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PRELIMINARY COMMENT S ONLEA D EXPOSUR E b y Ralp hL . Keeney , Rakes hK . Sarin , an d Rober t L . Winkle r Thi s documen t i s i n respons e t o a reques t t o commen t o n methodologie s fo r estimating bloo d lead concentration s i n selecte d populatio n groups . Th e inten t i s t o mak e suggestion s fo r developing , implementing , an d documenting a rationa l procedur e t o obtai n thes e desire d estimates , rathe r than t o complet e an effor t t o provid e reasonabl e estimates . I n considering thi s document , i t i s essentia l t o realiz e tha t al l o f the suggestion s ar e base d o n a limite d effor t an

d henc e shoul d b e considere d preliminary . Th e repor t i s organize d a s follows . Sectio n 1 outline s ou r inten t i n a genera l mode l fo r th e exposur e analysi s fo r lead . Sectio n 2 present s sampl e calculation s base d o n informatio n i n the Pedc o document . Sectio n 3 present s genera l comment s o n extension s an d additiona l informatio n neede d fo r a n actua l implementatio n o f the exposur e analysis . Th e repor t i s summarize d i n Sectio n 4 . Tw o reference s ar e frequentl ycite d i n thi s report . Th e "Pedc o document " refer s t o the pape r title d "Scenari o fo r analysis " whic hwa s sen t t o u s along wit hth e Ma y18 , 198 4 lette r b yDr . Ro n Whitfield . Th e "criteri a document " refer s t o the Environmenta l Protectio n Agency' s four-volume repor t title d "Ai r qualit ycriteri a fo r lead. "P. 3

Sectio n 1 . Exposur e Analysi s fo r Lea d

I n suggesting possibl e alternative s fo r th e exposur e analysi s w e define d the following objectives : 1 . Th e outpu t o f th e exposur e analysi s shoul d b e a meaningfu l inpu t t o an ysubsequen t health-ris k assessment . 2 . Th e inpu t requirement s o f th e exposur e analysi s shoul d b e easil y availabl e (fro

mpas t studie s o r experts ' opinions ) an d th e exposur e mode l shoul d b e easil yimplementabl e o n a microcomputer . 3 . Th e mode l shoul d b e genera l enoughs o tha t the result s fo r a specifie d populatio n grou

p (e.g. , childre n 1- 2 year s old ) i n a give n locatio n (e.g. , Minneapolis ) can b e easil ygenerated . 4 . Th e assumption s mad e i n th e mode l shoul d b e explici t s o tha t whe n additiona l informatio n become s availabl e the mode l can b e update d easily . Thes e objective s led u s t o examin e th e leve l o f aggregatio n tha t th e exposur e mode l shoul d have . Th e highes t leve l o f aggregatio n i s t o wor k directl ywit hbloo d lead levels , perhap s througha regressio n mode l o r othe r statistica l mode l wit ha fewappropriat e independen t variables . Th e coefficient s o f the mode l coul d b e obtaine d fromexisting studie s o r inferre d fromresponse s o f experts . A t the othe r extreme , th e lowes t leve l o f aggregatio n i s t o mode l al l o f the variou s step s leading t o th e fina l bloo d lead levels . Fo r example , i n th e approac htake n b yBille r e t a l , eac hcohor t grou p i s trace d through a variet yo f microenvironment s o n a n hou r t o hou r basis , some sor t o f simula

tio n mode l i s use d t o predic t lead exposure , an d a detaile d physiologica l mode l i s use d t o obtai n the >• oo d lead level s o n a dayt o da ybasis . W e believ e tha t a n i " : * ediat e leve l o f aggregatio n mayb e appropriate . Ou r curren t though t *.. s ' . woul d us e on e mont ha s a n averaging time . Sinc e the hal f lif e o f b*l » *-*.'• indicate d i n th e criteri a documen t t o b e betwee n 2 0P. 4

an d 4 0 days , a mont hmayb e a reasonabl e perio d t o conside r t o examin e the fluctuation s i n bloo d lead levels .P. 5

Sectio n 2 . Sampl e Calculation s fo r Lea d Exposur e Ther e ar e two distinc t component s addresse d t o calculat e lea d exposure . Submode l 1 concern s lead consumptio n an d Submode l 2 concern s bloo d lead level s give n consumption . Thi s sectio n consider s bot han d illustrate s th e calculation s necessaryt o estimat e lead exposur e using dat a fromthe Pedc o an d criteri a documents . W e describ e th e approac hi n simpl e step s indicating th e assumption s tha t ar e made . Mor e detaile d comment s o n man yo f th e assumption s ar e foun d i n Sectio n 3 . SUBMODE L 1 . LEA

