0 1 1 1 1 1 1 45. 0 1 1 1 1 1 1 40. 0 1 1 1 | | 1 35. 0 1 1 1 1 I 1 30. 0 1 I I | | 1 25. 0 1 1 1 1 1 1 20. 0 1 12 0 1 1 5,87 0 1 1 1 15. 0 1 5,26 0 1 5.79 0 1 33,50 0 1 8,30 0 1 1 12. 0 I 54,50 0 1 12.20 0 1 36,60 0 1 23,10 0 1 1 9. 0 I 84,20 0 1 234,00 0 1 81,80 0 1 28,80 0 1 1 7. 0 I 118,00 0 1 298,00 0 1 116,00 0 1 36,10 0 1 1 0. 0 1 122,00 0 1 305,00 0 1 116,00 0 1 47,50 0 1

1 MAX
. CONCENTRATIO

N 1 20. 0 1 17. 0 1 23. 0 1 18. 5 1 1 PEOPL E A TMAXIMU

M 1 12 0 1 4,46 0 1 2 9 1 1 1 1



### 7-2 4P.3 6



### TABL E 7-24 . ESTIMATE S O F ADULT S WITHCARDIOVASCULA RDISEAS E WHOS E MAXIMU M 8-HOU RC OEXPOSURE OCCUR S I

N SELECTEDCONCENTRATIO

N RANGE S ASSUMIN

G 1 5 PPM/ 1 EXE

XSTANDARD I S ATTAINE D

1 CONCENTRATIO

N 1 1 1 I | 1 RANG

E 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A1 S

TLOUIS 1 1 (PPM ) 1 I 1 j j

1 60. 0 < C < = 100. 0 1 1 1 I I 1 55. 0 < C <= 60. 0 I I I | | 1 50. 0 < C < = 55. 0 1 1 1 I | 1 45. 0 < C <= 50. 0 1 1 1 1 I 1 40. 0 < C <= 45. 0 1 1 1 1 1 1 35. 0 < C < = 40. 0 1 1 I | | 1 30. 0 < C <= 35. 0 1 I I I | 1 25. 0 < C <= 30. 0 I I 1 1 I 1 20. 0 < C <= 25. 0 1 12 2 1 1 5.87 0 1 1 1 15. 0 < C <= 20. 0 1 5,14 0 1 5,79 0 1 27,60 0 1 8,30 0 1 1 12. 0 < C < = 15. 0 1 49,30 0 1 6,44 0 1 3,05 0 1 14,80 0 1 1 9. 0 < C <= 12. 0 1 29,70 0 1 222,00 0 1 45,30 0 1 5,73 0 1 1 7. 0 < C <= 9. 0 1 33,50 0 1 64,40 0 1 34,50 0 1 7,26 0 1 1 0. 0 < C <= 7. 0 1 3.89 0 1 7,13 0 1 1 11,50 0 1

1 MAX
. CONCENTRATIO

N 1 20. 0 1 17. 0 1 23. 0 1 18. 5 1 1 PEOPL E A TMAXIMU

M 1 12 0 1 4,46 0 1 2 9 1 1 1 1



### 7-2 5_P.3 7



### TABL E 7-25
. ESTIMATE S O F OCCURRENCE S FO R ADULT S WITH CARDIOVASCULA RDISEAS E O F COHb LEVELS EXCEEDIN G SELECTE D VALUE S ASSUMIN G

1 5 PPM/ 1 EXEXSTANDAR D I S ATTAINE D

1 COH B LEVE L 1 1 EXCEEDE D1 1 (PERCENT ) 1

1 3.7 0 I 1 3.5 0 1 1 3.3 0 1 1 3.1 0 1 1 3.0 0 1 1 2.9 0 1 1 2.7 0 1 1 2.5 0 I 1 2.3 0 I 1 2.1 0 1 1 2.0 0 1 1 1.5 0 1 1 1.0 0 1 1 0.0 0 1

1 MAX . COH B CONC . 1 1 ENCOUNTER S A T MAX . 1 5 6 7 1,07 0 CHICAG OI

6 7 1 24 0 1 1,13 0 1 6,33 0 1 21,30 0 1 71,20 0 I 180,00 0 1 361.00 0 1 ,120,00 0 1 ,400,00 0 1 ,000.00 0 I

3.1 0 1 5 4 f LOS ANGELE S 1

1.56 0 1 8,65 0 1 21.40 0 1 61,00 0 1 193,00 0 1 319,00 0 f 6,320,00 0 1 166,000,00 0 1 2,670,000,00 0 1

2.8 9 1 70 1 1 PHILADELPHI A 1

1 1 5 1,02 0 7 9 1

83 3 1 1,91 0 1 6,04 0 1 11,90 0 1 24,30 0 1 65,40 0 I 131,00 0 1 216,00 0 1 371,00 0 I 493,00 0 I ,850,00 0 I ,100,00 0 1 ,000,00 0 1

3.7 5 1 1 5 1 1 2

41 6 S T LOUIS 1

12 0 I 33 2 1 1,64 0 1 7,90 0 I 20,40 0 I 46,30 0 1 84,80 0 1 108,00 0 1 789,00 0 1 ,500,00 0 1 ,000,00 0 I

3.1 6 1 5 1



### 7-2 6P.3 8



### TABL E 7-26 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E WHOEXPERIENC E COH bLEVEL S EXCEEDIN

GSELECTEDVALUE S ASSUMIN G 1 5 PPM/ 1 EXE

XSTANDAR

DI S ATTAINED

1 COH B LEVE L 1 EXCEEDE D 1 (PERCENT )

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 3.0 0 1 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.0 0 1 1.5 0 1 1.0 0 1 0.0 0

1 MAX . COH B CONC . 1 PEOPL E AT MAXIMU M CHICAG O

6 6 8 1 80 0 2,39 0 4,20 0 9,17 0 20,10 0 32,50 0 85,30 0 122,00 0 122,00 0

3.1 0 5 4 LO S ANGELE S

1,56 0 2,60 0 5,63 0 5,79 0 8,90 0 16,30 0 230,00 0 305,00 0 305,00 0

2.8 9 70 1 PHILADELPHI A

4 3 39 8 82 2 2,81 0 6,38 0 11,30 0 22,80 0 30,70 0 34,30 0 35,30 0 35,40 0 58,40 0 116.00 0 116.00 0

3.7 5 1 5 S T LOUI S 1

11 9 | 33 1 | 1.24 0 1 4,16 0 1 9,51 0 I 15,70 0 I 21,60 0 I 23,00 0 I 28,70 0 I 43,90 0 1 47,50 0 1

3.1 6 1 5 1



### 7-2 7P.3 9



### TABL E 7-27
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WHOS E MAXIMUM COHbLEVE L OCCUR S INSELECTE D RANGE S ASSUMING 1 5 PPM/ 1 EXE XSTANDARD I S ATTAINE D

1 COH

B LEVE L 1 1 1 1 1 1 RANG

E 1 CHICAG O1 LOS ANGELE S 1 PHILADELPHI A 1 S T LOUI S 1 1 (PERCENT ) 1 I I I I

1 3.7 0 < C < = 10.0 0 1 1 I 4 4 1 I 1 3.5 0 < C < s 3.7 0 1 I I 35 6 1 1 1 3.3 0 < C < = 3.5 0 1 I I 42 3 1 ' 1 1 3.1 0 < C < = 3.3 0 1 6 7 1 I 1,98 0 1 12 0 1 1 3.0 0 < C < = 3.1 0 1 1 5 1 I 3,57 0 1 21 2 1 1 2.9 0 < C < = 3.0 0 1 72 0 I 1,56 0 1 4,88 0 1 90 9 1 1 2.7 0 < C < = 2.9 0 1 1,59 0 1 1,04 0 1 11,50 0 1 2,92 0 1 1 2.5 0 < C < = 2.7 0 1 1,81 0 1 3,03 0 1 7,87 0 1 5,35 0 1 1 2.3 0 < C < = 2.5 0 I 4,97 0 1 16 1 1 3,64 0 1 6,16 0 1 1 2.1 0 < C < = 2.3 0 1 10,90 0 1 3,11 0 1 98 1 1 5,93 0 1 1 2.0 0 < C < = 2.1 0 1 12,40 0 1 7,36 0 1 13 2 1 1,40 0 1 1 1.5 0 < C < = 2.0 0 1 52,80 0 1 214,00 0 1 23,00 0 1 5,73 0 1 1 1.0 0 < C < = 1.5 0 1 36,20 0 1 74,70 0 1 57,90 0 1 15,20 0 1 1 0.0 0 < C < = 1.0 0 1 7 0 1 63 9 1 1 3,59 0 1

1 MAX . COH

B CONC . 1 3.1 0 1 2.8 9 1 3.7 5 1 3.1 6 1 1 PEOPL E A T MAXIMU

M 1 5 4 1 70 1 1 1 5 1 5 1



### 7-2 8 

# JP.4 0



### "best-estimate " microenvironmen t factor s develope d i n Sectio n 6 wer e use d t o simulat e the contributio n o f ga s stove s an d smoking t o tota l C O exposure . 7.1. 1 Attainmen t o f 9 ppm/ 1 ExE xStandard NE Mestimate s i n Table s 7- 1 through7- 9 wer e develope d b y adjusting the ai r qualit ydat a fo r eac hstud yare a using the roll-bac k formul a describe d i n Sectio n 5. 1 s o tha t the mos t pol

lute d neighborhoo d typ e jus t meet s a " 9 ppm/ 1 ExEx " standard , i.e. , on e specifying tha t the expecte d numbe r o f 8-hour C O value s exceeding 9 ppmshal l no t b e greate r than on e pe r year . Tabl e 7- 1 provide s estimate s o f the numbe r o f occurrence s fo r adult s wit hcardiovascula r diseas e o f 1-hour exposure s t o C O concentra

tion s exceeding selecte d values
. (Exposure s exactl yequa l t o zer o ar e counte d a s exceeding zero. ) Thus , eac hcolum n i n Tabl e 7- 1 present s a cumulativ e frequencydistributio n i n whic hthe numbe r o f 1-hour exposure s increase s a s C O concentratio n decreases ; the distributio n reache s a maximu ma t a C O concentratio n o f zero . Thi s maximu

m i s the numbe r o f adult s wit hcardiovascula r diseas e use d i n the simulatio n time s the numbe r o f possibl e occurrence s i n a yea r (8760)
. AlthoughNE Myield s individua l frequencydistri

bution s fo r cohort s wh o ar e a t low , medium , an d highactivit ylev

el s whe n a give n C O concentratio n i s encountered , onl ythe tota l frequencydistributio n fo r al l activit ylevel s i s presente d i n Tabl e 7-1
. According t o thes e estimates , non e o f the four stud y area s woul d hav e mor e than 6,91 0 occurrence s o f 1-hou r C O expo sure s abov e 2 5 ppmi f a 9 ppm/ 1 ExE xstandard wer e jus t attained
. Tabl e 7- 2 use s an alternativ e exposur e indicator , adult s wit h cardiovascula r diseas e wit h1-hour exposures . Thi s i s the numbe r o f adult s wit hcardiovascula r diseas e i n the stud yare a tha t experienc e on e o r mor e 1-hour exposure s pe r yea r t o C O concentra

tion s tha t excee d a specifie d value
. Thi s exposur e indicato r i s als o expresse d a s a cumulativ e frequencydistribution
. The numbe r o f adult s wit hcardiovascula r diseas e expose d a t zer o concentra

tio n (o r above ) i s the tota l populatio n o f the stud yarea . 7-2 9P 1 0 0 1

- J ll >

* < rt> p H 0 ) • t o

c n p 3 o fl) el - s ' fl) ( D X 1 3 o ( 0 d

- J h 1 fl) U ) o fl) ( 0 r t p 3 P c + fl) C O P H fl)
H » O n P O J d M r t ( 0 S p - r t tr r t p O 3 W X 

### § P 3 0 ) r t P O 3 C O d H < fl) *< ^ ^ 2 5 G 2 J w C O ^- ^ M l o H P O i d P * r t 3 (i ) P * (D 0 ) p 3 O i H i fl) 3 P P 1 fl) ( 0 Pged H t r fl) ( A fl) P H ( D
r t t r fl) 3 i f 0 ) 3 < J P M c fl) U ) H i o 

## B a p 3 a M 

### s (/ ) 2 5 P f t P o 3 0 ) M K fl) 0 ) P - r t t r P 3 a 2 5utri- i Q \ M o o 3 P 1 H i O H P O i P P * r t H i fl) 3 O J P " fl) ( A 0 ) 3 O i P » O l •

- J i Q \ P » O O 3 P 1 H i 0 H 0 > o . d M r t 3 0 > P 1 I D ( 0 • H I 3 * ( D < P ) P " P fl) d 1 0 ( D O i H i O M
r t tr fl) 3 * ( D 3 0 if l M O t r p 3

T-> fl) < fl) M p 3
r t tr fl) c r P - o 0 a p - C O M3.8 K> P 1 0 0 p i C O C U t r fl> ( 0 r t fl) ( 0 r t p 3 P r t fl) • r t p - H i p O > O i < P - C Q 0 H *< O 0 g g P - r t r t fl) fl)

_ O > C O > r > • — o o C O d t r o o g g p - r t r t fl) rt) 3 * P L 0 H fl) O o 9 g fl) 3 O i fl) O J r t o t o U l o 3 * P > <! fl) c r ro ro 3 H fl) T J O K r t fl) O i p 3
r t t r fl) P » P - r t fl) H 0 > r t d » i fl> •
H tr n > o M fl) P 3 > p n C O o p fl) 3 o o 3 fl) C O H ) H o 3 r t 3 * fl)
c o r t d O J * < t r
• < » o o -
* • fl>
• < * • fl> r t P p < • M
< ft) P 1 d n > C O i i ft> 3 m P 3 if l H i H O 3 K ) O C

O fl) 0 f t p - •-3 0 3 * 3 fl)

- J < • ft)
. u P 1 • d m d C O n > O i H i o h r t 3 - fl) W P > P 1 a ft) 3 fl) O O 3 ( 0 r t P i 3 r t p - ( A
r o p « 0 0 •

H 3 3 * P - C O < ft) P 1 d (D P

P 1 r t fl> H 3 P r t p - < fl) < P P « d fl> ( 0 H ) o H C O O 3 fl) O H i
r t tr fl> 0 ) ( P < P M p p c r P - fl> C O p K fl) a P - C O o d ( 0 ( A (D 0 . P 3 P 3 P P - ^ < ( A P - C Q H d 3 ( A fl) X T J P 1 O i i p - 3 u q r t & r n > p 3 T J P o r t o 3 fl) X T J o ( A d i i fl) fl) ( A r t p 3 P r t fl) (A O H i d ( A p 3 o H i
r t t r fl) i i n > P ( A o 3 ( A H i O H r t tr fl) ( A fl> n 3 - o p o fl) ( A P - ( A
u 3 P - < fl) 3 c r fl) P - o « : • C O fl) 3 C A P - r t p - < p - r t *< r t tr fl) ( A fl) < J p p « d fl) C Q p - ( A T J i i o < p - O J fl) o . p 3 P 3 W • O > 3 fl) 3 0 H P 3 O J rt § • »- - > c r i i p . fl) H i C A g § g P i i ~ j 1 N > t o • ^ d P « P « O i 0 o p g fl) 3 r t P r t P O 3 O H i
r t t r fl) H P r t P o 3 P H 1 fl) H i O i i
r t 3 * fl) O 3 * o P O fl) o H i P C A ( A P - U 3 3 fl) O i
r t o r t 3 * fl) < P H
. p P o r P - r o ( A P 3
r t 3 * fl> P M * o O i i p - r t & • g P I i fl) M P - ( A r t fl) O J p 3 H P t r P - r o 3 P r t fl> n o a t r p- 1 r o < A ) P * ( A P 3
r t t r fl> fl> X T J O C Q fl) O i T J 0 T J d p - P r t p O 3 C O • C O TJ fl) O p - H l P O < P H d fl> ( A •^ P er M rt"

~ j i N i C O P " P - C O r t ( A
r t tr fl) iQ fl) 3 (D h P P 1 P P " uQ O • i P - r t % P ( A fl) O i t r ^ < 2 5 M 3 ; r t O fl) ( A r t P 1 P - 3

•- 3 P t r p « n >

•~ 4 1 M • P - 3
r- 3 P t r P fl)

- J 1 4 * ^ o o 3 T J P 1 1 fl) o . c p - r t tr O J ^ o C O o ^ o o o M 1 3 " o d H p < fl) 1 1 p i Q C D fl) X T J O ( A d H ( D C Q 3 C 

### p 5 * fl> n o H i C O 1 tr o d h M r j 3 3 P - 3 v O P < fl) 1 1 P i Q (D fl) X T J o ( A d i i fl> ( A P t r 0 < n > v o T J T J 3 P - C Q P > O ^ J

^ 1000 p « 1 3 * o d h o o 3 o fl> 3 r t H P r t p o 3 P - C Q t o U l • as T J T J 3

_ * H P t r p - t o

« j i p « ^. ^

. C O p 3 p M P H P 1 ^ < ^
r t tr fl) fl> X T J fl) H P - fl) 3 O fl) O J P 3 n 3 * P o p i Q O P - C Q P - t o • o T J T J 3

. . t-3 P t r P - rt)

~ j i *«
. *-* ^ C 3 * P M rt)
r t tr m 3 P X p -mum ^ o i i ro X p 3 T J p * fl) ^ r t 3 * fl) 3 P X p 3 g 0 0 1 3 * O d i i H d 3 3 P - 3 i Q P < fl) h P i Q fl) O O 3 O fl) 3 r t H P r t P o 3 O o 3 O fl) 3 ti - l l P f t P O 3 C Q H i O 1 1 0 0 1 tr o P n n d 3 3 p - 3 u a P < fl> n p *f l fl) ( A f t tr P 3 H i o i i M i 3 * O d n p < J fl)rages < P P * d fl> p 3
r t 3 * fl) ( A fl) H P - fl) C O « % T J o P « P 1 d r t P 3 r t fl) X T 3 O (A d n o > ( A d ( A d p M M ^ < o o o p i i p r t M O £ fl) H
. C Q P - < fl) 3 * O d H p - ^ < o o 3 O fl) 3 f t H P f t P o 3 ( A P - ( A P * fl) C O C Q
r t tr p 3 o h fl) • O d p p - r t o r t 3 " rt) 3 * p i Q 3 * fl> C Q r t P < fl) M p i Q fl) n o o o 3 o fl) 3 r t h P r t p o 3 C O •
t o fl) o p d C Q fl)
r t t r fl) p < 1 fl> M P u q n > o H i P 3 * < 0 0 ( A d o o r o ( A 1 ( D X o fl) T J ri - f t tr P r t ( 0 X T J O C Q d H fl) C Q P h fl) fl) C Q f t P 3 P f t fl) O i p 3
r t fl) H 3 C Q o H i 0 0 1 t r o d n H d 3 3 P - 3 u 3 i-3 P c r M rt) C Q

- 4 1 •!> f t tr i i o d u a 3 *

- j i as P h fl> C O p 3 p - P 1 P i i
r t O
r- 3 P c r P 1 fl) C Q

- J 1 P 1
r t 3 - n o d i Q t r7-3 I Q P 3 i « P 1 fl) P 3 r t ( P H < P P * • fl) ( A r t p 3 P r t fl) ( A P H fl) 3 O f t O g g d P * P r t P - < 5 fl) ** • fl) P O tr T J m P * r fl) X T J o ( A d n fl) H i P P 1 P " C Q < P - r t t r p 3 P L< fl) P n t p - r t t r p 3 C O fl) p * rt) o f t fl) O i p 3 f t fl) h < P P 4 C Q o H i P 1 1 t r o d n n o o o 3 o r o 3 r t H P f t p o 3 ( A •
H 3hese o P n O i p o < p C Q o d P » P h O i p - C Q fl) P C Q fl) £ t r o fl> X T > rt) H P - fl) 3 O fl)
r t tr fl) p h T J fl) P * * fl) X T J o ( A d i i c o o H i
r t 3 " fl) n 3 P t r p - n >

^ j i U l T J H O < P - O i (D C Q rt) C A r t p 3 P r t fl) C Q O H i
r t tr rt) 3 c g 3 * fl) n o H i p O J P P 1 r t C Q € p - r t t rP.4 2

TABL E 7-28 . ALGORITHM USE DTOCALCULAT E CARBOXYHEMOGLOBI N I N BLOODO F COHORT S 1 . Give nthe altitude , calculat e averag e barometri c pressur e (P g ) :

P B= 760*exp(-0.0000386*Alt ) 2 . Calculat e capillary oxyge npressur e (P c 0 2 ) : p c 0 2 = 0.209*(P B -47 ) - 46. 9 3 . Calculat e quantit y B : B= (1/D L ) + (P B-47)/V A 4 . Le t (%0 2 Hb ) = 10 0 5 . Calculat e quantit y A : A = p c 0 2 /(M*(%0 2 Hb) ) 6 . Calculat e quantit y F : F = exp(-t*A*60*10 4 /(1.38*Hb*Vb*B) ) 7 . Calculat e tria l (%C0Hb ) value :

(%C0Hb ) = (%C0Hb) Q * F + (B*V C Q+ (Pg-47)*10" 6 *(C0))*(1-F)/ A 8 . Calculat e (%0 2 Hb ) valu e fo r nex t iteration :

New (%0 2 Hb ) = I00*(«0 2 Hb)/((%0 2 Hb ) + (%C0Hb) ) 9 . Startingwit hthe new valu e o f (%0 2 Hb ) repea t Step s 5 through8 . Com par e the (%C0Hb ) calculate dwit htha t fro m the previou s iteration . Repea t cycl e unti l tw o successive COHbvalue s agre e withi nthe desire d accuracy .

7-3 1P.4 3

TABL E 7-29
. VALUE S ASSIGNE D TO VARIABLE S I NALGORITHM USE D T O ESTIMAT E CARBOXYHEMOGLOBI N Variabl e Haldan e constan t Hemoglobi n concentratio n Endogenou s C

O productio n rat e Altitud e C O diffusio n rat e
Bloo d volum e Ventilatio n rat e Category Al l Females Males Females Male s Al l Females Male s Females Male s Lo wexercis e Mediu m exercis e Hig h exercis e Valu e 218. 0 13. 8 grams/10 0 m l 15. 7 grams/10 0 m l 0.006 2 ml/mi n 0.008 1 ml/mi n 0 3 1 ml/min/tor r 3 4 ml/min/tor r 4,80 0 m l 5,80 0 m l 8,00 0 ml/mi n 20,00 0 ml/mi n 35,00 0 ml/mi n

7-3 2P.4 4



### cardiovascula r disease , value s wer e no t develope d fo r the two age / occupatio n group s consisting o f children
. Th e valu e use d fo r th e endogenou s C O productio n rat e (V rf 

### J i s 0.008 1 ml/mi n fo r adul t male s an d 0.006 2 ml/mi n fo r adul t females
. Thes e value s ar e simpl e weighte d (b ythe numbe r o f sub

jects ) average s o f th e result s o f si xstudie s fo r males'*" 9 

### an d four studie s fo r females 5- 8 

### reporte d i n the literature
. The valu e use d fo r the C O diffusio n rat e i n the lun g i s 3 4 m l (min«m

m Hg ) fo r adul t male s an d 3 1 m l (min'm

mKg ) fo r adul t females
. Thes e value s ar e take n fro mJoumard , e t al. 1 0 

### Th e value s use d fo r bloo d volume ar e 5,80 0 m l fo r adul t male s an d 4,80 0 m l fo r adul t females
. Eac ho f thes e value s wa s calcu

late d b ymultiplying two othe r values : the 7 4 ml/kg bod yweigh t fo r averag e male s an d 7 3 ml/k g bod

yweigh t fo r averag e female s reporte d b

ySjostrand 1 1 

### multiplie d b y7 8 k g averag e weigh t fo r adul t male s an

d 6 5 kg averag e weigh t fo r females , respectively
. Th e latte r two value s ar e base d o n dat a provide d b ya publicatio n o f the U.S . Nationa l Cente r fo r Healt hStatistics. 1 2 

### Ventilatio n rate s use d fo r bot hadul t male s an d adul t female s ar e 8 liters/mi n fo r a lowexercis e level , 2 0 liters/mi n fo r a mediu mexercis e level , an d 3 5 liters/mi n fo r a highexercis e level
. Th e basi s fo r thes e value s i s a stud yb yNiinimaa , e t al. 1 3 

### Th e lowexercis e leve l valu e represent s sleeping an d sitting , the mediu mexercis e leve l valu e represent s walking an d othe r ligh t form s o f exercise , an d the highexercis e leve l valu e represent s form s o f exercis e mor e strenuou s than walking
. Obviousl ythes e thre e categorie s represen t a partitioning o f a continuu mo f exer cis e level s (se e Tabl e A- l o f the Offic e o f Ai r Qualit yPlanning an d Standard s Staf f Pape r o n Sulfu r Oxides 11 

### *)
. I n essence , the algorith mpresente d i n Tabl e 7-2 8 estimate s the COH blevel s o f an individua l a t the en d o f ever

yhou r o f the year . AlthoughCOH blevel s are , strictl yspeaking , the resul t o f C O exposure , theycan b e describe d using concept s simila r t o thos e use d fo r C O exposure . Fo r example , Tabl e 7- 7 list s the

7-3 3p 1 1 fl) TJ 1 1 o i_i
. fl) O f t fl) O i r t o P 1 vo 0 0

- j t r ^ d C Q p 3 i d

- J 1 f t O J tr *
. fl> 3 d P " r t p - T J P * P o p f t p - < fl) H i P o r t o • 1 P » • P> v o U l • r- 3 t r fl) fl) C Q r t p 3 P r t fl> C Q d C Q fl) P 1 V O

- 4 o o fl) 3 C Q d ( A O i p r t P H i o H el - s ' fl) H i o d n o p - r t p fl) ( A t r d r t p 3 0 r t tr fl) h s : P C O 3 0 f t • P v Q fl) t r n fl> P * * O i o $ j 3 < - P 1 1 P fl) ( A P 3
v Q fl) 3 fl) H P P * H i n 0 3 O 3 fl) P i Q fl) \ O O o d • o p r t p o 3 v O H O d T ) r t O H i o H P 3 f t t r fl> o P p o d P > P r t p o 3 ^ t r d r t r t t r n ) H i P O r t r t t r P r t r t tr fl> 3 P P " fl) \ H i fl) 3 P P " fl) TJ fl) H Oent- 3 P H fl) >- ^

.

• 3 tr ( D H i p o r t r t 3 * P r t 3 P i i i i p - fl) O i s : 0 3 fl) 3 P H fl) P P * H H i rt) 3 P P * fl> S P C Q P o 0 o d 3 r t fl) O i 3 P H fl) P 3 O i H i fl) 3 P p fl) p 3 fl) P O 3 * 0 H i r t tr fl) H i 0 d h o p - r t p fl) ( A

.— . c n t o d P H i fl) 3 P P 1 fl) P 3 O i

• o 0 0 <* P O o 3 UJ
. P 3 O f t P o 3 5 5 p - r t 3 * fl) C Q r t p 3 P r t fl> C O O H i r t t r fl> T J fl) 1 1 o fl) 3 f t P u 3 fl) C O 0 H i P O i d P " r t ( A € t r 0 P i i n > fl) C O r t p 3 P r t ( D C O H i o H O P h O J P o < p C Q o d P 1 P • i P O J d p * r t C Q t r ^ d ( A P 3 i Q el - s ' fl) ( A fl) f t * ! 0 < P P " d fl> ( A p 3 2 5 W 

### s H ( D C O r t P 3 P r t fl) ( A H i 0 H f t t r fl> * tr 0 H fl> T J 0 T J d p " P r t p 0 3 S fl) H fl) n p f t p 0 ( D o . O i o ^ 3 r t o r t tr fl) 03 fl) P P 1 r r 3 * ^ M O i d o p f t p o 3 < » P 3 d 33 fl) P » H i P H fl) 0 - P f t P • »- • U l
H 3 r t t r p - C Q p TJ TJ P 1 P - o p r t p O 3 0 H i p O i P M r t 3 P M fl) C Q L n • 0 0 <* P

.
l ^ tr fl> ( 0 fl> < P p d n > C O P H fl) t r P ( A (t > O i o 3 a • U ) • a fl> TJ P n 

# s fl) 3 r t o H i o H i P C L d M f t H i fl) 3 P P * fl) C O 

### s p - r t t r o P H o . p o < P C O o d p » P n 0 - p - C Q fl) P C Q fl) * P ( 0
* » • to dP P 3 O i H i o H P H fl) H i 0 H O P 1 1 O i P 0 < P C O o d *-> P n P O i d H r t C Q • H t r fl> < p M d rt) C Q d C O n > O J H i O H f t t r fl) TJ fl> n o fl) 3tage > ( A TJ H fl) < P - O d C O p « *< 3 0 r t fl) 0 . > r t t r fl) fl) ( 0 r t p 3 P r t fl) ( A TJ H fl) C Q fl) 3 r t rt> O J p 3 r t t r fl) r t P t r t-> ( D C Q H i 0 1 1 T ) t r p H p O i fl) P 1 T J t r p P ^ P 3 O i r o • o M TJ fl) H O fl) 3 r t
H i O n C O r t « f 0 d p - C Q • TJ C D 1 1 O fl) 3 r t H i o i i n t r p o P v Q 0 ^ P - • 0 0

- ~ j T ) rt) H O fl) 3 r t H i 0 i i tr> 0 C Q 

## S v Q fl) P » fl) C Q ^ t o t c o P « T J fl) H O fl) 3 r r O O w t r H fl) <! fl) P « C Q fl) X O fl) fl) O i p 3 U 3 r o • o o TJ fl) n o c o 3 r t • £ P X P - 3 g n o s t r M c o < A ) M C Q P n fl>
p i • VO r o r t 3 * fl) T J tr p M P O i fl) P » TJ 3 * P P P O J d r-> Ct C Q « P - f t 3 * O P h O i P O < P C Q O d p « P n O i p - C O ro P C O fl) fl) T 1 fl) n p fl) 3 o fl) d 3 O i fl) H r t 3 * fl) v o T J TJ 3 \ P * W N t d X ( A r t P 3 O i P i i 0 . *
> TJ TJ n 0 X p - 3 P r t fl) p * *< M • • O T J fl) M O fl) 3 r t o H i O P n O i p 0 < P C O o d P > P n o < p - ( A fl) P C Q fl) K p - r t 3 " O O W t r *-> ( D < rt) P * C O fl) X o fl) fl) O i p 3 uQ C O • o TJ fl) n o n > 3 r t H P t r P « r p

» j i c o o C Q t r o S C Q r t t r P r t 3 O 3 fl) O H i r t t r fl> C O r t d O i » < P i i fl> P C O tr P < fl> P O i d M r t C A *, p el - s ' P O i d M r t ( A t. p - f t 3 * o p H O i P o < p C A O d T-> P H O i P - C O fl) P C O fl) p 3 r t t r fl) C O r t d O i ^ < p n C D P TJ o TJ d P 1 p r t P O 3 • 0 - P - H i H i rt) n fl) 3 r t O O 3 3 t r P 1 ( D < fl> P 1 ( A r t O r t t r fl) o o n n fl) ( A TJ o 3 O i p 3 v Q TJ fl) 1 1 O fl) 3 r t P v Q fl) O H i r t O r t P p * r t t r rt) fl) C O r t p 3 P r t fl) C A O H i P O i d T~> ct C O £ p - r t 3 * o p n O i p o < P ( A o d p « P n O i p - C O fl) P C O fl) fl) X TJ fl) H P rt) 3 O P 3 C Q r t d O i K ; P n ( D P ( A o P 3 t r rt> o o 3 TJ P H fl) O i t r *< 3 O H g P P - p - N P f t P 0 3 ^ P - • rt) • ^ t r • < o o 3 < fl) H fl -ing H t r ( D n rt> P P r t p - < r o H i n I D u Q p fl> 3 o p fl) C Q o H i t r p - v Q t r n o ta t r P « ro < t o p » C O p 3 O 3 uO
. f t 3 * ( D H i O d n P - ct 3 P - r t< fl) fl) i i < O i P P - P 1 C O c o ri - l l p - t r d r t p o 3 C O ^ C t r p M fl> n 3 P t r \-> ( D

- J 1 v o P « P - C A il - e a H rt) C Q d p « r t c o p 3 O i P - C O O H fl) r t fl) < P H 1 d fl) ( A •
> C A € O P P> O J t r fl> n > X TJ fl) O f t rt> O i ^ r- 3 P t r p > fl) C Q

~ J 1

- J p 3 O J

-- J 1 0 0 T J H fl) C Q fl) 3 f t O g g d P 1 P I fl) X TJ fl) 1 1 P fl) 3 O fl) r t 3 - fl) P n tr p - v Q t r fl) C O r t n O a t r M fl) < fl) M ^ P - r t tr p 3 C Q C D P " fl) o f t fl) O i n p 3 m ( D C Q o H iCOHb • ^ j i V O
r-> P - C Q ci - c o r t tr fl) 3 g g J5 * fl> n o H i P a d p * fl - e a £ p - r t S ' O P n o . p o < p C O o d p * P i i O i p - C O fl) p C Q fl) K tr O ct tr P r t rt> X TJ fl) H P - fl) 3 O ( D O O W t r p < ( D < rt> P « C O t. tr p a tr c o X o fl) fl) O i C Q rt) M rt) O f t rt> O i < p M d fl) c a •

•^ P t r P 1 fl> ^3 P t r M rt)

^ J 1 0 0 P * P - ( A f t ( A f t t r fl) 3 g g 5* fl) H o H i P O i d P 1 f l - e a S P - r t tr o P n O J p o < ; P C O o d M p H
. O i P - ( A ( D P ( A fl) 3 c g o* rt) H o H i o O O d H H fl) 3 O fl) C O o H i O o a tr P fl> < fl> P - C O r t t r P r t fl) X o fl) fl) o . C Q fl) P " rt) o r t fl) O i < P P 1 d fl) e o •P.4 6



### TABL E 7-30
. PERCENTAG E O F ADULT S WIT H CARDIOVASCULA RDISEAS E EXPERIENCING COHbLEVEL S EXCEEDIN

GSELECTE D VALUE S ASSUMING 9 PPM/ 1 EXE XSTANDARD I S ATTAINE D
COHbleve l exceede d (percent ) 3.0 0 2.9 0 2.8 0 2.7 0 2.6 0 2.5 0 2.4 0 2.3 0 2.1 0 2.0 0 1.5 0 1.0 0 0.0 0
Max . COHb cone . Percen t a t maximu

m Chicag o

7.9 3 81.1 5 100.0 0

1.9 2
0.0 4 Lo s Angele s

1.9 0 82.9 5 100.0 0

1.8 7 0.2 3 Philadelphi a

0.0 3 0.5 9 2.3 5 29.5 7 74.3 1 100.0 0

2.3 1
0.0 1 St . Loui s

0.0 4 33.0 5 71.5 8 100.0 0

2.0 2
0.0 1



### 7-3 5I CO as H i

o n r t t r n > VO T J T J 3 \ P « w X w X o p C O fl) • c o •
•~ J c n T J fl) H O fl) 3 f t ^ O 0 3 T J P H fl) O i « P - f t 3 " P 3 P X P - 3 g O H i
r o • c o P * T J rt) H O fl) 3 f t fl) ( A r t p 3 P r t fl) 0 . fl) X o fl) fl) O i r o • 0 0 VO T J fl) n o (D 3 e + • TJ 3 * P - P 1 P O i fl) P 1 T J t r P P 3 * P C Q P 3 P X p - 3 g O O 3 3 c r P * n > < n > P * o H i C Q r t P 3 O J P h a C Q • > p - p * H i o d n C O r t d O i >< P H rt) P ( A t r P < rt) o o 3 3 c r P 1 n > < ro P * ( A K tr p o 3 " n > nQ d p p " o 1 1 T J T J 3 \ P * w X w X C A f t p 3 O J P i i O J r t 3 * P 3 d 3 O J fl) n r t t r rt)
P 1 r o T J * 2 3 \ p " w X w X p 3 O i
v o T J T J 3 \ p *
r d X w X p - 3