D CONSUMPTION Ther e ar e si xstep s i n Submode l 1 . W e wil l illustrat e calculation s using on e populatio n grou p o f interest , namel yblac k childre n betwee n 1 an d 2 year s o f ag e wh o ar e i n povert yan d liv e i n home s buil t afte r 195 0 i n th e Minneapolis

St . Pau l area . Step 1 . Thi s group , whic hcontain s 65 1 individual s according t o th e Pedc o document , shoul d firs t b e divide d i n term s o f the representativ e ai r qualit ytha t theyar e expose d t o a s indicate d b ythe locatio n o f th e ai r qualit ymonitor s (ma p code s At o K) . Sinc e the ai r qualit ymonitor s ar e limite d i n an ycity , an assumptio n abou t th e demographi c distributio n mus t b e made . W e us e a naiv e assumptio n fo r thi s illustratio n tha t the 65 1 childre n ar e evenl ydistribute d acros s th e monitor s i n term s o f exposure . Thus , w e can sa ytha t approximatel y6 0 childre n i n our populatio n grou p ar e expose d t o th e ai r qualit yindicate d b yth e monito r corresponding t o eac hmap code . Not e tha t thi s calculatio n doe s no t requir e tha t a populatio n grou p actuall yliv e i n the vicinit yo f th e locatio n o f a n ai r qualit ymonitor . W e onl yrequir e a n assumptio n tha t a give n locatio n ha s th e same ai r qualit ya s th e ai r qualit y indicate d b

ya particula r monitor . Amor e realisti c assumptio n migh t b e t oP. 6

assign a highe r proportio n o f th e populatio n i n povert yt o location s nea r eithe r a smelte r o r a batteryplan t (e.g. , map code s F o r K) . Additiona l demographi c informatio n woul d b e valuabl e i n thi s regard . Th e inhalatio n level s o f lead wil l depen d o n the numbe r (or proportion ) o f peopl e expose d t o variou s ai r qualit ylevel s i n eac ho f th e months . I n ou r example , thi s distributio n fo r eac hmont hi s give n fromth e quarterl y informatio n i n th e Pedc o document . Fo r th e firs t month , th e concentratio n 3 range s from0.2 2 t o 1.6 4 yg/ m. Fo r ou r subsequen t illustratio n w e wil l onl yus e 6 0 childre n expose d t o map cod e Aai r quality . Th e lead concentratio n exposur e fromai r fo r thes e childre n fo r 1 2 month s o f 198 1 is , respectively , 0.41 , 0.41 , 0.41 , 0.37 , 0.37 , 0.37 , 0.37 , 0.37 , 0.37 , 0.56 , 0.56 , an d 0.56 , measure d i n yg/m 3 (se e Pedc o Tabl e 2) . Step 2 . Base d o n the ai r qualit yexposur e i n Step 1 , th e tota l amoun t o f lead inhale d pe r da yi s calculated . Fo r a give n mont hthi s dail yamoun t wil l remai n constan t an d thu s i t i s a n averag e amoun t fo r the month . W e mak e the following assumptions :

• th e rati o o f indoo r t o outdoo r ai r qualit y(Tabl e 7- 7 i n th e criteri a document ) i s 0. 5 3

• the amoun t o f ai r inhale d i s 1 0 m/da y

• th e indoo r an

d outdoo r time ar e 2 0 hours/dayinsid e and 4 hours / da youtsid e

• seasona l factor s (e.g. , bot hthe indoor/outdoo r activit ydivisio n an d the indoor/outdoo r ai r qualit yrati o mayvaryb yseason ) ar e ignore d fo r th e purpose s o f ou r simpl e example . Th e averag e lead inhale d pe r dayca n no wb e calculated . Fo r the 6 0 childre n i n ou r example , thi s calculatio n fo r mont h1 i sP. 7