• 3 P t r p * rt>
-o . 1 C O r o • > ( A C D X T J rt) O f t C D O J ^ n o 3 3 t r P 1 rt> < n > p - C O p n (D t r p - v Q 3 * rt) h d 3 O i rt) n r t 3 * rt)
T-> c n P
. 3 P P 1 * < N fl) O i • z 0 

## 3 p H p - N fl) O i o o 3 3 t r fl) C O r t P 3 P r t (D e o H i O n r t t r p - ( A
e o r t P 3 O i P H O i P H fl) P * p - C Qted T J T J 3 \ P » M X w X 3 C A f t p 3 O i P H O i P - e o el - s ' fl) P 1 rt) P C Q r t ( A r t n p 3 v Q fl) 3 r t o H i el - s ' fl)
r t 3 * H rt) fl) C Q r t P 3 O iards < P p * d fD C Q fl) X o c o n > 0 - p 3 v Q P " c n T J T J 3 (A 3 * P H p * 3 o r t fl) X o (D fl) O i O 3 fl) T J fl) n ^ < fl) p h •

»- 3 3 * fl)
5 P " c n 3 fl) fl) r t P ( A f t P 3 O i P H O i C O T J fl) O P - H i * < P 3 v Q el - s ' P f t f t t r fl) fl) X T J fl) O r t fl) O i 3 c g t r (D h o H i 0 0 I tr o P n n o P C O C O p g T J f t P O 3 f t t r P r t
r t t r (D 3 o ( A f t T J O P " P « d r t fl) O i 3 fl) P - v Q 3 " t r o 1 1 3 * O o a r t *< T J fl) < P - P * P « C J
. d C O r t 2 3 M £ fl) C O r t p 3 P r t (D ( A p 3

•-3 P c r p < (D ( A

^ j i M v o f t t r H o d v Q 3 *

^ 1 1 r o -o . P h rt) t r P (A n > o . o 3
r t t r (D - j • P * • C J
> r t r t P p - 3 g rt) 3 r t O H i P « c n TJ TJ 3 \ P « M X w X c n r t P 3 O i P H o . r t tr fl) 3 P X p - 3 g o o 3 3 c r H n > < fl> P « p 3 T 1 tr p M P O i rt> P > T J t r p P p - ( A
c o • o c o T J (D n o ro 3 f t • P 1 fl) < (D M C O « t r p o t r r o i O d P p o h fl> X o fl) fl) O i
r o • c o 0 0 T J rt) n o fl> 3 r t p 3 a rt) 1 1
r t t r p - e o P e o e o d 3 T J r t p O 3 M X w X ( A r t P 3 o . P h O i • 2 3 O r t C D
r t t r P r t P p « P * ( A r t d O J ^< P h fl> P C O tr p < fl> 3 P X p - 3

• 3 n o 3 3 t r t-3 P t r P < (D

~ j i C O p « T J n o < p - O J fl) C O 3 o 

## y p p « p N fl) O i o o 3 3 t r fl> C A r t p 3 P r t fl) ( A H i o n r t 3 " fl) M r o T J T J 3 \ p « fl) C O r t p 3 P r t rt) ( A ^ « P 3 O i H P c r P « fD C Q

^ 4 1 P 1 c n r t 3 * H o d v Q 3 * -o . l P « 0 0 T J n o < J p - O i fl) o o 3 3 t r ( D ( A r t p 3 P r t fl) ( A • fl) C Q r t p 3 P r t fl> ( A ^ » i-3 P c r P - fl> ( A

^ j i P 1 c o r t t r h o d v O 3 "

> J 1 P * C n T J n o < p - O i fl) 0 0 1 3 * o d 1 1 fl) X T J o C A d H (D w X w X C O r t p 3 O i p H
. O i •

H 3 P c r P « ( D C O

^ J 1 p " o el - s ' H O d i Q t r

^ 4 1 M r o T J n o < p - O J (D P 1 1 t r o d n fl> X T J 0 ( A d n fl> n 3 * p - c o s P 1 r o T J T J 3 \ P * M X w X3 e o r t P 3 O J P h o . p - ( A P 1 fl) C O (A (A f t h P - 3 u 3 fl) 3 f t
r t 3 * P 3
r t 3 * ( D
v o T J T J 3 P " 0 0 1 tr o p n o o < p p « d (D ( A (D X o fD fl) O i P 3 v O P * K ) T J T J 3 e o 3 - P M P « 3 o r t (D X o rt) rt) O i o 3 rt) T J fl) n ^ < rt) p 1 1 • p n fl> P C J
. d C O r t 3 fl) fl) fl - e a P C O r t P 3 O J P H O i C O T J fl) O P - H i ^ < P 3 v Q
r t 3 * P r t el - s ' (D (D X T J fl) O r t fl) O i 3 g 5 * fl) H O H i P (A C O C g T J r t p o 3
r t 3 * P r t el - s ' rt) 3 o ( A r t T J o P - P 1 d r t ( D O i 3 fl) P - v Q t r t r o n t r o o O i
r t * < T J ( D p 3 fl) p o 3 " C O r tudy • 3 P c r t-> ( D C O

~ j i P < o r t S * n o d v Q t r

- j i M 0 0 T J n o < 3 P - O i rt) 2 S 2 fl) ( A r t p 3 P r t rt) C O c r P C O C D O i O 3 el - s ' fl) ^ J • M • r o
> r t r t P p - p g rt) 3 r t o H i P 1 f> J T J T J 3 \ P * W X M X c n r t P S a P h O - M 3

P M f t P 1 fl) 4> . M K X fl) P * 4 3 d o P

- O P « r o r t O ^^ P > • o M »— »
« j P 3 O i P 1 • P 1 v o c n P - e a P T J T J H o X P 3 P r t fl) P 1 * < rt) i Q d P P > r t o v Q H o S r t 3 * rt) P O tr *< fl> P n H i i i o 3 M V O 0 0 o f t o p * v o 0 0 « J • n 3 * P r t P - ( A ^ P " • o

~ J r o p - ( A P T J T J H o X P - 1 P 3 O J P " • o

- 4 t o

• » P
v Q n o £ r t s * H i P O f t o H O o H n < D e o T J o 3 O i P 3 UJ
. r t o P T J H
. o C J
. fl) O r t rt) O i p > T J fl) 1 1 Oent i i P r t p O o H i
p i v o 0 0 o r t o r t P P 1 a • c n • T J o T J d t-> P f t P o 3
r t o M V O

- o o f t o r t P P - a • c n • T J o T J d M P r t,ion, i-3 tr rt)
P * • P « v o c n 3 d T-' ct P - T J M P - O P r t p - < fl) H i P O r t O M P - ( A
r t t r rt) T J n o O i d o r t o H i P > • P " M c n ^
r t 3 * fl)P.4 8



### TABL E 7-31 . PERCENTAGE OF ADULT S WITHCARDIOVASCULA RDISEAS E EXPERIENCIN

G COH bLEVEL S EXCEEDIN

GSELECTEDVALUE S ASSUMIN G 1 2 PPM/ 1 EXE

XSTANDAR

DI S ATTAINED
COH bleve l exceede d (percent ) 3.0 0 2.9 0 2.7 0 2.5 0 2.3 0 2.1 0 2.0 0 1.5 0 1.0 0 0.0 0

Max . COH

b cone . Percen t a t maximu

m Chicag o

0.0 6 1.0 2 3.0 9 7.3 0 49.1 8 98.3 6 100.0 0

2.5 2
0.0 2 Lo s Angele s

0.8 1 1.6 7 1.9 0 21.4 4 98.3 6 100.0 0

2.3 8
0.5 1 Philadelphi a

0.0 3 0.1 3 0.6 7 4.0 3 14.7 4 25.3 4 27.6 7 31.7 2 98.2 8 100.0 0

3.0 3
0.0 1 St . Loui s

0.3 9 5.8 5 15.7 9 26.5 3 51.1 6 90.7 4 100.0 0

2.5 9
0.0 1



### 7-3 7

### TABL E 7-32
. PERCENTAG E O F ADULT S WITHCARDIOVASCULA RDISEAS E EXPERIENCING COHbLEVEL S EXCEEDINGSELECTE D VALUE S ASSUMING 1 5 PPM/ 1 EXE XSTANDARD I S ATTAINE D
COHbleve l exceede d (percent ) 3.7 0 3.5 0 3.3. 0 3.1 0 3.0 0 2.9 0 2.7 0 2.5 0 2.3 0 2.1 0 2.0 0 1.5 0 1.0 0 0.0 0
Max . COHb cone . Percen t a t maximu

m Chicag o

0.0 5 0.0 7 0.6 6 1.9 6 3.4 4 7.5 2 16.4 8 26.6 4 69.9 2 100.0 0 100.0 0

3.1 0 0.0 4 Lo s Angele s

0.5 1 0.8 5 1.85
. 1.9 0 2.9 2 5.3 4 75.4 1 100.0 0 100.0 0

2.8 9 0.2 3 Philadelphi a

0.0 4 0.3 4 0.7 1 2.4 2 5.5 0 9.7 4 19.6 6 26.4 7 29.5 7 30.4 3 30.5 2 50.3 4 100.0 0 100.0 0

3.7 5 0.0 1 St . Loui s

0.2 5 0.7 0 2.6 1 8.7 6 20.0 2 33.0 5 45.4 7 48.4 2 60.4 2 92.4 2 100.0 0

3.1 6 0.0 1



### 7-3 8- J

1 CO VO O

O 3 T J p h p - e o O 3 C O t r fl> r t K fl> fl> 3 r t 3 * (D
r t K 0 3 O < rt) c c o £ 3 p 3 O O 3 3 cr M (D < fl) P 1 • H 3 * fl) i Q • 1 (D P f t fl) M 3 g g 5 * fl) n o H i o P n O J p o < J P C Q o d p « P i 3 P p > rt) ( A t r fl> v Q p 3 ( A f t o o . o 3 p 3 P r t fl> P C Q n ro C O d H r t £ p - r t 3 * p 3 el - S - C D 3 0 a (D M ( A P S O fl) P P « P * O O 3 * O h r t C O p 3 O P 1 d a C D C Q o 3 fl) H i fl) 3 P p - (D C Q • o p 1 1 O i p 0 < 3 P ( A O d p * p n 3 p P 1 fl) C Q •
t-3 tr fl) O i p - H i H i (D H fl) 3 O fl) P 3 T J tr
• < ( A p o p * o U 4 KJ v£ ) p - < fl) C O el - s ' P - C O H i fl) 3 P P 1 fD C Q n n > P o 3 * r t 3 * fl) 3 * P i « 3 * fl) C O r t n O 3 3 cr p * c o < fl> p « C O a rt) C O T J p - f t fl> el - s ' fl) n n > cr ( D p 3 v Q 3 o H
. fl) n fl> C Q d p - r t H i n o 3 P
v Q P - < fl) 3 T J P r t r t fl) n 3 O H i O O fl) X T J o C O d n fl> • 

### s 0 h fl) o p 1 1 O i p 0 < p ( A o d P 1 P n T J 3 *
• < ( A P o p " o u j *< t r P < fl> P ( A p - v Q 3 P - H i P O P 3 r t P 3 T J P O r t O 3
r t 3 * fl) O O 3 3 c r p * fl) < 3 fl> P « C O K tr p o 3 " t-3 P t r p - C D

^ J 1 C O 4 > ^ p - r t P - C O p T J T J P H fl) 3 r t el - s ' P r t ei - S - C D 3 P P 1 rt) \ H i fl) 3 P p fl> O i p - H i H i rt) r i fl) 3 O C D ( A P 3 O O 3 T J P H P - 3 v Q el - s ' fl) fl) ( A r t p 3 P r t rt) ( A P 3
r- 3 P t r p fl)

« o 1 c o C O £ P - f t 3 " el - s ' fl) fl) e o r t P 3 P r r rt) C O p 3 3 P P * fl) C O P 3 O i H i fl) 3 P P - fl) C Q « t r O 3 * P < fl) o p n O i p 0 < P C O o d p > P n O J p - C O C D p C Q fl) • el - s ' fl) 3 o n C D ( A P - <f l 3 P - H i P O P 3 r t O i p - H i H i fl) 1 1 C D 3 O fl) cr n > r t £ C D fl) 3
r t t r ( D T J fl) H O C D 3 r t P v Q fl) o H i P O i d M r t v Q H fl) P r t fl> n T J fl)
• 1 o rt) 3 r t P U 4 fl) o H i H i fl) 3 P P » rt) C Q P 3 r t t r ( D T J o T J d P 1 p f t p o 3 p - e o o d r t « fl) p i Q 3 " rt) O i c r C O r t d o . * : P H n > P
r t tr P 3 P O i d P< r t H i (D 3 p H (D C O •

r 3 s - I D H i P O f t
r t t r P r t
r t tr at H (D p - C A p C O P > p i Q trtly T J (D 1 1 O fl) 3 r t 3 O i i fl) P O i d p - r t 3 P H fl) C O S p - r t 3 * O P H O i P O < P C O o d p « P n o . p - ( A n > P C Q fl) P 3 rt) P O t r o oqui p 3 p 3 v Q el - s ' fl) M P ( A r t
r t ^ o H i P o r t O n C Q ^
r t tr fl) h fl) P n n > P T J T J 1 1 o X p - 3 p ti - ro M ^ < r o

- j P H fl) a> C Q r r p 3 P r t C D O i
r t o t r P < ro o P H O J p o < P C O o d P > P H O J P - C O ro P C O ro • t r P < a> o P i i O i p o < P C O o d T-> P n O i p - C O C D p C O ro ^ K tr ro i i ro P C O c n • 0 0 T J fl) H o ro 3 f t o H i p O i d p * r t 3 P P « (D C O r t 3 - fl) H i P O r t
r t t r P r t O 3 H •< :

• u • r o T J fl) n o ro 3 r r 0 H i P 0 - d H r t H i ro 3 p p " fl) C O p n ro ro C O f t p 3 p r t fl) O i r t O P n ro H i o n 3 P p ro C Q p 3 O i H i ( D 3 P P 1 fl) C O S p - r t t r o P n O i p o < P C Q o p p - P n O i p - ( A ro P C O ro P 3 O i n C D H i Mect r t tr ro P o. d P 1 r t T J o T J d H P r t p O 3 P - ( A H i ro 3 P p « ro •

• 3 tr p n o . ^ r t 3 * ro rt) X T J o C O d 1 1 ro ro C O r t p 3 P r t (D C O T J P r t r t fl) n 3 0 H i O O fl) X T J O C Q d n ro • c n ro 0 o 3 O i ^ p C Q p « p - U 3 t r r t P * K
v Q H I D P r t ro n T J ro h o ro 3 f t P U 4 fl) O H i 3 P f t n > O i o o 3 3 t r M ro <: ro p - ( A p 3
r t t r ro c r p o 0 O i o H i H i ro 3 P P « ro C Q * • P (A C Q d 3 p - 3 v Q el - s ' ro C Q P 3 C D ~ J • M • p i

-- ^

. H S fl) O i p - H i H i a> H
. fl) 3 O ro C O p 3 r t t r ro C O ro < p p > d ro C O n ro C A d H r t p 3 3 1 P - v Q tr ro i i ro ( A r t p i o d C Q T J tr >< : C A P o P 1 0 v O p o p p * < p n p P cr P * ro C O H i o 1 1 3 P p - fl) ( A P 3 O i H i ro 3 p M ro C O ,-^ C O ro C D c n ro o r t p o 3 o H i
r t s n ro ro H i P o r t o n C Q •

* d p n C A r t ^ o < P - H i H i C D h ro 3 r t < J P M d ro C A K C D n ro P C O C O p uO
. 3 ro O i
r t o < p n p - i r t o fl) X o ro ro O J ( A ro p » ro o el - fl) O i n o 3 3 cr p « ro < ro p - C O d 3 O i ro h ei - s - ro C O p 3 C D C Q r t P 3 O i P H O i p - e o P H rosuit H 3 * fD O i P - H i H i ro h C D 3 O ro p 3 el - s ' ( D 3 g 5 o * ro n o H i 3 P P * C D C O P 3 O i H i at 3 P p < ro ( A ro C O r t p 3 p r t C D O i 0 0 l tr o d ti P < fl) i i P v Q (D C O f t P 3 O J P n O i p - C O 3 C D f t p 3 C D P O 3 * o H i el - s ' at H i o d n C O r t d O i ^ < P n ro P C O • r- 3 tr fl) C D C O f t P 3 P r t ro C O P n ro cr P C Q ro O i o 3 r t tr at P C Q ( A g g T J r t p o 3 r t t r P r t P
v o T J T J 3 \ P « w X w X p n ro p s i-3 P t r p « at ~~t i C O c o ^ p 3 O i ei - S - C D ro C O r t p 3 P el - fl) C O H i O n 3 P P * ro C O P H ro p 3

•-3 P t r p " ro

- j i c o O o 3 3 c r at C O r t p 3 P r t C D ( A H i o H
. 3 P p * ro ( A P 3 O i H i o n H i C D 3 p p « ro C O •

•- 3 3 * ro ro C O r t p 3 P ti - ro C O H i o 1 1 H iemales M 3 r t t r p - e o C O fl) O r t p O 3 • » P cr n p - fD H i O O 3 T J P H P - C O O 3 P - 1 0 3 P O i ro t r ro r t € ro ro 3 (A C D M ro oted - 4 • r o
2 • > p i M \ **1 W s ^ tr* W n o 2 TJ > 

### w H c n o 2 3 c nP.5 1

TABL E 7-33

. ESTIMATE S O F ADUL TFEMALE S WIT H CARDIOVASCULA R DISEAS E WH O EXPERIENC E COH b LEVEL S EXCEEDIN G SELECTE D VALUE S ASSUMIN G

9 PPM/ 1 EXEXSTANDAR D I S ATTAINE D

1 COH

B LEVEL 1 i 1 1 1 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A1 S

TLOUIS I 1 (PERCENT

) 1 I I | |

1 3.7 0 1 I I | | 1 3.5 0 1 I | | | 1 3.3 0 1 1 1 1 1 1 3.1 0 1 1 I I | 1 3.0 0 1 1 1 I | 1 2.9 0 1 1 1 1 1 1 1 ' t1 I 1 1 2.7 0 II I I I 1 2.5 0 1 1 1 I I 1 2.3 0 1 1 I 66 1 1 1 2.1 0 1 1 1 1.04 0 1 1 1 2.0 0 1 1 I 4,48 0 | 3 9 1 1 1.5 0 1 11,80 0 1 4,91 0 | 29,70 0 1 15,30 0 1 1 1.0 0 1 85,50 0 1 219,00 0 1 74,50 0 1 29,30 0 1 1 0.0 0 1 103,00 0 1 259,00 0 1 98,80 0 1 40,40 0 1
1 MAX
. COH B CONC
. 1 1.9 3 1 1.8 8 1 2.3 2 1 2.0 3 1 1 PEOPL E A TMAXIMU

M 1 10 3 1 1,33 0 1 30 1 1 1 1

7-4 0 

# JP.5 2



### TABL E 7-34 . ESTIMATE S OF ADUL T MALE S WIT HCARDIOVASCULA RDISEAS E WHO EXPERIENC E COH

bLEVEL S EXCEEDIN

GSELECTEDVALUE S ASSUMIN G 9 PPM/ 1 EXE

XSTANDARDI S ATTAINE D

1 COH

B LEVE L 1 1 1 1 | 1 EXCEEDE

O1 CHICAG O1 LOS ANGELE S 1 PHILADELPHI A 1 S T LOUI S 1 1 (PERCENT ) I j | j |

1 3.7 0 1 | l | | 1 3.5 0 1 1 1 I | 1 3.3 0 1 1 1 I | 1 3.1 0 1 1 1 I | 1 3.0 0 1 1 1 I | 1 2.9 0 1 1 1 I | 1 2.7 0 1 1 I | | 1 2.5 0 1 I I I | 1 2.3 0 I I - I | | 1 2.1 0 1 I 1 28 9 1 1 1 2.0 0 1 I 1 74 6 1 I 1 1.5 0 1 7,25 0 I 6,77 0 1 39,50 0 1 16,10 0 1 1 1.0 0 1 114,00 0 1 292,00 0 1 99,40 0 1 39,50 0 1 1 0.0 0 1 142,00 0 1 357,00 0 1 136,00 0 1 55,80 0 1

1 MAX . COH

B CONC . 1 1.8 3 1 1.7 5 1 2.1 9 1 1.8 6 1 1 PEOPL E A T MAXIMU

M 1 14 2 1 4,07 0 1 4 1 1 1 5 1



### 7-4 1« J

i • u r o 3 5 O J ro P * o P 3 o 3 P - K 3 n (D T J n ro C A ro 3 r t 3 P C J
. o n C O r t H d o r t d i i P p - H i C D P r t d n ro C O •
t d fl) O P d C O ro r t t r ro o H i T J ro 0 T J P 1 fD 3 d C O r t O i ro P P > 3 p el - s ' P 3 *< n p P O i 0 H i o o 3 T J p » ro X p - r t p at C O *
t-3 tr ro ro X T J O C O d n ro 

# e >< 3 at r t t r O O i d C A ro O i
r t o ro ( A r t p 3 P el - i D fl) X T J o ( A d H ro o H i P * P H if l C D ^ O i P - < (D n C O C D
UJ
. M Osdn -o . • •t ^ a z n C J » H3 > H Z t-3 K H 

### z 2 ! M 3 M t x TJ O c n C 3 

### § M c n r- 3 P I J 2 ^ t-3 M c n p -

3 O O n T J 0 n P r t C D f t t r p - C O o 

### o C O 0 d N O rt) • r t 0 N ro n 0 t r ro o P d C O fl) f t t r ro 3 d p < r t p - T J P " P O P f t P - <! fl) H i P O r t o H K P ( 0 P e o ( A g g ro O i f t o p p « H
. ro P O i ^ < o o 1 1 1 1 ro C O T J o 3 O i P S v Q f t o ( A 3 o * • p 3 v Q P 3 f t H P 3 C O T J o 1 1 r t P r t P o 3 < rt) 3 * P O M C D C O K P c a C O C D ei - C D A d P (D i Q d P M
r t o C M fl) n o •
> C O O i p - e o f l d c a C Q ro O i p 3 C A ro o r t p o 3 as • O J ^ el - s ' ro p O i O i p - r t p - < ro H i P o r t o H r t P - < J (D H i P o r t O n C O 0 H i t o • T-> o p 3 0 . P " • r o o N n fl) C Q TJ C D 0 f t P - < ! fl) H K ^ P 3 a . P o . o . p - r t p - < ( D H i P 0 r t 0 H C Q P P 1 o 3 i O I H o p O i t, p

• < C O 1 1 3 p o n 0 ro 3 < p n o 3 g fl) 3 r t C O $ P - r t 3 *
5 t r ro C O r t i ro C O r t p 3 P r t C D 3 3 d M r t p - T J M p -ca- p > fl) < at M C O P n ro « o ro 3 ro M P p - p -
• < ro X T J C D n p ro 3 o ro O J p 3 fi - l l P 3 C O T J o M r t P r t p o 3 <! fl) t r p o P ro ( A o H
. t-3 t r ro C A ro i i (D e o d H r t e o P n C D 3 o f t d 3 ro X T J (D O ti - ro O i • H 3
r t t r ro Z h j [2 3 o a ro P> ^ T J ro P

* • o o C O o d n o ro C O P n C D p 3 o P> d O J ro O J • o ro 3 r t ,~ * e n r t • tr* o d p - C A ^ — r r o 4 ^ • M T J ro n o ro 3 r t ^- ^ TJ 3 " P - P * P o . ro P 1 T J 3 * P P

— » s - p - v Q t r ro i i S 3 * (D 3 P - 3 O i O O n H i 0 d H C O r t d O i • < : P H C D P C O P 3 p H ^ N ro 

### o . « » 3 P X P - 3 g g O O 3 3 t r M ro < ro M e o P • 1 (D O 3 P 1 •< P 1 • o T J ro n i 3 p 3 ro Il - S - C D C Q P - u j 3 P - H i P O P 3 O (D o H i P 3 O J o O H
. C Q o d H O fl) ( A o 3 O O 3 3 c r P ro < ro M e o • ^ o H
r t t r ro n s at C O ro r t P t r P « ro C O o P 3 t r ro o o 3 T J p M ro O i
r t O

• 3 P c r P « ro ( A

- j i ^ i
r t t r h o d v Q t r «o . 1 V O f t O O i ro r t ro n P 1 ro < ro P> ( A p 3 ro X T J O C A ro O J T J o T J d P « P r t p o 3 CO
. p 3
r t 3 * ro p c r e o ro 3 o ro o H i p 3 O i o o n C O o d h o ro C Q • t- 3 P t r P 1 ro C O

- O i c o

- 4 f t t r i i o d v Q 3 -

~ j i c o v o T J n 0 < p - O i ro r t 3* i i ro ro p 3 O i p o P r t o n c a O H i o o 3 3 t r s - p - v Q 3 * (D n i. tr ro 3 p 3 O i o O n C O 0 d n o ro ( 0 P n ro p 3 o p d O i ro a • P n ro p 3 o M d O i ro O i • £ P X P - 3 g 0 0 l tr o P n o o C D X T J o ( A d n ro C O P n ro P> • o r r o

- j •

-o T J (D h O ro 3 r T o o ro X T J o C O d n ro ( A P i i ro H ro C O c a r t t r P 3 M • o T J (D n o ro 3 r t tr p vf l 3 1 ro n s: tr ro 3 p - 3 O i o o 1 1 C O O d h o C D C O tr P < 3 C D P 3 p 3 O H C D H i H i ro o r t o 3 P 1 1 t r o d h P 3 O i 0 0 1 tr o d H C D X T J o C O d n ro C O • 3 P X P 3 g M Ihour o o 3 T J P n p - 1 0 o s 

### c p - r t t r t-3 P t r p < ro ( A

« j i r o P 3 O i

« J 1 c n n ro < ro P p - C O
r t 3* P r t p 3 O i O o n ( A 0 d n o ro C O d 3 O i ro n ; r t t r ro v o T J T J 3 \ M M X c n X C O r t P 3 O J P h O J p 3
r t 3 * C D P t r e a ro 3 o ro o H i p 3 O i O o n C Q o d n o ro C Q • r t tr at 3 g g 5* at n o H i T J ro o T J P 1 ro ( D X T J O C O fl) O i
r t O P 1 l tr o P h P 3 

### o - 0 0 1 tr O d n n o o o 3 O ro 3 ti - l l P r tions P H ro C O P 3 T J M ro o d r t T J d r t o H i e a d o tr P 3 P 3 P p > ' ^ ( A P - ( A •

H 3 tr at "< T J H o < P - O i ro ro C A r t p 3 P r t rt) C A o H i ,- , P - • ro • ^ P 3 * fi - l l o H i o n P M P 1 3 p - o H
. o ro 3 < p h o g g ro 3 r t c a

— .

. t-3 P t r p - C D C Q

-~J 1 C O c n P 3 O i

-o 1 C O Z P - r t 3 "
r t 3 * C D P P * P * P O J O i P - r t p - < 3 C D 3 p o H O ro 3 <! P n o 3 3 ro 3 r t H i P O r t O n ( A C O C D r t ro • Q d p M
r t o N ro n o r t tr ro C Q p i O 3 p - H i p o P 3 o ro o H i
r t t r ro ( A ro n o C Q o d n o ro C O

• » K ro o P 3 H at T J ro P r t r t 3 - ro p 3 P P 1 K ( A P - e o c a r t O < C D C O p 3 O J ( A 3 o rK p 3 v Q O O 3 ti - l l P - c r d ti - ro r t o f t o r t P T~> O O C D X T J o c a d H C D •
t-3 O ro < P M d P ti - ro ^ 3 tr ro < D X T J 0 C O d H ro • ro C O r t p 3 P ti - ro e a O i p - ( A o d e o C O C D O i p 3 c n ro o r t p o 3

- o « M P C O e a d 3 ro
UJ
. P C O ^ j • C O

• 3 3 3 W c n H O Z H *1 H o > z n M o *n H z o o o » c n O a » o M c nP.5 4



### TABL E 7-35 . ESTIMATE S OF ADULT S WIT HCARDIOVASCULA RDISEAS E WHOHAV

E 1-HOU RC OEXPOSURE S ABOV

E SELECTEDVALUE S UNDER9 PPM/ 1 EXE X STANDARDWIT HINDOO

RSOURCE S OMITTED

1 CONCENTRATION 1 EXCEEDE D 1 (PPM )

1 60. 0 1 55. 0 1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 PEOPL E AT MAXIMU M CHICAG O

1,25 0 11,40 0 22,30 0 53,20 0 108,00 0 119,00 0 122,00 0

25. 7 52 3 LO S ANGELE S

5,79 0 62,20 0 ; 188,00 0 256,00 0 299,00 0 305,00 0

21. 7 5,79 0 PHILADELPHI A

1,27 0 1,27 0 3,80 0 21,60 0 36,80 0 69,30 0 85,40 0 99,00 0 116,00 0

36. 0 1,27 0 S T LOUI S 1

70 8 1 6,20 0 I 7,28 0 1 19,50 0 1 28,80 0 1 36,60 0 1 43,40 0 1 47,50 0 1

32. 0 I 70 8 1



### 7-4 3P.5 5



### TABL E 7-36
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WH O HAVE 8-HOU RCO EXPOSURE S ABOVE SELECTE D VALUE S UNDE R9 PPM/ 1 EXE X STANDARD WIT H INDOORSOURCE S OMITTE D

1 CONCENTRATIO

N1 1 | | 1 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 ST LOUI S 1 1 (PPM

) I I1 1 |

1 60. 01 1 1 1 I 1 55. 01 1 1 1 1 1 50. 01 1 1 1 I 1 45. 01 1 III 1 40. 01 1 1 1 1 1 35. 0I I1 II 1 30. 01 1 I I| 1 25. 01 1 1 1 1 1 20. 01 1 I I1 1 15. 01 1 II| 1 12. 01 I| 2,16 01 1 1 9. 01 5,26 0 1 5,79 01 32,30 01 7,22 0 1 1 7. 01 54,20 01 13,40 01 36,30 01 22,50 01 1 0. 01 122,00 01 305,00 01 116,00 01 47,50 01

1 MAX . CONCENTRATIO

N1 11. 6 1 10. 5 1 13. 01 10. 71 1 PEOPL E A T MAXIMU

MI14 71 5,79 01 10 0I4 5 1



### 7-4 4P.5 6



### TABL E 7-37
. ESTIMATE S O F OCCURRENCE S FO RADULT S WITH CARDIOVASCULA R DISEAS E OF COHb LEVEL S EXCEEDIN G SELECTE D VALUE S UNDE R 9 PPM/ 1



### EXE XSTANDARD WITH INDOORSOURCE S OMITTE D

1 COH B LEVE L 1 1 EXCEEDE D1 1 (PERCENT ) 1

1 3.7 0 1 1 3.5 0 I 1 3.3 0 1 1 3.1 0 I 1 3.0 0 1 1 2.9 0 1 1 2.7 0 1 1 2.5 0 1 1 2.3 0 1 1 2.1 0 1 1 2.0 0 1 1 1.5 0 1 1 1.0 0 1 1 0.0 0 1

1 MAX . COH B CONC . I 1 ENCOUNTER S A T MAX . 1 CHICAGO1

45,20 0 1 3,720,00 0 1 1,070,000,00 0 f

1.8 9 1 6 6 1 LO S ANGELE S

60,10 0 3,540,00 0 2,670,000,00 0

1.8 2 2.03 0 PHILADELPHI A

36 7 1,87 0 140,00 0 1,340,00 0 1,020,000,00 0

2.2 2 5 3 S T LOUI S 1

2 1 1 22.10 0 1 775,00 0 I 416,000,00 0 1

2.0 0 1 2 1 1



### 7-4 5

### TABL E 7-38
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E WH O EXPERIENC E COHbLEVEL S EXCEEDIN GSELECTE D VALUE S UNDE R 9 PPM/ 1 EXE XSTANDARD WIT H INDOORSOURCE S OMITTE D P.5 7

1 COH

B LEVE L 1 I I1 1 1 EXCEEDE

D 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 ST LOUI S 1 1 (PERCENT

) 1 1 1 1 1

1 3.7 01 | I| | 1 3.5 01 | I| | 1 3.3 01 1 1 1 1 1 3.1 01 1 1 I I 1 3.0 01 1 1 1 1 1 2.9 01 1 1 I1 1 2.7 01 I I1 1 1 2.5 01 I I| I 1 2.3 0 1 I III 1 2.1 0 II 1 15 6 1 1 1 2.0 0 1 1 1 86 4 I2 1 | 1 1.5 01 9,17 01 5,79 01 33,00 01 9,11 01 1 1.0 01 75,80 01 175,00 01 47,10 01 26,00 01 1 0.0 01 122,00 01 305,00 01 116,00 01 47,50 01

1 MAX . COH B CONC . 1 1.8 9 1 1.8 21 2.2 21 2.0 01 1 PEOPL E A T MAXIMU

MI6 6 1 2,03 01 5 3 1 2 1 1



### 7-4 6P.5 8



### TABL E 7-39 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E WHOS E MAXIMU M COH bLEVELOCCUR S I

N SELECTEDRANGE S UNDER9 PPM/ 1 EXE XSTANDAR

D WIT HINDOO

RSOURCE S OMITTED

1 COH

B LEVE L 1 1 1 1 1 1 RANG

E 1 CHICAG O 1 LO

S ANGELE

S 1 PHILADELPHI

A 1 ST LOUI S 1 1 (PERCENT

) 1 1 1 1 1

1 3.7 0< C <= 10.0 01 II I1 1 3.5 0< C <

= 3.7 01 1 1 I I 1 3.3 0< C <= 3.5 01 I I1 1 1 3.1 0< C <

= 3.3 01 1 1 1 1 1 3.0 0< C <

= 3.1 01 1 1 1 1 1 2.9 0 < C <= 3.0 01 1 1 1 1 1 2.7 0 < C <

= 2.9 01 I I1 1 1 2.5 0 < C <= 2.7 01 1 I I1 1 2.3 0< C <= 2.5 01 1 - 1 1 1 1 2.1 0< C <= 2.3 0 1 1 1 15 71 I 1 2.0 0 < C <