3 3 Lead inhale d (yg/day ) = 1 0 m/day[(2 0 hrs . insid e x0.4 1 yg/ mai r qualit y x0. 5 inside/outsid e ai r qualit yratio ) + ( 4 hrs . outsid e x0.41)]/2 4 hrs . = 2. 4 yg/day . Th e result s fo r al l 1 2 month s o f 198 1 are , respectively , 2.4 , 2.4 , 2.4 , 2.1 , 2.1 , 2.1 , 2.1 , 2.1 , 2.1 , 3.2 , 3.2 , an d 3. 2 yg/day . Step 3 . I n thi s step w e estimat e th e amoun t o f lead ingeste d i n th e for mo f dusts . Th e categorie s o f dust s ar e househol d dusts , soi l dusts , stree t dusts , an

d occupationa l dusts . Th e dus t lead concentratio n wil l correlat e t o some exten t wit hai r lead concentratio n bu t additionall ywil l depen d o n famil ygardens , interio r lead paint , distanc e fromth e residenc e t o a smelter , etc . W e recommen

d tha t a fewconvenien t (fro mthe standpoin t o f dat a collection ) categorie s b e use d t o arriv e a t th e dus t lead concentratio n tha t a populatio n i s expose d to . I n our exampl e w e assume the bas e cas e fromTabl e 7-2 3 o f the criteri a document . W e als o assume the amoun t o f dus t ingeste d i s th e same a s i n Tabl e 7-2 3 fo r the 6 0 children . Thus , th e calculatio n fo r th e dus t lea

d consume d i s a s follows :

Typ e o f dus t Househol d dus t Stree t dus t Occupationa l dus t Dus t lead concentratio n yg/ g 30 0 9 0 15 0 Dus t inge s

g/da y 0.0 5 0.0 4 0.0 1 ted Dus t lead

consume d yg/da y 1 5 4. 5 1. 5 21. 0 (Not e tha t th e origina l Tabl e 7-2 3 ha s a n inconsistenc yi n th e stree t dus t calculatio n sinc e 90(0.04 ) =3.6 . Thi s inconsistenc yshoul d b e resolved , bu t w e d o no t hav e sufficien t informatio n t o resolv e it. )P. 8

Using informatio n fromTabl e 7-2 5 o f th e criteri a document , notic e tha t fo r the 6 0 childre n living i n th e household s nea r a smelte r (represented b y map code s F an

d G) , ther e mayb e a n increas e i n dust s t o 25,00 0 yg/g , an d fo r the childre n living i n house s buil t befor e 1950 , the househol d dust s wil l ris e t o 200 0 yg/ g becaus e o f interio r lead paint . Ther e wil l b e simila r increase s du e t o famil ygardens , occupation , etc . I f the lead concentratio n i s correlate d wit hai r quality , the n th e monthl y average s o f the dus t lead consume d wil l varyove r th e period . Step 4 . W e no wcomput e th e lead ingeste d fromfood and milk . Thi s con sumptio n mayb e assume d constan t fo r some well-define d categorie s (e.g. , rura l vs . urban , poo r vs . non-poor , chil d vs . adult , mal e vs . female) . Fo r ou r exampl e the lea

d ingeste d fromfood an d mil k wil l b e 28. 7 yg/da y(Tabl e 7-1 8 o f th e criteri a document) . Step 5 . Th e amoun t o f lead ingeste d fromwate r an d beverage s can als o b e assume d t o b e constan t fo r some well-define d categories . W e us e Tabl e 7-2 1 i n the criteri a documen t t o assume tha t the 6 0 childre n i n ou r exampl e consume 11. 2 yg/dayo f lead fro mthi s source . Step 6 . Th e amoun t o f lea d inhale d pe r da

yan d ingeste d pe r daycan no w b e obtained . I n ou r exampl e th e amoun t o f lead inhaled/da yfo r eac ho f th e 1 2 month s i s give n i n Step 2 . Th e amoun t o f lead ingeste d wil l b e 60. 9 yg/day whic hi s obtaine d b yadding th e result s i n Step s 3 , 4 , an d 5 . Thi s i s assume d t o remai n constan t throughou t th e yea r fo r thi s exampl e calculation . SUBMODE L 2 . BLOO D LEA D CONTEN