= 2.1 0 1 1 1 70 9 I2 1 I 1 1.5 0< C <= 2.0 0 1 9,17 01 5,79 01 32,20 01 9,09 01 1 1.0 0< C <

= 1.5 01 66,60 01 169,00 01 14,10 01 16,90 01 1 0.0 0< C <

= 1.0 0I45,80 01 130,00 01 69,30 01 21,50 01

1 MAX . COH B CONC . 1 1.8 9 1 1.8 21 2.2 21 2.0 01 1 PEOPL E A T MAXIMU

M1 6 6 1 2,03 01 5 3 1 2 1 1



### 7-4 7P.5 9



### relevan t dat a base s ofte n ar e incomplet e and/o r inaccurate , professiona l judgmen t play s a significan t rol e i n selecting monitor s t o represen t neighborhoo d types , i n validating ai r qualit ydata , i n estimating cohor t populations , an d i n determin

ing cohor t movements . Ideally , th e uncertaint yi n eac hsignifican t facto r affect

in g exposur e woul d b e addresse d formall ywithi n the exposur e mode l s o tha t a forma l representatio n o f the uncertaint yi n eac h exposur e estimat e woul d b e par t o f the outpu t o f the model
. Forma l technique s fo r characterizing the uncertaint yi n estimate s generate d b

yapplying th e NE Mmode l ar e unde r development
. Du e t o limitation s o f time an d resources , thes e technique s wer e no t availabl e fo r thi s application
. Instead , severa l source s o f uncertaint ywer e investigate d vi a a limite d sensitivit yanalysis
. Severa l value s wer e use d fo r some o f the inpu t quantitie s t o se e ho wsensitiv e selecte d exposur e estimate s ar e t o thi s variation
. Th e input s chose n ar e the microenvironmen t factors , the larges t sourc e o f uncertaint yi n estimating exposure , an d the physiologica l variable s use d i n determining bloo d COHblevel s from exposur e patterns . Lower , best , an

d uppe r estimate s o f microenvironmenta l fac

tor s ar e presente d i n Sectio n 6.0
. Thes e differing estimate s o f microenvironmenta l factor s wer e use d t o calculat e exposur e esti

mate s fo r adult s wit hcardiovascula r diseas e i n Chicago , assuming a 9 ppm/ 1 ExE xstandard i s jus t met . Exposur e estimate s fo r 1-hour averag e an

d 8-hour averag e C O concentration s ar e presente d i n Table s 7-4 0 an

d 7-41
. Th e result s indicat e tha t the differenc e betwee n the lowe r estimate s an d th e uppe r estimate s i s appreciable
. Thi s larg e variatio n primaril yresult s fro mthe larg e difference s betwee n lowe r an

d uppe r estimate s o f multiplicativ e microenviron

men t factors , particularl ythos e fo r transportatio n vehicle s an d roadsides
. Table s 7-4 2 through7-4 4 provid e COHbleve l estimate s corre sponding t o the same lower , best , an d uppe r estimate s o f micro

environmen t factors
. Th e resulting variatio n i n COHblevel s i s 7-4 8P.6 0



### TABL E 7-40 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E I

N CHICAGO WIT H1-HOU

RCARBO N MONOXID E EXPOSURE S ABOVE SELECTEDVALUE S UNDER1 2 PPM/ 1 EXE XSTANDAR

DUSIN GBEST , LOWER , AN

DUPPERMICROENVIRONMENT FACTOR S

1 CONCENTRATION 1 EXCEEDE O 1 (PPM )

1 60. 0 1 55. 0 1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 PEOPL E A T MAXIMU

M BES T ESTIMAT E 1

11,20 0 I 11,40 0 1 22,30 0 I 59,20 0 1 108,00 0 1 119,00 0 1 122,00 0 I 122,00 0 1

34. 6 1 52 3 1 1 LOWE RESTIMAT E

1 11,20 0 1 22,00 0 1 51,10 0 1 99,90 0 1 120,00 0 1 122,00 0

1 23. 0 1 52 3 UPPERESTIMAT E 1

1,25 0 1 11,20 0 1 11,40 0 1 19,50 0 1 22,30 0 1 51,10 0 1 59,20 0 1 99,60 0 1 121,00 0 1 122,00 0 I 122,00 0 I 122,00 0 I 122.00 0 I

58. 0 1 52 3 1



### 7-4 9P.6 1



### TABL E 7-41 . ESTIMATE S O F ADULT S WIT HCARDIOVASCULA RDISEAS E I

N CHICAGO WITH8-HOU

RCARBO N MONOXIDE EXPOSURE S ABOV E SELECTEDVALUE S UNDER1 2 PPM/ 1 EXE XSTANDAR

DUSIN GBEST , LOWER , AN

DUPPERMICROENVIRONMENT FACTOR S

1 CONCENTRATIO

N 1 1 1 1 1 1 EXCEEDE

D1 BEST ESTIMAT E 1 1 LOWE RESTIMAT

E 1 UPPE

RESTIMAT

E 1 1 (PPM ) 1 1 1 1 1

1 60. 0 1 I I I | 1 55. 0 1 1 1 1 1 1 50. 0 1 I | I I 1 45. 0 1 1 I 1 1 1 40. 0 1 I | I | 1 35. 0 1 1 1 1 1 1 30. 0 1 I I 1 1 1 25. 0 1 1 I I 77 6 1 1 20. 0 1 I . I | 5,26 0 1 1 15. 0 I 1,90 0 1 I | 31,00 0 1 1 12. 0 1 5,26 0 I I 1 86,40 0 1 1 9. 0 I 67,30 0 1 I 4,67 0 1 115,00 0 1 1 7. 0 1 93,30 0 I I 61,60 0 1 121,00 0 1 1 0. 0 1 122,00 0 I I 122,00 0 1 122,00 0 1

1 MAX . CONCENTRATIO

N | 16. 0 1 1 10. 6 1 29. 0 1 1 PEOPL E A T MAXIMU

M 1 5 4 1 1 33 5 I 5 4 I



### 7-5 0

### TABL E 7-42 . ESTIMATE S OF OCCURRENCE S FO RADULT S WITHCARDIOVASCULA RDISEAS E I N CHICAGOOF COH

bLEVEL S EXCEEDIN

GSELECTEDVALUE S UNDER1 2 PPM/ 1 EXE XSTANDARDUSIN

GBEST , LOWER , AN

DUPPERMICROENVIRONMENT FACTOR S P.6 2

1 COH B LEVE L 1 EXCEEDE D 1 (PERCENT )

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 .3.0 0 1 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.00 . 1 1.5 0 1 1.0 0 1 0.0 0

1 MAX . COH B CONC . 1 ENCOUNTER S AT MAX . BES T ESTIMAT E 1

13 4 I 2,46 0 1 16,60 0 1 39,70 0 1 1,240,00 0 1 32,700,00 0 I 1,070,000,00 0 1

2.5 2 1 2 4 1 LOWE RESTIMAT E 1

14,70 0 1 2,890,00 0 1 1,070,000,00 0 1

1.7 8 1 6 7 I UPPERESTIMAT E 1

3,98 0 I 9,39 0 1 24,10 0 I 53,00 0 1 83,30 0 I 120,00 0 I 257,00 0 1 562,00 0 I 1,210,00 0 1 2,480,00 0 1 3,580,00 0 I 31,500.00 0 1 409,000,00 0 1 1,070,000,00 0 1

4.5 5 1 2 4 I



### 7-5 1P.6 3



### TABL E 7-43
. ESTIMATE S O F ADULT S WIT H CARDIOVASCULA RDISEAS E I

NCHICAGO EXPERIENCINGCOHbLEVEL S EXCEEDIN GSELECTE D VALUE S UNDE R1 2 PPM/ 1 EXE X STANDARD USIN

GBEST , LOWER , AN

D UPPE RMICROENVIRONMENT FACTOR S

1 COH B LEVE L 1 EXCEEDE D 1 (PERCENT )

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 3.0 0 1 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.0 0 1 1.5 0 1 1.0 0 1 0.0 0

1 MAX . COH B CONC . 1 PEOPL E A T MAXIMU

M BES T ESTIMAT E 1

1 3 8 6 0 12 0 12 2 7 8 I 25 0 1 77 0 1 91 0 1 00 0 1 00 0 1 00 0 1

2.5 2 1 2 4 1 1 LOWE RESTIMAT E

1 3,76 0 1 78,30 0 1 122,00 0

1 1.7 8 1 6 7 UPPERESTIMAT E 1

1,31 0 1 2.67 0 1 3.55 0 1 5,09 0 I 7,38 0 1 8,55 0 1 12,10 0 I 24,30 0 I 55,60 0 1 75,10 0 1 85,80 0 1 117,00 0 1 122,00 0 1 122,00 0 I

4.5 5 1 2 4 1



### 7-5 2P.6 4



### TABL E 7-44 . ESTIMATE S OF ADULT S WITHCARDIOVASCULA RDISEAS E I

N CHICAG O WHOS E MAXIMU

M COH bLEVELOCCUR S I

N SELECTEDRANGE S UNDER1 2 PPM/ 1 EXE X STANDARDUSIN

GBEST , LOWER , AN

DUPPERMICROENVIRONMENT FACTOR S

1 COH

B LEVE L 1 1 1 1 1 1 RANG

E 1 BES

T ESTIMAT

E 1 1 LOWE RESTIMAT

E 1 UPPE

RESTIMAT

E 1 1 (PERCENT

) 1 1 1 1 1

1 3.7 0< C <= 10.0 01 1 1 I1,31 0 1 1 3.5 0< C <= 3.7 01 1 1 1 1,36 01 1 3.3 0< C <= 3.5 01 II| 88 1 1 1 3.1 0< C <= 3.3 0II I| 1,54 01 1 3.0 0< C <= 3.1 0til l2,29 01 1 2.9 0 < C <= 3.0 01 1 1 1 1.17 0 1 1 2.7 0 < C <= 2.9 0 1 1 1 I3.55 01 1 2.5 0< C <= 2.7 0 I7 9 I| | 12,20 01 1 2.3 0 < C <= 2.5 0 1 1,18 01 1 1 31,30 01 1 2.1 0 < C <= 2.3 0 1 2,51 01 1 1 19,60 01 1 2.0 0 < C <= 2.1 0 I5.15 0 1 1 I10,60 01 1 1.5 0< C <

= 2.0 0 1 51,10 01 I3,76 01 30,90 01 1 1.0 0< C <

= 1.5 01 59,60 01 1 74,60 01 4,94 0f 1 0.0 0< C <

= 1.0 01 1,93 01 1 43,30 01 1

1 MAX . COH B CONC . 1 2.5 21 1 1.7 8 1 4.5 5 1 1 PEOPL E A T MAXIMU

M1 2 4 1 1 6 71 2 4 1



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. p - w o C O C O C D D i c u c r o < C D • O o 3 C O p - C Q f t C D 3 f t t, P el - s ' r t 3 * C D P 1 c u 1 1 i Q C D < c u n p - fu r t p - O 3 C O p - 3 M 1 t r o p i i c u 3 D
. C O 1 tr o P n o oP.6 6



### 7. 5 REFERENCE S 1
. Memorandu

mfro mHarveyRichmond , Ambien t Standard s Branch , t o Mik e Jones , Chie f o f the Ambien t Standard s Branch , U.S . Environmenta l Protectio n Agency , Researc hTriangl e Park , Nort hCarolin a 27711
. Septembe r 8 , 1982
. 2
. F . L . Rodkey , J . D . O'Neal , an d H . A . Collison , "Oxyge n an d carbo n monoxid e equilibri a o f human adul t hemoglobi n a t atmospheri c an

d elevate d pressure, " Blood , Vol
. 33 , No . 1 , 1960 , pp . 57-65
. 3
. U.S . Departmen t o f Health , Education , an d Welfare , Publi c Healt hService , Hemoglobi n an d Selecte d Iron-Relate d Find

ing s o f Person s 1-7 4 Year s o f Age ; Unite d States , 1971-1974
. Advanc e dat a numbe r 46 , January26 , 1979
. 4
. R . F . Coburn , e t al , "Endogenou s carbo n monoxid e productio n i n man, " J . o f Clin
. Invest. , Vol
. 42 , 1963 , pp . 1172-1178
. 5
. S . R . Lync han

d A . L . Moede , "Variatio n i n the rat e o f endogenou s carbo n monoxid e productio n i n norma l human beings, " J . Lab
. Clin
. Med. , Vol
. 79 , 1972 , pp . 85-95
. 6
. P . D . Berk , e t al , "Compariso n o f plasm a bilirubi a turnove r an d carbo n monoxid e productio n i n man, " J . Lab
. Clin
. Med. , Vol
. 83 , 1974 , pp . 29-37
. 7
. M . Delivoria-Papadopoulos , R . F . Coburn , an d R . E . Forster , "Cycli c variatio n o f rat e o f carbo n monoxid e productio n i n norma l women, " J . Appl
. Physiol. , Vol
. 36 , 1974 , pp . 49-51
. 8
. R . P . Brouillard , M . E . Conrad , an d T . A . Bensinger , "Effec t o f bloo d i n the gu t o n measurement s o f endogenou s carbo n monoxid e production, " Blood , Vol
. 45 , 1975 , pp . 67-69
. 9
. C . A . Coltman an d G . M . Dudley , "The relationshi p betwee n endogenou s carbo n monoxid e productio n an d tota l heme mas s i n norma l an

d abnorma l subjects, " Am . J . Med
. Sci. , Vol
. 258 , 1969 , pp . 374-385
. 10
. R . Joumard , e t al , "Mathematica l model s o f the uptak e o f carbo n monoxid e o n hemoglobi n a t lowcarbo n monoxid e levels, " Env . Healt hPersp. , Vol
. 41 , 1981 , pp . 277-289
. 11
. T . Sjostrand , "Blood volume, " Handboo k o f Physiology , Vol
. 1 , Sectio n 2 , Chap
. 4 , 1962 , pp . 51-62
. 12
. U . S . Nationa l Cente r fo r Healt hStatistics , Advanc e Data . No . 3 , Novembe r 19 , 1976 , an d No . 14 , Novembe r 30 , 1977
.

7-5 5P.6 7



### 13
. V . Niinimaa , P . Cole , S . Mintz , an d R . J . Shephard , "Ora l nasa l distributio n o f respiratoryairflow, " Resp . Physiol , Vol
. 43 , 1981 , pp . 69-75
. 14
. Revie wo f the Nationa l Ambien t Ai r Qualit yStandard s fo r Sulfu r Oxides : Assessmen t o f Scientifi c an d Technica l Infor

mation , Strategie s an d Ai r Standard s Division , Offic e o f Ai r Qualit yPlanning an d Standards , U . S . Environmenta l Protectio n Agency , Researc hTriangl e Park , N.C . 27711 , Novembe r 1982
. 15
. U . S . Departmen t o f Health , Education , an d Welfare , Publi c Healt hService , CoronaryHear t Diseas e i n Adults
. Unite d States ; 1960-1962 , Vita l an d Healt hStatistic s Serie s 11 , No . 10 , Decembe r 1975
.

7-5 6

### SECTIO N8 NATIONWID E EXTRAPOLATION S
Th e exposur e mode l describe d i n the preceding section s i s applie d directl yt o individua l urbanize d areas . T o obtai n C O exposur e an

d COHbdistribution s fo r al l urbanize d area s directl y fro mthe mode l woul d requir e tha t the mode l b e applie d t o eac h urbanize d are a separatel yan d the distribution s obtaine d b e summe d according t o the expressio n
n E(C ) = Z

e . (C ) , (8-1 ) i= l x 

### wher e E(C ) i s the tota l numbe r o f exposure s t o a concentratio n above C fo r al l urbanize d area s an d e.(C ) i s the exposur e dis

P h 

### tributio n fo r th e i

— are a o f n urbanize d areas . Analogou s expression s can b e writte n fo r the numbe r o f peopl e wit hexpo sure s above selecte d concentration s an d the numbe r o f peopl e whos e maximu

mexposur e occur s i n selecte d ranges . T o carryou t thes e computation s woul d requir e the developmen t o f pollutan t concentratio n an

d human activit ydat a base s fo r eac hurbanize d are a i n the U.S . Suc han analysi s i s no t feasibl e a t the presen t time
. Accordingly , roughestimate s o f nationa l exposur e fo r adult s wit hcardiovascula r diseas e wer e mad e b yextrapolating the exposur e an

d COHbestimate s obtaine d fro mmodelling the four stud yarea s discusse d i n previou s sections , namely , Chicago , Lo s Angeles , Philadelphia , an d St . Louis
. Th e extrapolatio n procedur e use d i s describe d i n Sectio n 8.1
. Result s o f the extrapolatio n ar e presente d i n Sectio n 8.2
. Adiscussio n o f the uncertaint yabou t the accuracyo f thes e estimate s i s give n i n Sectio n 8.3
.

8- 1P.6 9



### 8. 1 EXTRAPOLATIONPROCEDUR E Equatio n 8- 1 can b e rewritten , i n term s o f exposure s pe r perso n i n the population , a s
n E(C ) = Z P.e?(C ) (8-2 )

i= l 1 L 

### wher e e?(C ) i s the exposur e distributio n pe r perso n i n the popu 1 j. U 

### latio n an

d P . i s the populatio n o f the i

— urbanize d area . A s wit hEquatio n 8-1 , analogou s equation s can b e writte n fo r eac h o f the exposur e an

d COHbdistribution s provide d b ythe model
. The effec t o f factoring ou t the populatio n i s t o bring the e.(C ) value s fo r differen t area s jus t meeting a give n alternativ e stan

dard int o close r agreement . Ther e wil l continu e t o b e significan t differences , however , an d the basi c assumptio n o f the extrapola

tio n i s tha t the e.(C ) fo r the four bas e stud yarea s ar e sufficien t t o represen t thes e difference s exhaustively
. Therefore , the firs t step i n applying th e metho d wa s t o assign eac hurbanize d are a t o on e o f the four bas e areas . Th e valu e o f n i n Equatio n 8- 2 wa s se t equa l t o four , an d P . became the tota l populatio n o f urban

i j_t

_ 

### ized area s assigne d t o the i

—bas e area . Th e ultimat e goa l o f the extrapolatio n i s t o estimat e wha t the exposur e o f the sensitiv e populatio n (i.e. , adult s wit h cardiovascula r disease ) woul d b e i n 198 7 unde r eac ho f thre e ai r qualit yassumptions
. Thes e assumption s ar e tha t the thre e ai r qualit ystandard s discusse d i n Sectio n 7 ar e jus t me t i n al l urba n areas . Sinc e some urba n area s ar e expecte d t o hav e cleane r ai r i n 198 7 than require d b ythe give n standards , NE Mestimate s whic har e base d o n jus t meeting the standard s ar e highe r than theywoul d b e i f theyha d bee n base d o n estimate d 198 7 quality
. Th e C O exposur e an

d COHbdistribution s fo r eac ho f the four bas e area s ar e divide d b ythei r respectiv e adul t populatio n value s t o obtai n the e.(C ) distributions
. T o obtai n the urba n populatio n estimate s t o associat e wit heac ho f the bas e areas , eac ho f the urbanize d area s wit hpopulation s greate r than 200,00 0 i s assigne d 8- 28-3 3 c u W p 3 t Q el - s ' C D C U D
. C J - P C O 

## 0 C D 3 f t D i C D C O O H P - c r ( D D
. P 3 el - S - C D P « C U C O f t T J c u n c u v O n ( U T J 3 * • c r C D C O r t p n c r c u 3 T J O T J P P 1 C U r t p O 3 D
. C U r t P » ( U < c u p r-> C U cr p « C D H i o n el - s ' P - C Q T J P H T J O C Q C D C u 3 D
. H i o H f t t r C D H i c u o r t o n p c o C D D - H l O n r t tr C D C D X f t h c u T J o p - c u r t P O 3 •

r 3 t r f D p * V O

- J o D
. C U ct c u K C D n C D f t tr C D a • C/ > • T J O T J P M c u r t p o 3 D
. C U f t c u c u 3 D i C U 3 a> C O r t p g c u r t C D D
. ut) H O 2 r t 3 - H c u f t C D f t 0 D < C D f t ( D 

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. P 3 O r t p O 3 £ P - r t t r p * v o 0 0 o r t O r t c u r-> -1 • p * • P 1 ^ ^

.