T S o fa r w e hav e illustrate d calculation s (i n Step s 1-6 ) fo r the dail y amoun t o f lead inhale d an d ingeste d fo r th e 1 2 month s i n a year . I t i s assume d tha t withi n a mont hther e i s n o variatio n i n th e inhalatio n o r ingestio n amounts . A t thi s poin t w e sugges t tw o alternative s t o comput e bloo d leadP. 9 8 level s (yg/dl ) fo r eac ho f th e 1 2 months . Befor e w e discus s thes e alternatives , w e provid e a genera l observatio n tha t the degre e o f uncertaint yi n th e dat a reporte d i n the criteri a documen t i s sufficien t t o warran t th e explici t us e o f exper t opinio n t o complemen t th e dat a use d fo r th e modeling . I n Submode l 1 , th e dat a ar e reasonabl ysufficien t s o tha t th e explici t quantificatio n o f the judgment s o f expert s can b e kep t a t a minimum , althoughsuc hinformatio n can stil l b e veryuseful . W e als o sugges t tha t fo r some healt heffect s i t mayb e desirabl e t o encod e expert s b yproviding themwit hsome initia l condition s abou t a populatio n grou p an d the lead inhalatio n an d lead ingestio n amount s calculate d i n Step s 1-6 . W e no wdiscus s two alternativ e approache s tha t relat e the lead inhalatio n an d th e lead ingestio n wit hth e bloo d lead levels . Physiologica l Modeling Approac h I n thi s approac hw e wil l assume tha t the bloo d lea d i s i n dail yequilibriu m wit hothe r compartment s an d the bloo d lea

d level s fluctuat e onl ymonthl y(thus , ther e wil l b e 1 2 bloo d lead level s fo r a n individua l i n a year) . Adiagrammati c representatio n o f thi s mode l i s give n i n Figur e 2 . B ymaking assumption s abou t th e depositio n rate s an d absorptio n rate s a s show n i n the figure , w e ca n calculat e the tota l lead absorptio n (yg/day ) fo r a membe r o f a populatio n group . Asampl e calculatio n fo r th e 6 0 childre n i n ou r exampl e wil l b e a s follows : [2.4y g (dailyinhalation ) x0.3 5 (depositio n i n lowe r airways ) x1 (absorptio n rate) ] + [(60. 9 + 0.1 5 x2.4 ) (dailyingestion ) x0. 1 (absorptio n rate) ] =6.9 5 yg/day . Not e tha t thi s numbe r mayb e considerabl yhighe r i f th e absorptio n rate s give n i n Tabl e 10- 3 o f th e criteri a documen t ar e used . Thus , th e abov e calculatio nP.1 0

i s a sampl e calculatio n an d th e numerica l figur e mayno t b e realistic . I f w e assume a 50 % excretio n rate , the n a dail yretentio n o f 3.4 7 yg/day wil l b e predicte d fo r eac ho f th e 6 0 children . W e no whav e t o mak e severa l assumption s abou t th e intercompartmenta l transpor t o f lead , th e half-lif e o f bloo d lead (e.g. , 3 0 days) , the time i t take s t o reac ha ne wequilibriu mwit han increas e o r decreas e i n lea d intake , an d th e bloo d volume . W e ca n the n comput e o n a mont ht o mont hbasi s the ne w bloo d lead levels . Thi s par t o f th e mode l canno t b e constructe d fromth e informatio n i n th e criteri a document . W e believe , however , tha t wit ha modes t amoun t o f informatio n fromexperts , i t i s possibl e t o buil d a simpl e mode l tha t can provid e reasonabl e estimate s o f averag e monthl ybloo d levels . Correlationa l Approac h I n thi s approac hthe relationship s obtaine d fromthe observationa l an d experimenta l studie s reporte d i n Chapte r 1 1 o f th e criteri a documen t ar e use d t o correlat e bloo d lead wit hth e inhale d lead an d ingeste d lead . Th e model s fo r inhale d lead an d ingeste d lead wil l b e discusse d separately . Inhale d Lead . A s show n i n Figur e 3 , w e nee d a relationshi p betwee n bloo d lead leve l (y ) an

d inhalatio n lead amoun t (z) . Th e studie s hav e provide d dat a o n the relationshi p betwee n yan d ai r lead concentratio n (x) , sa yy= f(x) . Fo r example , f mayb e linea r wit ha slop e o f 1.9 7 + 0.3 9 fo r childre n an d 1.6 4 + 0.2 2 fo r adults . I n ou r Step s 1 an d 2 w e hav e establishe d a relationshi p betwee n z an

d x , sa yz = g(x) . I t i s therefor e possibl e t o deriv e a relation

shi p betwee n yan

d z , sa yy= h(z) . W e recommend tha t exper t opinio n b e sough t t o establis hth e relationshi p betwee n yan

d z . O f course , th e result s o f experimenta l an d observationa l studie s shoul d b e use d t o provid e a benchmark . Thi s approac hmayb e easie rP.1 1 1 0

t o implemen t than seeking exper t opinio n o n th e relationshi p y= f(x) . Thi s i s becaus e ther e ar e man ymor e intervening variable s tha t influenc e f a s compare d wit hh . I n ou r exampl e th e contributio n o f inhale d ai r t o bloo d lead wil l b e 0.8 2 yg/d l (assuming f i s linea r wit ha slop e o f 2) . Ingeste d lead . Th e bloo d lead contributio n b yingestio n i s divide d int o foo d an d wate r an

d dus t ingestion . Arelationshi p betwee n lead intak e an d bloo d lead leve l mus t b e established . I f w e assume a linea r relationshi p bewtee n bloo d lead leve l an d dietaryleve l intak e wit ha slop e o f 0.0 6 (se e th e criteri a document , pag e 11-160) , the n fo r ou r exampl e th e incrementa l bloo d lead contributio n wil l b e compute d a s

0.0 6 x(28. 7 + 11.2 ) = 2. 4 yg/d l sinc e food an

d wate r intake s wer e 28. 7 an d 11. 2 yg/day , respectively , from Step s 4 an

d 5 . Finally , th e relationshi p betwee n soi l an d dus t lea

d an d bloo d lead i s use d t o comput e the incrementa l bloo d lead contributio n fromthi s source . Again , i f w e assume th e linea r relationshi p wit ha slop e o f 1. 8 yg/d l (se e th e criteri a document , pag e 11-161) , the n fromStep 3 w e us e th e dus t lead concentratio n o f 54 0 yg/ g o r 0.5 4 mg/ g an d thu s th e bloo d lead contributio n wil l b e 1. 8 x0.5 4 = 0.97 2 yg/dl . Th e tota l bloo d lead concentratio n fo r eac ho f th e 6 0 childre n i n ou r exampl e wil l b e

0.8 2 (inhalatio n contribution ) +2. 4 (food an d beverag e contribution ) + 0.97 2 (dus t contribution ) = 4.19 2 yg/dl .P.1 2 1 1 Notic e tha t the dus t lead concentratio n i s a variabl e wit ha larg e range . I f w e assume 200 0 yg/ g concentratio n (whichmayb e reasonabl e fo r a n inne r zon e o f the city) , the n th e bloo d lead concentratio n fo r the 6 0 childre n wil l b e predicte d t o b e 6.8 2 yg/dl . I n orde r t o ge t the estimate s o f th e percentag e o f bloo d lead level s fo r th e indicate d populatio n grou p o f black s age d 1-2 , additiona l calculation s simila r t o thos e abov e nee d b e completed . First , a se t o f calculation s fo r eac ho f the ai r qualit ymonitor s B throughK need s t o b e completed , assuming 6 0 individual s i n eac hgroup . Next , simila r calculation s fo r the othe r black s age d 1-2 , indicate d i n Tabl e 1 o f the Pedc o document , nee d t o b e completed . Thes e group s ar e seve n individual s i n povert yi n pre-195 0 housing , 5 6 individual s no t i n povert yi n pre-195 0 housing , an d 193 5 individual s no t i n povert yi n post 195 0 housing . Th e resulting bloo d lead concentration s o f thes e thre e group s nee d t o b e combine d wit hthe informatio n fromthe 65 1 individual s i n povert y living i n post-195 0 housing t o provid e th e require d bloo d lead distribution s fo r black s aged 1-2 . Th e sampl e calculation s presente d i n thi s sectio n utiliz e poin t estimate s o f the variou s parameter s i n th e model . T o ge t a mor e realisti c distributio n o f bloo d lead level s fo r particula r groups , uncertaint yabou t th e parameter s shoul d b e incorporate d explicitl yint o th e analysis . T o illustrat e thi s notion , conside r on e parameter , th e amoun t o f time spen t indoor s pe r day . W e use d an estimat e o f 2 0 hour s pe r dayindoor s i n ou r calculations . However , th e averag e numbe r o f hour s spen t indoor s wil l varywithi n the grou p o f 6 0 children . Suppos e tha t thi s variatio n coul d b e represente d b yth e following probabilit ydistribution : Averag e hour s insid e pe r 