•-3 3 * C D M v o

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• < P in at D i
r t O C D C Q r t p 3 C U r t C D c r c u C O C D c u 1 C D C U T J o T J P M C U r t p O 3 D
. C U f t C U f t 3 * C D * < C U n C D C D X t- r i i c u T J 0 M fit Ct C D D
. r t o M v o 0 0 ^ J ^- * C Q C D C D 0 1 C D O r t P O 3 2 5 o r t C D
r t t r c u r t ( U P 1 r t t r 0 P v Q 3 " ei - S - C D C D P - O ^- % n *- * < C U p P a> ( 0 c u n C D t r c u C O I D D
. o 3 M v o ^ j o P r tban"- r r tr a> D
. C D C O p h C D D
. C D X f t 1 1 c u T J o p » ft) f t C D D > D > P - ( 0 ct 1 1 p - c r P ct p o 3 ( 0 • T J n p - c u r t C D C D P - 0 ^- » O

— ' < (ii p p a> ( 0 H i o n C D at a tr ai X T J o C O p i i C D P) 3 D J O O a t r D
. p - C O ii - i i p - c r P ct ,H - o 3 » <ields w • D p fit ct p o 3 0 0 1 t o o H i el - s ' C D c u D
. C J
. P C O ct a> D i T J 0 T J p p - c u r t p 0 3 < fit P « P at c o m 3 D
. r t t r C D fit T J T J 1 1 o 1 C U H C D C U C Q S P - r t tr T J o T J P r-> fit Ct P o 3 C O
v Q n C D ft> f t C D h
r t S - C U 3 ro o o ^ o o o • C O d c r C O r t p ct p ct p 0 3 P - 3 c u 1 1 C D C U T J o T J d H C U f t P O 3 P - 3 P < v o

~ 4 o r t o ct tr a> ct o ct fit p « P 1 v o ^ 1 o T J O T J P P « C U r t P O 3 P - 3 P H tr fit 3 T-3 tr p - C O C U D J C J
. P C O 

## ff C D 3 r t P - C O 3 C U D
. C D t r *l p ( 0 p 3 v Q f t tr at n C U f t p o o H i el - S - C D
r t O r t c u P 1 d n cr ft> 3ized r o o o ^ o o o p - C Q M C D C O C Q
r t tr fit 3
r t 3 * C D
r t O r r fit p > T J 0 T J d P " c u r t p O 3 O H i P n cr fi> tt p - N C D D i c u r t C D C U C Q • p - c u ct p o 3 0 H i c u C Q C Q 0 o p - c u f t C D Qt p h c r c u 3 p - N C D O i c u n C D ft) C Q
* : p - r t tr T J o T J d M ft) f t P o 3
v O M C D ft) r t C D 1 1than 

## £
c u DC J
. d C O 

## g C D 3 f t P - C Q h C D • D d p - n C D D
. t r C D o c u p C O C D
r t t r C D
r t o r t fit M C O C D 3 C Q p - r t p - < at T J 0pu- M a, •+ t o o o ^ o o o •*~* ^ c u K ( D c u C Q C Q P l Q 3 C D D i
r t o n tr p o ft) If l 0 • d n t r c u 3 p - N C D D
. C U H C D ft) ( 0 •" » P 3 O P < d D p - 3 v Q f t 3 " C D a C D < K ! 0 h * " d n t r c u 3 P - N C D D
. fit rt at fit

. —. T J o T J • t r c u C O C D ft) H C D ft) •

r 9 tr p - ( 0 C O p - r t d ft) r t P O 3 O O O d n C O c r ( D o C U p C O C D ( 0 C D < ! C D H C U P « o H i f t tr a>

T-> fit n mest T J C D n o C D 3 r t o H i el - S - C D f t O ct C U P > d n c r C U 3 T J o T J d r-> fit it P - o 3 P - C O ft* t o C O O o p fit ct at D J 2 p - r t tr
r t 3 * p - C Q a o t a> < at n c u P > r t 3 - o d i Q 3 * o 3 M ^ < ro r o c u H C D C U C O S C D h C D fit C O C Q P - v Q ti C D D - r t o O 3 * P O fit v Q o ^ O < C D n c o c n r-> v o

- O O ft) n C D D i P - C O f t r i H - t r d r t C D D i n C D M c u r t P - < C D P * » < C D < J C D 3 P 1 K : Q l g o 3 i D
r t 3 * C D H i o d 1 1 t r c u C O C D ft) neas. r t tr C D P o c n d H t r c u 3 p - C M C D D i fit rt C D ft) C O £ P - f t 3 - T J 0 T J d H ft) f t P O 3 C Q
v Q H C D ft) f t C D 1 1 f t tr fit 3 t o o o ^ o o o p - 3 O H C D ft) ft) H C D H P - C Q f t C D D i P 3 H ft) c r P 1 C D 0 0 1 t- 1 •
» C D < P - C D s : o H i f t 3 - ( D C Q C D D
. ft) r t C U
r t C D < C D ft) P « C O
r that r 3 3 * C D
r t o r t fit P ft) 3 D
. C O C D 3 C Q P - r t p - < C D T J o T J d P " ft) r t p 0 3 C O ft) C O C O p ut) 3 ( D D
. r t 0 C D ft) O 3 * c r c u C Q C D cr c u ( 0 C D D i O 3 M v o

- O O O C D 3 C O p C O D i ft) f t ft) • H i o H C D ft) O 3 - cr ft) C Q C D ft) n C D ft) •

T-3 tr at T J o T J d M ft) r t p o 3 D J ft) ct fit P C O C D D
. ft) f t
r t t r p - c o C Q r t ft) v Q C D Cere r t t r C D c r c u C O C D ft) n C D ft) "— ' « ft) C O o cr r t ft> p 3 C D D
. t r

• < C O p g g p 3 v Q el - S - C D ft) t o C O O O p - ft> r t C D D i T J O T J d P " ft) ei -ions ro o o • * o o o fit C Q C O o o p ft) f t C D D J K p - r t t r C D ft) o 3 " t r c u C O C D c u M C D ft) ^- ^ * : t r p o s- p 3 O M d D i C D D
. r t t r fit ct O H i ct O ct ft) M T J o T J P \-> fit Ct P O 3 H i o n d H cr ft> 3 ft) n C D c u C O
« : p ct tr T J o T J p T-> ft) r t P o ti <Q tt at fit ct at n r t tr fit 3 o o 3 o C D 3 f t n ft) r t p o 3 *• • o P 1urr ft) r t C D ^ ft) 3 D i
v Q C D 3 C D r t ft) P « o tr ft> n ft> o el - C D n o H i f t tr a> m n C D ft) •

H 3 S * C D T J H o X P 3 p - r t ^ < r t O f t t r C D t r c u ( 0 C D ft) r t C D ft) ^ ft) < at H ft) ut ) C D 

### s p 3 D i C O T J C D C D D - « » o t r C O C D r t < a> D » T J C D ft) X n o r t o o 3 C D 0 H i
r t tr at H i o d H t r P C O C D c u H C D ft) ( 0 t r ft) C O C D D i o 3 C O d o 3 - o o 3 C O p * D i C D n ft) f t p o 3 C O ft) C OP.7 1

TABL E 8-1
. URBANIZE D AREAPOPULATIO NDAT AUSE D TO EXTRAPOLAT E MODE L RESULT S

Are a Chicag o Lo s Angele s Philadelphi a St . Loui s Total s Associate d

urbanize d area s 

### 2 2 26 2 5 3 2 

### 105 197 0

Pop . o f associate d urbanize darea s wit hpop . >200,00 0 38,894,36 5 26,339,24 9 20,553,52 3 17,350,71 2 103,137,84 9 198 7 Sensitiv e pop . o f associate d urbanize darea s 1,886,00 0 1,277,00 0 997,00 0 841,00 0 5,001,00 0



### B yusing an expression , whic hi s mathematicall yequivalen t t o the pe r perso n approac hdescribe d above , the desire d extra

polate d distribution s can b e calculate d directl yfro mthe exposur e distribution s whic har e calculate d fo r the four stud yareas . Tha t is , E(C ) can b e calculate d fromthe e . (C ) fo r the four stud yarea s b

yusing the expression , E(C ) =
wher e Tota l Populatio n (1970 ) Tota l Populatio n > 200,00 0 (197Q ) 4 E i= l f 

### i e 

### i ( C ) 

### (8-3 )
f = Tota l Pop , o f i-typ e urban area s i Tota l Pop . o f it hurban are a 8. 2 EXTRAPOLATIONRESULT S Th e result s o f th e nationwid e extrapolatio n ar e presente d i n Table s 8- 2 through8-12
. The firs t nin e table s can be divide d int o thre e set s o f thre e tables
. Table s 8-2 , 8-3 , an d 8- 4 presen t exposur e estimate s fo r a one-hou r averaging time
. Estimate s o f occurrence s during 198 7 among adult s wit hcardiovascula r diseas e o f 1-hour averag e C O exposure s abov e selecte d concentratio n value s during 198 7 unde r four alternativ e ai r qualit yassumption s ar e presente d i n Tabl e 8-2
. Estimate s o f the numbe r o f adult s wit hcardiovascula r diseas e i n the urban U.S . wh o woul d incur 1

- hou r averag e C O exposure s abov e the sam e se t o f selecte d
8- 4P.7 2



### TABL E 8-2 . ESTIMATE S OF OCCURRENCE S I N TH E CARDIOVASCULA

RADUL T URBA

N U.S . POPULATIO N O F 1-HOU

RAVERAGE C

OEXPOSURE S ABOVE SELECTE DCONCENTRATIO

N VALUE S UNDERALTERNATIVE AI RQUALITYASSUMPTION S

CONCENTRATION

1 EXCEEDE D1 (PPM ) I

50. 0 1 45. 0 I 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 I 9. 0 1 7. 0 1 0. 0 1

MAX . CONCENTRATION 1 ENCOUNTER S A T MAX . 1 9 PPM 8HR1EXE X11 2

10.20 0 1 21.90 0 I 168.00 0 1 915.00 0 I 6.620,00 0 1 27.700,00 0 I 102.000.00 0 I 370.000.00 0 1 45.900.000.00 0 1

36. 0 1 10.20 0 1 PPM

8H R1EXE X

4 5 10.20 0

21.90 0 124.00 0 359.00 0 1,700,00 0 6,570.00 0 31.300,00 0 88.500.00 0 296.000,00 0 873,000,00 0 ,900,000,00 0

49. 0 10,20 0 1 5 PPM

8H R1EXE X1

21,90 0 I 33,60 0 1 359,00 0 1 849,00 0 1 2,140.00 0 1 6,310.00 0 1 21,300.00 0 1 78,700.00 0 1 185.000.00 0 1 602,000.00 0 1 1,640,000.00 0 1 45.900,000.00 0 1

61. 5 1 10.20 0 1



### 8- 5P.7 3



### TABL E 8-3
. ESTIMATE S O F CARDIOVASCULA RADULT S INURBA

NU.S . WIT H 1-HOU

R AVERAG E C O EXPOSURE S ABOVE SELECTE D CONCENTRATION VALUE S UNDE RALTERNATIVE AI RQUALITYASSUMPTION S

1 CONCENTRATION 1 EXCEEDE D 1 (PPM )

1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0
I 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 PEOPL E A T MAXIMU M 9 PP M

8H R1EXE X11 2

10,20 0 1 21,90 0 1 157,00 0 1 535,00 0 1 1,290,00 0 1 2,820,00 0 1 4,390,00 0 1 5,140,00 0 I 5.240,00 0 1

36. 0 1 10.20 0 1 PP M

8HR1EXE X

10,20 0 21,90 0 113,00 0 348,00 0 691,00 0 1,290,00 0 2,900.00 0 4,290.00 0 5,030,00 0 5,240,00 0 5,240,00 0

49. 0 10,20 0 1 5 PPM

8HR1EXE X1

21,90 0 1 21,90 0 1 348,00 0 I 531,00 0 I 872,00 0 1 1,270,00 0 1 2,510,00 0 1 4,290,00 0 1 4,800,00 0 1 5,220,00 0 1 5,240,00 0 1 5,240,00 0 I

61. 5 1 10,20 0 1



### 8- 6-PO



### TABL E 8-4
. ESTIMATE S O F CARDIOVASCULARADULT S I NURBA NU.S . WHOS E MAXIMUM 1-HOU RAVERAG E C O EXPOSUR E OCCUR S I NSELECTE D CONCENTRATIO N RANGE S UNDE RALTERNATIV E AI RQUALIT YASSUMPTION S

1 CONCENTRATION 1 RANG E 1 (PPM )

1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0
t 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 i 0. 0 < C < = < c < =
< C < =
< C < = < c < = < c < =
< C < s < c < = < c < = < c < = < c < = < c < = 55. 0

50. 0 45. 0 40. 0 35. 0 30. 0 25. 0 20. 0 15. 0 12. 0 9. 0 7. 0

1 MAX . CONCENTRATION 1 PEOPL E A T MAXIMU M 9 PPM

8HR1EXE X

10,20 0 11,70 0 135,00 0 378,00 0 753,00 0 1,530,00 0 1,570,00 0 747,00 0 107,00 0

36. 0 10,20 0 1 2 PPM

8HR1EXE X

10,20 0 11,70 0 90,60 0 235,00 0 344,00 0 603.00 0 1.610,00 0 1.390,00 0 738,00 0 211,00 0 4,73 0

49. 0 10.20 0 1 5 PP M

8HR1EXE X1

326,00 0 I 184,00 0 1 341.00 0 1 401.00 0 t 1,240.00 0 1 1,770,00 0 1 510,00 0 1 426,00 0 1 18,60 0 1

61. 5 1 10,20 0 1



### 8- 7P.7 5



### TABL E 8-5 . ESTIMATE S O F OCCURRENCE S I N TH E CARDIOVASCULA

RADUL T URBA

N U.S . POPULATIO

N OF 8-HOU

RAVERAGE C

OEXPOSURE S ABOV

E SELECTEDCONCENTRATIO

N VALUE S UNDERALTERNATIVE AI RQUALITYASSUMPTION S

1 CONCENTRATION 1 EXCEEDE D 1 (PPM )

1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 ENCOUNTER S A T MAX . 9 PPM 8H R1EXE X|1 2 PPM

8HR1EXE X

1 429,00 0 200,00 0 I 4,290,00 0 6.340.00 0 1 54.900.00 0 63,500.00 0 1 322,000,00 0 45,900,000,00 0 1 45,900,000,00 0

14. 0 1 18. 5 23 2 1 23 2 1 5 PPM 8H R1EXE X1

104,00 0 1 3,830,00 0 1 29,200.00 0 1 206.000,00 0 1 835,000,00 0 t 45,900,000,00 0 1

23. 0 I 23 2 1



### 8- 8 

# JP.7 6



### TABL E 8-6 . ESTIMATE S OF CARDIOVASCULA RADULT S I

N URBA N U.S . WIT H8-HOU

R AVERAGE C

OEXPOSURE S ABOVE SELECTEDCONCENTRATIO N VALUE S UNDERALTERNATIV E AI RQUALITYASSUMPTION S

1 CONCENTRATION 1 EXCEEDE D 1 (PPM )

1 50. 0 1 45. 0 1 40. 0 I 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0

1 MAX . CONCENTRATION 1 PEOPL E AT MAXIMU

M 9 PPM 8HR1EXE X11 2 PPM 8HR1EXE X1 1 5

1 176.00 0 1 98.00 0 1 538.00 0 1 618,00 0 1 2,410,00 0 1 2,650,00 0 1 4,090,00 0 1 5,240,00 0 1 5,240,00 0 1

14. 0 1 18. 5 1 23 2 1 23 2 1 PPM 8HR1EXE X1

49,40 0 1 529,00 0 I 1,770,00 0 I 3,660,00 0 1 4,950,00 0 1 5,240,00 0 I

23. 0 t 23 2 1



### 8- 9P.7 7



### TABL E 8-7
. ESTIMATE S O F CARDIOVASCULARADULT S I NURBA NU.S . WHOS E MAXIMUM 8-HOURAVERAG E C O EXPOSUR E OCCUR S INSELECTE D CONCENTRATIO N RANGE S UNDE RALTERNATIV E AI RQUALIT YASSUMPTION S