### 2 4 2 2 2 0 1 8 1 6 

### da y Probabilit y



### 0. 2 0. 2 0. 3 0. 2 0. 1P.1 3 

### 1 2 Carrying ou t the calculation s o f th e averag e lead inhale d pe r da yfo r eac h o f the five possibl e value s o f the averag e numbe r o f hour s spen t insid e pe r day , w e arrive a t th e following distributio n fo r th e averag e amoun t o f lea d inhaled : Averag e lead inhale d (yg/day ) 2.0 5 2.2 2 2.3 9 2.5 6 2.7 3 Probabilit y 

### 0. 2 0. 2 0. 3 0. 2 0. 1 Thus , instead o f having a singl e figur e fo r the averag e amoun t o f lead inhale d pe r day , w e hav e a distribution . Give n ou r assumptions , w e woul d estimat e tha t 20 % o f our grou p o f childre n woul d inhal e a n averag e o f 2.0 5 yg/day , 20 % woul d inhal e a n averag e o f 2.2 2 yg/day , an d s o on . I n a simila r manner , uncertaint yabou t an yo f th e parameter s i n th e mode l coul d b e introduce d an d include d i n th e analysis . Th e calculation s require d ar e o f the same natur e a s i n our simpl e exampl e withou t uncertainty . Th e numbe r o f calculation s require d wil l increas e rapidl ya s uncertaint yabou t mor e parameter s i s introduced , bu t thi s ca n b e handle d readil yo n a computer . Th e inten t o f th e sampl e calculation s i n thi s sectio n i s t o illustrat e th e leve l o f aggregatio n tha t w e recommend an d t o showthe type s o f calculation s tha t ar e involved . I n the nex t sectio n w e discus s th e assumption s i n mor e detai l an

d indicat e wha t sor t o f additiona l informatio n migh t b e helpfu l i n extending the model .P.1 4 •1 3 Sectio n 3 . Comment s abou t lead exposur e calculation s Thi s sectio n elaborate s o n man yo f the assumption s necessaryt o calculat e lead exposure . Th e comment s wil l b e place d i n a n orde r corresponding t o the orde r i n whic hth e assumption s wer e necessaryi n the sampl e calculation s i n Sectio n 2 . DISTRIBUTIONO F LEA D CONCENTRATION S INAI R Lead concentration s ar e onl ymeasure d a t selecte d monitors , ye t on e i s concerne d abou t exposur e everywhere . Thus , assumption s ar e necessaryabou t th e lead concentration s i n ai r everywhere . Th e exampl e calculation s assume d tha t the 1 1 monitor s eac hrepresente d 1/1 1 o f th e tota l are a o f exposure . However , two o f thos e monitor s wer e nea r batteryfacilitie s an d two nea r lead smelters . W e woul d expec t tha t th e proportion s o f tota l area s nea r suc hfacilitie s woul d b e les s than 2/1 1 i n eac hcase . I t would , therefore , seemreasonabl e t o mak e judgments , base d o n data , abou t the percentag e o f the tota l exposur e are a wit h characteristic s simila r t o eac ho f thos e represente d b ythe 1 1 monito r sites . I t i s importan t t o recogniz e tha t thi s assumptio n mus t alway s b e mad e eithe r implicitl yo r explicitly . T o assume tha t th e monitor s ar e completel yrepresen tativ e o f th e ai r qualit yo f a n entir e are a o f concer n i s simpl yon e o f th e man ypossibl e assumption s abou t ai r lead concentrations . DEMOGRAPHI C DISTRIBUTIONO F POPULATIONEXPOSE D Th e nex t ke yassumptio n woul d matc hindividual s i n a give n populatio n grou p wit hdifferen t ai r exposur e levels . Th e illustratio n assume s tha t th e 65 1 childre n i n th e grou p o f concer n wer e evenl yexpose d t o lead ai r concen tration s representativ e o f th e 1 1 monito r sites . I n fact , demographi c dat a ma yindicat e tha t certai n populatio n group s ma yb e mor e likel yt o liv e i n inne r cities , an