1 CONCENTRATION 1 RANG E 1 (PPM )

1 50. 0 1 45. 0 1 40. 0 1 35. 0 1 30. 0 1 25. 0 1 20. 0 1 15. 0 1 12. 0 1 9. 0 1 7. 0 1 0. 0 < C < =
< C < =
< C < =
< C < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = < c < = 55. 0

50. 0 45. 0 40. 0 35. 0 30. 0 25. 0 20. 0 15. 0 12. 0 9. 0 7. 0

1 MAX . CONCENTRATION 1 PEOPL E A T MAXIMU

M 9 PPM8H R1EXE X11 2 PPM 8H R1EXEX1 1 5

1 176,00 0 1 98,10 0 i 362,00 0 1 520,00 0 1 1,870,00 0 I 2,030,00 0 1 1,680,00 0 1 2,590,00 0 1 1,160,00 0 1

14. 0 1 18. 5 1 23 2 1 23 2 I PP M 8H R1EXEX1

49,40 0 I 480,00 0 1 1,240,00 0 1 1,890,00 0 1 1,290,00 0 1 291,00 0 1

23. 0 1 23 2 1



### 8-1 0P.7 8



### TABL E 8-8 . ESTIMATE S OF OCCURRENCE S AMON GCARDIOVASCULA

RADULT S I

N URBA N U.S . OF COHbLEVEL S EXCEEDIN GSELECTE DVALUE S UNDERALTERNATIVE AI RQUALITYASSUMPTION S

1 COH B LEVE L 1 EXCEEDE D 1 (PERCENT )

1 3.7 0 1 3.5 0 1 3.3 0 1 3.1 0 1 3.0 0
I 2.9 0 1 2.7 0 1 2.5 0 1 2.3 0 1 2.1 0 1 2.0 0 1 1.5 0 1 1.0 0 1 0.0 0

1 MAX . COH B CONC . 1 ENCOUNTER S A T MAX . 9 PPM 8H RlEXE X11 2 PPM

8HRlEXE X

4 29 6 45,90 0 1 2

4 1 73 0 00 0 ,00 0 1 57 0

1 2,65 0 1 14,80 0 1 76,70 0 57 0 1 473,00 0 ,00 0 1 1,580,00 0 ,70 0 1 2,730,00 0 ,00 0 1 38,300,00 0 ,00 0 1 1,070,000,00 0 ,00 0 1 45,900,000,00 0

2.3 0 1 3.0 2 12 0 1 12 0 1 5 PPM 8H RlEXE X1

63 7 1 6,69 0 1 15,30 0 1 51.80 0 1 106,00 0 1 250,00 0 1 810.00 0 1 1.880,00 0 1 4,100,00 0 1 8,580.00 0 1 13,900,00 0 I 151.000,00 0 1 2,270,000,00 0 1 45,900.000,00 0 1

3.7 5 1 12 0 1 , 1



### 8-1 1P.7 9



### TABL E 8-9 . ESTIMATE S OF CARDIOVASCULA RADULT S I

N URBA N U.S . EXPERIENCIN

G COH bLEVEL S EXCEEDIN

GSELECTEDVALUE S UNDERALTERNATIV E AI RQUALITYASSUMPTION S

1 COH B LEVE L 1 1 EXCEEDE OI 1 (PERCENT ) I

1 3.7 0 1 1 3.5 0 1 1 3.3 0 1 1 3.1 0 1 1 3.0 0 1 1 2.9 0 1 1 2.7 0 1 1 2.5 0 1 1 2.3 0 1 1 2.1 0 1 1 2.0 0 I 1 1.5 0 1 1 1.0 0 1 1 0.0 0 1

1 MAX . COH B CONC . 1 1 PEOPL E A T MAXIMU

M 1 9 PPM 8H

RlEXEX11 2

28 1 1 . 5,50 0 1 22,20 0 1 742,00 0 1 4,140,00 0 1 5,240.00 0 1

2.3 0 1 12 0 1 PPM

8H RlEXE X1 1 5

28 1 1 1.25 0 1 6.23 0 1 42.00 0 1 217,00 0 I 452.00 0 I 660.00 0 I 2.100,00 0 I 5.090.00 0 I 5,240.00 0 1

3.0 2 1 12 0 1 PPM

8HRlEXE X1

34 5 1 3.20 0 1 6.60 0 I 25,80 0 1 58.20 0 1 132,00 0 1 308,00 0 1 506,00 0 1 732,00 0 1 1,060,00 0 1 1,350,00 0 I 3,480.00 0 I 5.180.00 0 1 5.240,00 0 I

3.7 5 1 12 0 1



### 8-1 2P.8 0



### TABL E 8-10 . ESTIMATE S OF CARDIOVASCULA RADULT S I

N URBA N U.S . WHOS E MAXIMU

M COH bLEVELOCCUR S I

N SELECTEDCONCENTRATIO

N RANGE S UNDERALTERNATIV

E AI RQUALITYASSUMPTION S

1 COH B LEVE L 1 RANG E 1 (PERCENT )

1 3.7 0 < 1 3.5 0 < 1 3.3 0 < 1 3.1 0 < 1 3.0 0 < 1 2.9 0 < 1 2.7 0 < 1 2.5 0 < 1 2.3 0 < 1 2.1 0 < 1 2.0 0 < 1 1.5 0 < 1 1.0 0 < 1 0.0 0 <

1 MAX . 1 PEOPL E C < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = c < = 10.0 0

3.7 0 3.5 0 3.3 0 3.1 0 3.0 0 2.9 0 2.7 0 2.5 0 2.3 0 2.1 0 2.0 0 1.5 0 1.0 0

COH B CONC . A T MAXIMU

M 9 PPM

8H RlEXE X

5 1 6 72 0 3,40 0 1,10 0 28 5 ,23 0 ,70 0 ,00 0 ,00 0 ,00 0

2.3 0 12 0 1 2 PPM

8H RlEXE X

28 5 97 2 4,99 0 35,90 0 175,00 0 235,00 0 208,00 0 1,440,00 0 2,990,00 0 149,00 0

3.0 2 12 0 1 5 PPM

8H RlEXE X1

35 1 1 2,86 0 1 3,40 0 1 19,20 0 I 32,40 0 1 74,10 0 I 175,00 0 I 198,00 0 I 227,00 0 1 327,00 0 1 291,00 0 1 2,130,00 0 I 1,700,00 0 I 63,00 0 1

3.7 5 1 12 0 1



### 8-1 3P.8 1



### TABL E 8-11 . PERCENTAGE OF CARDIOVASCULA RADUL T URBA

N U.S . POPULATIO

N EXPERIENCIN

GCOH bLEVEL S EXCEEDIN

GSELECTEDVALUE S UNDERALTERNATIV

E AI RQUALITYASSUMPTION S
COHbleve l exceede d (percent ) 3.7 0 3.5 0 3.3 0 3.1 0 3.0 0 2.9 0 2.7 0 2.5 0 2.3 0 2.1 0 2.0 0 1.5 0 1.0 0 0.0 0 9 ppm8 hr

1 ExE x

0.0 1 0.1 0 0.4 2 14.1 6 79.0 1 100.0 0 1 2 pp m8 hr 1 ExE x

0.0 1 0.0 2 0.1 2 0.8 0 4.1 4 8.6 3 12.6 0 40.0 8 97.1 4 100.0 0 1 5 pp m8 hr 1 ExE x 0.0 1 0.0 6 0.13 " 0.4 9 1.1 1 2.5 2 5.8 8 9.6 6 13.9 7 20.2 3 25.7 6 66.4 1 98.8 5 100.0 0



### 8-1 4P.8 2



### TABL E 8-12 . ESTIMATE S OF CARDIOVASCULA RADULT S I

N URBA N U.S . EXPERIENCIN

GCOH bLEVEL S EXCEEDIN

GSELECTEDVALUE S A

GIVE N NUMBEROF DAY S ASSUMIN G9 PPM/ 1 EXE

XSTANDARDI S ATTAINED

CONCENTRATION EXCEEDE D (PERCENT )

3.7 0 3.5 0 3.3 0 3.1 0 3.0 0 2.9 0 2.7 0 2.5 0 2.3 0 2.1 0 2.0 0 1.5 0 1.0 0 0.0 0 1 NUMBE RO F TIME S

DA YI 2- 4 DAY S 1 5-2 5 DAY S 1

28 1 1 1 1 5,50 0 1 1 1 21.80 0 1 1,12 0 1 I 372.00 0 1 656,00 0 1 909,00 0 1 673,00 0 1 2,570,00 0 1 25,300,00 0 1 > 2 5 DAY S 1

39,200,00 0 I 1,910,000,00 0 1



### 8-1 5P.8 3 ,



### concentration s unde r the same assumption s ar e presente d i n Tabl e 8-3
. Estimate s o f the numbe r o f urba n U.S . adult s whos e maximu m 1-hour averag e C O exposur e woul d occu r i n variou s concentratio n range s ar e presente d i n Tabl e 8-4
. Analogou s estimate s fo r 8-hour averag e C O exposure s ar e pre sente d i n Table s 8-5 , 8-6 , an d 8- 7 respectively
. Simila r esti

mate s fo r COHblevel s resulting fro mC O exposur e ar e presente d i n Table s 8-8 , 8-9 , an d 8-10
. Th e absolut e number s presente d i n Tabl e 8- 9 ar e presente d i n percentag e for mi n Tabl e 8-11
. Estimate s o f th e numbe r o f adult s wit hcardiovascula r diseas e wh o woul d hav e thei r bloo d COHblevel s elevate d abov e selecte d concentration s fo r variou s number s o f day s i f a n 8-hour averag e 9 ppm/ 1 ExE xstandar d wer e jus t me t i n al l urba n area s ar e presente d i n Tabl e 8-12
. The tabl e indicate s the frequencyo f repeate d pea k COHblevels
. The tabl e indicates , fo r example , tha t o f th e 5,50 0 adult s wit hcardiovascula r diseas e wh o ar e estimate d t o hav e thei r bloo d COHbleve l excee d 2. 1 percen t unde r the 9 ppm/ 1 ExE xstandard , non e woul d have i t occu r mor e than on e day
. 8. 3 UNCERTAINTYO F TH E NATIONWID E ESTIMATE S Th e uncertaint yo f the C O exposur e an d COHbestimate s mad e fo r the fou r bas e citie s wa s discusse d i n Sectio n 7.4
. The nation

wid e estimate s ar e eve n mor e uncertai n becaus e o f th e additiona l uncertaint yintroduce d b ythe extrapolatio n o f exposur e estimate s fo r thes e four citie s t o al l urban area s i n the U.S . Forma l mean s o f dealing wit hthe uncertaint yo f nationwid e estimate s ar e unde r development , bu t wer e no t availabl e fo r thi s analysis
. Hence , n o attemp t wa s mad e t o formall yrepresen t the uncertaint yo f th e estimate s presente d i n Sectio n 8.2
. Th e analy

se s discusse d i n Sectio n 7. 4 indicat e tha t uncertaint yi s alread y grea t a t the cit ylevel
. Tha t eve n greate r uncertaint yexist s i n the nationwid e estimate s shoul d b e recognize d whe n considering the estimate s presente d i n Table s 8- 2 through8-12
. 8-1 6P.8 4



### APPENDI XA
Sectio n 3. 1 describe s the developmen t o f activit ypattern s fo r the 5 6 populatio n subgroup s use d i n the NE Manalysis
. Ref

erenc e 2 o f Sectio n 3. 4 contain s thes e 5 6 activit ypatterns . Thi s appendi xcontain s thre e example s o f thes e activit ypatterns . A t the top o f eac htabl e i s a labe l indicating the age-occupatio n group , the subgroup , an d the percentag e o f the age-occupatio n grou p falling int o the subgroup
. I n the bod yo f the tabl e ar e hourl yassignment s t o locations , microenvironments , an d activit y level s fo r weekdays , Saturdays , an d Sundays
. Not e tha t the hou r designate d " 1 AM " i s the hou r whic hend s a t 1 AM .

A- lP.8 5

ACTIWIT TPATTERN S B TAGE-OCCUPATIO N SUBGilOU P
A- 0 6R0UP : 4

— Clerica l worker s SUB6ftOUP: 2 PC TI N SU86R0UP:2 6 £>A YO F WEE K

WEEKDAY S

SATURDA Y

SUNDA Y TIM E

O F DAY

A M

P M

A M

P M

A M

P M LOCATION/MI CRCENVIRONMENT/ACTIVITY
1

H 2 1

y 2 1

H 2 1

N 2 1

H 2 1

H 2 1 2

H 2 1

y 1 1

H 2 T

H 2 1

H 2 1

H 2 1 3

H 2 1

V 1 1

H 2 1

H 2 1

H 2 1

H 2 1 4

H 2 1

i i 1 1

H 2 1

H 2 2

H 2 1

N 2 1 5

H 2 1

y 1 1

H 2 1

H 2 1

H 2 1

H 5 3 6

H 2 1

y 3 1

H 2 1

H 2 1

N 2 1

H 4 2 7

H 2 1

H 2 1

H 2 1

H 2 1

H 2 1

H 2 1 8

H 3 1

H 2 1

H 2 1

H 2 1

H 2 1

H 2 1 9

y 1 1

H 2 1

H 2 1

H 3 1

H 2 1

H 2 1 LEVE L 1 0

y 1 1

H 2 1

H 2 2

H 2 1

H 2 1

H 2 1 B Y 1 1

y 1 1

H 2 1

H 5 2

H 2 1

H 3 1

H 2 1 H O 1 2

y 1 1

H 2 1

H 2 1

H 2 1

N 2 1

H 2 1

LOCATIO N CODES ; H-hoa e W=wor k MICROENVIRONMEN TCODES : 1 = wor k

o rschoo l 2 = bo« e o rothe r3 = transpor tvehicl e 4 s roadsid e 5 = outdoor s 6 - kitche n ACTIVIT YLEVELS : 1-lo u 2=aediu a 3=hig h

A- 2ACTIVIT YPATTERN S B YAGE-OCCUPATIO N SUBGROU P



### A- 0 GROUP : 6—Operative s ^Laborer s SUB6R0UP: 6 PC TI N SU86R0UP:1 6 DAYO F MEE K

hEEKOAY S TIM E

O FDA Y

AM

P M

SATURDA YA

M

P M

SUNDA Y A

M

P M LOCATION/MICRQENVIRQNNENT/ACTIVITY-LEVE L B YHOU R

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2

H 2 1

y 3 1

H 2 1

H 2 1

H 2 1

H 2 1 H 2 1

y 3 1

H 2 1

H 2 1

H 2 1

H 2 1 H 2 1

y 2 1

H 2 1

H 5 2

H 2 1

H 2 1 H 2 1



### u 3 1

H 2 1

H 2 1

H 2 1

H 2 1 H 2 1

y 3 1

H 2 1

H 2 1

H 2 1

H S 2 H 2 1

H 2 1

H 2 1

U 2 1

H 2 1

H 2 1 y 3 1

H 2 1

N 2 1

H 2 1

H 2 1

H 2 1 y 3 1

H
' 2 1

H 2 1

H 4 2

H 2 1

H 2 1 y 3 1

H 2 1

H 2 1

H 2 1

H 2 1

H 2 1 y 3 1

H 2 1

H 2 1
H 2 1

H 2 1

H 2 2 y 4 2

H 2 1

H 2 2
H 2 1

H 3 1

H 2 1 y 2 1

H 2 1

H 2 1

H 2 1

H 2 1

H 2 1

LOCATIO N CODES : H=hoa e W=*or k MICROENVIRONMEN TCODES : 1 - wor k

o rschoo l 2 - hoa e o rothe r 4 = roadsid e 5 = outdoor s ACTIVIT YLEVELS : 1-lo w2=aediu a 3-hig h 3 = transpor tvehicl e 6 - kitche n

A- 3ACTIVIT YPATTERN S 6 YA6E-OCCuPATIO N SUBGROU P

A - 0 6R0UP : 9—Housewive s SUBGROUP: 1 PC TI N SUBGROUP:4 2 DA YO F TIM E LOCATION/MICROENVIRONMENT/ACTIVITY-LEVE LB YHOU R MEE KO F DAY1 2 3 4 5 6 7 8 9 1 0 1 1 1 2

WEEKDAY S A M

P H

SATURDA YA

M

P M

SUNDA YA M

P H H

2 1

H 2 1

H 2 1

i f c 1

H 2 1

H 6 1 H 2 1

H 2 1

H 2 1

H 2 1

tt 2 1

H 2 1 H 2 1

tt 3 1

tt 2 1

H 5 2

H 2 1

H 2 1 H 2 1

H 2 1

H 2 1

• H 2 1

H 2 1

H 2 2 H 2 1

H 2 1

H 2 1

tt 2 1

tt 2 1

H 5 2 H 2 1

H 6 1

H 2 1

N 2 1

H 2 1

H 2 1 tt 6 1

tt 2 1

H 2 1

H 2 1

H 2 1

H 6 1 H 2 2

H 2 1

H 6 1

H 4 2

H 6 1

H 2 1 H 2 1

H 2 1

H 2 2

H 3 1

tt 2 1

H 2 1 H 2 1

H 2 1

H 2 1

tt 2 1

H 2 1

H 2 1 H 2 2

H 2 1

tt 2 1

H 2 1

H 2 1

H 2 1 H 5 1

H 2 1

tt 2 1

H 2 1

H 3 1

H 2 1

LOCATIO N CODES : H-hoa e y=wor k MICROENVIRONMEN TCODES : 1 = wor k

o rschoo l 2 = taoae o rothe r3 = transpor tvehicl e 4 = roadsid e S = outdoor s 6 - kitche n 

### ACTIVITYLEVELS : 1 = lo v 2=aediua 3-hig

h

A- 4P.8 8



### APPENDI XB COHOR T POPULATION S B

YSTUDYAREA
Cohor t descriptio n
A- 0 qrou

p Student s 18 + 

### 0 1

Professional s 

### 0 2

Sale s worker s 

### 0 3 Home



### NT a 

### C R 1

S R 5

C R 1

C R 1

S R 5

S R 5

C R 1

C R 1 Wor k NTa 

### C R 1

S R 5

C C 2

S C 6

C C 2

S C 6

C C 2

S C 6 Sub

grou p 

### 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 5 1 2 3 4 5 Chicag o

19,31 6 37,79 2 9,23 8 17,63 6 5,89 7 11,53 8 2,82 0 5,38 4 170,39 3 76,13 3 79,75 8 36,25 4 11,84 5 5,29 3 5,54 5 2,52 0 47,28 2 21,12 6 22,13 2 10,06 0 8,80 6 3,93 4 4,12 2 1,87 4 33,25 0 16,23 8 3,86 6 6,95 9 17,01 1 2,31 2 1,12 9 

### 26 9 48 4 1,18 3 Cohor t population

Phila

delphi a 4,23 9 8,29 3 2,02 7 3,87 0 17,38 7 34,01 7 8,31 5 15,87 5 14,50 1 6,47 9 6,78 8 3,08 5 5,71 0 2,55 1 2,67 3 1,21 5 35,66 1 15,93 3 16,69 2 7,58 7 65,33 2 29,19 1 30,58 1 13,90 1 4,44 2 2,16 9 

### 51 7 93 0 2,27 3 1,74 9 

### 85 4 20 3 36 6 89 5 St . Loui s

3,75 3 7,34 4 1,79 4 3,42 7 5,33 4 10,43 6 2,55 1 4,87 0 13,36 4 5,97 1 6,25 6 2,83 4 3,48 9 1,55 9 1,63 3 

### 74 2 14,49 0 6,47 4 6,78 2 3,08 3 18,81 2 8,40 5 8,80 5 4,00 2 4,00 0 1,95 3 

### 46 5 83 7 2,04 6 1,04 4 

### 51 0 12 1 21 9 53 4 Los Angele s 17,26 1 33,77 1 8,25 5 15,76 0 61,32 6 119,98 5 29,33 0 55,99 3 41,75 9 18,65 8 19,54 7 8,88 5 31,50 3 14,07 6 14,74 6 6,70 2 40,36 6 18,03 6 18,89 5 8,58 9 263,14 0 117,57 3 123,17 2 55,98 7 11,36 4 5,55 0 1,32 1 2,37 8 5,81 4 8,57 3 4,18 7 

### 99 7 1,79 4 4,38 6 

### (continued ) B- lP.8 9

Cohor t descriptio n
A- 0 group Sale s worker s 0 3 (cont. )

Clerica l worker s 0 4 Hom e



### NT a 

### S R 

### 5

S R 

### 5

C R 

### 1

C R 

### 1

S R 

### 5

S R 

### 5 Wor k 

### NT a 

### C C 

### 2

S C 

### 6

C C 

### 2

S C 

### 6

C C 

### 2

S C 

### 6 Sub

group 

### 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 Chicag o

9,24 4 4,51 4 1,07 3 1,93 2 4,72 2 1,71 9 

### 83 9 20 0 36 0 87 9 141,16 3 65,54 0 22,68 7 10,08 3 2,52 0 10,08 3 9,81 3 4,55 6 1,57 7 

### 70 1 17 5 70 1 31,57 1 14,65 8 5,07 4 2,25 5 

### 56 4 2,25 5 5,88 0 2,73 0 

### 94 5 42 0 10 5 42 0 Cohor t populatio n Phila

delphi a 11,32 2 5,52 9 1,31 7 2,37 0 5,79 2 20,74 2 10,13 0 2,41 2 4,34 1 10,61 2 26,03 3 12,08 7 4,18 4 1,86 0 

### 46 5 1,86 0 10,25 0 4,75 9 1,64 7 

### 73 2 18 3 73 2 39,50 8 18,34 3 6,34 9 2,82 2 

### 70 6 2,82 2 72,38 0 33,60 5 11,63 3 5,17 0 1,29 3 5,17 0 St . Loui s

4,31 5 2,10 7 

### 50 2 90 3 2,20 8 5,60 2 2,73 6 

### 65 1 1,17 3 2,86 6 22,24 2 10,32 7 3,57 5 1,58 9 

### 39 7 1,58 9 5,80 6 2,69 6 

### 93 3 41 5 10 4 41 5 11,76 5 5,46 2 1,89 1 

### 84 0 21 0 84 0 15,27 4 7,09 2 2,45 5 1,09 1 

### 27 3 1,09 1 

### Lo

s Angele s 11,37 2 5,55 4 1,32 2 2,38 0 5,81 8 74,13 3 36,20 4 8,62 0 15,51 6 37,92 8 48,23 1 22,39 3 7,75 1 3,44 5 

### 86 1 3,44 5 36,38 5 16,89 3 5,84 8 2,59 9 

### 65 0 2,59 9 36,53 7 16,96 3 5,87 2 2,60 9 

### 65 2 2,60 9 238,17 5 110,17 5 38,27 8 17,01 3 4,25 3 17,01 3


### (continued )

B- 2o o 3 3 C at a.

C O i C O l- » ct TO

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!- • !- • r o c n »- • 4 ^ r o !- • c nt n 04»M04>i- i c o i—• i—• t o o o c n

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• 4 > iO Ct Ct <^3 *£t iO vo o o v

o o o cn

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. o o !- • t no o o o c o c n4 » v i c nv i !- • t o t nc o t o r o v iCraftsmen05. !-• o za

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i— • C O M C OV O0 0 v i c nv i v i »- • v o v o !— • t nv o C D v i c no o v o c nv o o oA-0groupHomeNTaWorkNTa

- 1 C O OC C C T O1ChicagoPhila-delphiaSt.LouisLosAngelesCohortdescriptionCohortpopulation

\o o 3 rt

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0 0 I 4 »Retired10

!-• ct za

ri ct TO

c nc n4 * c o r o !- •

ri 1— • 1— • 1— • r- i r o V I 1—

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r o•- • r o !- • r- i t o V Ov o t o VO v oo o o c o r o t o 4 a v | v o v Ov l v o ov o t o c nt nc n

r oI1 r o !-•ri C O CTl v l ri V I v i c nc o c nO t n t no o c

o 4 * to t o v | o 4» O 4 *

c n4= » 4 * 4 a *030000 0 oi— • v i c nc nc n t nC Do o r o r o r o r o 4 * !- • O 4 * o t nc o za

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i — • i— • r o4 a r o c nr o r o
ri 4 a 1— • v | v o 4 ^ t ov o r o

t o CO v l v o 4 * C O0 0 !- • r ov i o o t nv o r o

t o CO v l v o 4 * r ov i o v oo t o ro4 a r o c no oHousewives09

za

za

t or o !- •

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4 a CO o otnv o c oc n!- • o oro o O^O l

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r oc o t n4 * vo OCflslM4>4 > v oc no o t n4=

» •- • r or o t n4 a c nc n

i — • r o4 a v i c ni-

i t nt nv o O 4 * t n v i C Dc nv i c nv i r o M 4 > 4 » O l U l 4 a v j v l i—

• 4 a V OServiceworkers08

!- • ct 73

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as c n4 a t o r o i—

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o v or o •- • !- • t o c o v i o !- • o o r o v o c no o c n4 * 4 * t o

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t oc n!- • o v i c n v i c nc o r o v o v i t or o v o c nr o o ori V O V OO0 0 V O

ri ri ri r O t no r o t nr o t n v i o !- • o o r o v o t nv i t nt o c o i—

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ri 1— • ri 4 a c no o t o c no o o v i o o i- i r o o o o o t nt n4 a 0 0 c n4 a c nr- i r o 4 a r-

i c o

CO4 a )- • 4 a 0 0 c nC Dc nc o o o o i— • c nv i c nc ni-

i v i v o o o c nv o v i

i i — • c nv i i- i r o v i c n CT l 4 a ro 4 a 4 a i-

i 4 a v l 4 a v

o v j v o CO4 a cnr-

i 4= » 4 a I O4 a v l 4 a 4 a cnLaborers06(cont.)

c nc o 73

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r- i V I 0 0 !- • r o 0 0 0 0 tn4 a 4 a 0 0 4 a ro 0 4 a 0 II 4 a 0 0 C Ori CTl t O ri V O

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ri •— • ri r O O•- • 1— • t o 1— • 4 a !- • 4 a v o CO4 a 0 0 v oc n1— • r o c n4 a r oc n!- • r o c nc oA-0groupHomeNTaWorkNTa

x »

- JCO 0 c c c r 0 1ChicagoPhila-delphiaSt.LouisLosAngelesCohortdescriptionCohortpopulation

C OP.9 2

Cohor t descriptio n
A- 0 grou

p Retired 1 0 (cont. )

Children < 5 

### 1 1

Childre n 5-1 7 

### 1 2 Home



### NT a 

### S R 

### 5

C R 

### 1

S R 

### 5

C R 

### 1

S R 

### 5 Work 

### NT a 

### S R 

### 5

C R 

### 1

S R 

### 5

C R 

### 1

S R 

### 5 Sub

grou p 

### 1 2 3 4 5 6 1 2 3 4 1 2 3 4 1 2 3 4 5 6 1 2 3 4 5 6 Chicag o

3,27 7 3,93 3 3,27 7 4,91 6 

### 65 5 32 7 10,56 2 10,05 9 10,05 9 19,61 5 8,07 6 7,69 1 7,69 1 14,99 7 67,59 4 4,82 8 8,44 9 31,38 3 2,41 4 6,03 5 51,68 3 3,69 2 6,46 0 23,99 6 1,84 6 4,61 5 Cohor t population

Phila

delphi a 42,41 1 50,89 3 42,41 1 63,61 7 8,48 2 4,24 1 15,85 1 15,09 6 15,09 6 29,43 8 35,02 1 33,35 3 33,35 3 65,03 9 117,28 9 8,37 8 14,66 1 54,45 5 4,18 9 10,47 2 284,61 6 20,33 0 35,57 7 132,14 3 10,16 5 25,41 2 St . Loui s

10,83 6 13,00 3 10,83 6 16,25 4 2,16 7 1,08 4 10,49 4 9,99 5 9,99 5 19,48 9 10,50 6 10,00 6 10,00 6 19,51 1 82,69 0 5,90 6 10,33 6 38,39 1 2,95 3 7,38 3 91,29 4 6,52 1 11,41 2 42,38 7 3,26 1 8,15 1 

### Lo

s Angele s 112,63 1 135,15 7 112,63 1 168,94 6 22,52 6 11,26 3 24,30 4 23,14 6 23,14 6 45,13 5 113,15 1 107,76 3 107,76 3 210,13 7 149,88 1 10,70 6 18,73 5 69,58 7 5,35 3 13,38 2 905,87 9 64,70 6 113,23 5 420,58 7 32,35 3 80,88 2

B- 5P.9 3



### APPENDI XC DISCUSSIO

NO F AI R QUALITYINDICATOR S USE D INTH E NE MANALYSI S AN D ESTIMATE D CONCENTRATION S USE D INTH E REGULATOR YANALYSI S

Anumbe r o f reviewer s o f earl ydraft s o f thi s repor t have aske d ho wai r qualit yindicator s (AQI's ) use d i n the NE Manalyse s o f C O compar e wit hestimate d concentration s (EC's ) use d i n the regulatoryimpac t analysi s o f alternativ e C O NAAQS's . Thi s appen di xdiscusse s ho wEC' s ar e determine d an d wh ytheydiffe r fro

m AQI's . Fo r regulatoryimpac t analysi s purposes , EPAcharacterize s ai r qualit ylevel s i n urbanize d area s b ya singl e value
. Thi s value , the EC , i s determine d fro mexisting ai r qualit ydat a according t o the same criteri a tha t state s woul d us e t o determin e whethe r o r no t an are a attain s a propose d NAAQS . Thes e criteri a varyaccording t o the "form " o f the standard being analyze d an d the allowe d violatio n rate . I n the cas e o f CO , form s unde r con sideratio n includ e one-hou r an d eight-hou r dail ymaximu mstandard s wit hallowe d violatio n rate s o f on e an d five expecte d exceedance s pe r yea r ove r a thre e yea r period
. Th e E C fo r a give n urbanize d are a i s usuall ybase d o n ai r qualit ydat a fro

m the monito r whic hreporte d the highes t ai r qualit yvalue s ove r a two o r thre e yea r period
. According t o curren t EPAguidance , the E C mayb e determine d b yapplying the simpl e formul a 

# ( numbe r \ / allowe d \ o f year s J lexceedance ] + 1 (B-l ) analyzed / \ rat e J
t o a multi-yea r dat a se t fro m thi s monitor
. Thu s i f the permitte d exceedanc e rat e i s five an d thre e year s o f dat a ar e considered ,

C- lo

1 t o P
.

at r t r o 

# a H 3 H a v Q el - s ' C D O o H H at (f l TJ o 3 O
. H 3 v Q > O H H - 01 M p . 3 H - r t ( D D
. r t o r t t r at C A H - r t r o ( 0 d u C D D
. 3 O o H D i C D D i r t t r C D tr H - v Q t r C D (f l r t n o M ( D < C D H (f l • H 3 * C D (f l C D (- • C D O r t H O 3 O H i 3 O 3 H - r t O H (f l H i O H r t o H (f l H - 3 0) 3 P H t r P I 3 H - N C D D i p i H C D P i P i 3 D i H - D i C D 3 r t H - H i *< H - 3 v Q r t t r C D 3 O 3 H - r t O H S t r H - o tr rt C D 1 r t t r C D W n H i o H 0 ) o H - r t > < H - (f l D < C D r t C D H 3 H - 3 C D D
. t r • < p i 3 P M
r < N H - 3 i Q D i p i r t P > H i H O 3 p i «- • M 3 O 3 H - 1 3 P ) *< H C D TJ H C D (f l C D 3 r t D i H - H i H i C D H C D 3 r t 3 O 3 H - r t o H (f l •
r- 3 t r C D 3 o 3 H - r t O h d (A C D D i r t O D i C D r t C D 

# a H - 3 C D fit < at H
. p i v Q C D •
> ct tr H H D i H C D fit tn O 3 H - (f l r t t r P > r t P > 3 M n fi> ti D
. r t tr a> o o H rt C D (f l TJ O 3 D i H 3 v Q > O H D
. d H H - 3 v Q P * (f l H 3 v Q M C D

• < C D P i H 3 P > * < D i P - H i H i C D h (f l H - v Q 3 H - H i H O P i 3 r t H K : H I M O 3 r t 3 * C D el - s ' H C D C D K C D P ) H •9 . r Q ^ P fit M H - r t K H » 0 h p i ( A H 3 v Q H C D K C D P ) h *- ^ I-*
. v o v l v l ^ I - 1 VO v l 0 0 ^ O H M v o v l VO "— '

. > H H 

## • 8 p i H " H - r t
• < p i M H - r t K : o < C D H el - s ' H C D C D

• < C D P i H (f l <— » (- • vo v l v l 1 v l v o — ^ £ tr H - H " C D > o M — (f l H C D T » H C D ( A C D 3 r t P > H - H H C D T 3 H C D (f l C D 3 r t H 3 v Q D i H - H i H i C D H C D 3 r t r t 3 C D

• a C D H H - o D i (f l • M O

- (f l H C D T J H C D (f l ( D 3 r t P i < C D H P > v Q C D Pi H H D i P > r t P » •
M 3 P i D i D i H - r t H O 3 ^ W O P > 3 D i > O H < P > M c : C D (f l P > H C D D i C D r t C D 

# u H 3 C D D i H i h o 3 D i P > r t fit > O H

- (f l P I h C D

r Q p p i 3 r t H M C D (f l O 3 O c : 

# a C D (f l H i H - r t r t O r t 3 - C D P TJ TJ C D H r t p i H - (- • (f l O H i H i H - r- « M C D D i 1 3 t d o — (f l p i H C D c r p i u i C D D i O 3 o c r (A C D V C D D i < p i H " d C D (f l H i H O 3 H - 3 O O 3 TJ l- 1 C D r t C D D i p i r t P > (A C D r t ( A • t- 3 3 * C D H C D P i H C D P i 3 0 § t r C D H o H i n C D P i (A 0 3 (f l H i o H (1 1 C o 3 * M P > H v Q C D D i H - H i H i C D H C D 3 O C D (f l • 3 o H C D r t 3 * P i 3 (- • O TJ C D H O C D 3 r t •

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### the NE Manalysis
. Becaus e n o mor e than si xsite s (on e pe r neigh

borhoo d type ) ar e use d t o represen t C O level s acros s a NE Mstud y are a an d becaus e the boundaryo f the stud yare a i s smalle r than the corresponding urbanize d area , the monito r use d fo r determining the AQ I i s ofte n differen t fro mtha t use d t o determin e the EC .

C- 3P.9 6



### TABL E C-1
. ESTIMATE D CONCENTRATION S (EC'S ) DEVELOPE D B YEP AAN D CORRESPONDINGAI RQUALIT YINDICATOR S (AQI'S ) FRO MTABL E 5- 6

(concentration s i npart s pe r million )

Studyare a Chicag o Los-Angele s Philadelphi a St . Loui s 1-haverag e value ,

1 expecte dexceed
. E C 30. 9 37. 8 32. 9 27. 9 AQ I

24. 9 31. 4 19. 2 22. 8 8- hrunning averag e va l 1 expecte dexceed
. E C 18. 0 24. 4 14. 7 17. 0 AQ I

. . 15. 6 20. 3 14. 3 14. 7 j e 

### 5 expecte dexceed
. E C 14. 0 17. 0 11. 0 10. 0 AQ I

12. 9 16. 1 9. 9 10. 9



### C- 4P.9 7

TECHNICA LREPOR

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4 . TITL E AN D SU8TITL E Th e NAAQ

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7 . AUTHOR(S ) Ted Johnso n an d Ro

yA

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