d henc e perhap s nea r batteryplant s o r lead smelters , than1 4

i n the suburbs , whic hwoul d presumabl yhav e differen t lea d ai r concentrations . Suc hdemographi c informatio n coul d b e utilize d i n proportioning a populatio n grou p among th e lead ai r concentration s ove r the are a o f concern . PERSONAL FACTOR S AFFECTIN GLEA D EXPOSUR E Ther e ar e a numbe r o f persona l factor s affecting inhale d lead exposure , a s indicate d i n Step 2 o f th e exampl e i n Sectio n 2 . Theyconcer n the rati o o f indoo r t o outdoo r ai r quality , th e amoun t o f ai r inhaled , th e time spen t indoor s an

d outdoors , an

d the dependenc e o f thes e o n seasona l factors . I n th e exampl e calculation , w e assume d thes e factor s wer e the same fo r eac ho f the individual s o f th e populatio n grou p o f concer n an

d tha t theydi d no t varywit h th e seasons . However , w e coul d clearl ymak e assumption s abou t the percentag e o f a give n populatio n spending differen t amount s o f time indoor s an d outdoor s an d varying thi s wit hseasons . W e coul d als o assume a distributio n o n th e rati o o f indoo r t o outdoo r ai r quality . Th e result s o f suchassumptions , whic hcoul d b e base d o n variou s dat a sources , woul d b e a probabilit ydistribu

tio n fo r th e monthl yaverage s o f dail ylead inhale d fo r eac hpopulatio n grou p o f interest . EXPOSUR E FROMLEA

D CONCENTRATION S I NDUS T Th e exampl e assume d tha t al l individual s i n the populatio n grou p o f interes t wer e expose d t o th e same amoun t o f lead concentration s i n dus t an d tha t theyconsume d th e same amoun t o f lead pe r da ya s a result . W e migh t expec t tha t the lead concentration s i n dus t woul d b e correlate d wit hth e lead concen tration s i n air . Specifically , fo r instance , th e lead concentration s i n dus t a t schoo l playground s nea r verybus ystreet s mayb e muc hhighe r than elsewhere . Thes e type s o f consideration s coul d b e take n int o accoun t along wit hth e proportio n o f th e populatio n grou p o f interes t spending time i n suc hlocation s1 5

i n orde r t o calculat e inhalatio n o f lead i n dust . Othe r factors , sucha s whethe r the parent s i n a househol d wor k i n a lead smelte r o r a batteryplant , fo r instance , greatl yaffec t th e lead dus t i n th e home , a s doe s th e proximit y o f the home td suc hfacilities . B ymakin g assumption s abou t the proportio n o f a give n populatio n living wit hdifferen t characteristics , suc ha s proximit y t o thes e facilities , w e coul d agai n calculat e a probabilit ydistributio n fo r the averag e dail ylead consume d fo r a give n populatio n group . EXPOSUR E T O LEA

D DU E T O FOOD AND WATE R I n the exampl e calculation , w e assume d tha t al l individual s i n a give n grou p had th e same amoun t o f lead ingeste d du e t o foo d an d wate r consumption . B yassuming a distributio n fo r food an d wate r consume d fo r a give n populatio n group , w e woul d agai n ge t a probabilit ydistributio n fo r the amoun t o f lead i n thos e product s consumed . Specifically , fo r instance , w e migh t expec t tha t individual s eating a lo t o f home-grow n vegetable s an

d fruits , wh o als o liv e nea r facilitie s emitting lead , woul d hav e muc hhighe r ingestio n level s o f lead . PERSONAL HABIT S AND LEA D EXPOSUR E On e o f th e keypersona l habit s affecting lea d exposur e i s th e cleanlines s o f th e home . Thi s i s particularl yimportan t fo r smal l childre n wh o woul d craw l o n th e floor , pic k up the dus t o n thei r hands , an d the n stic k thei r hand s i n thei r mouths . Anothe r persona l habi t particularl yrelevan t t o smal l childre n i s pica . I f childre n liv e i n house s wit hlead pain t o n the interio r wall s o r i f theyea t soi l tha t happen s t o b e relativel yhighi n lead content , the n naturall yth e amoun t o f lead ingeste d increase s significantly . B ymakin g assumption s abou t th e proportio n o f a give n populatio n grou p wit hthes e persona l habits , w e can calculat e distribution s fo r lead exposure .P.1 7 1 6 DEPOSITIONAND ABSORPTIONRATE S Assumption s mus t b e mad e abou t th e percentag e o f lead i n ai r deposite d i n th e lowe r ai r way s an d the uppe r ai r ways , th e amoun t o f depositio n i n th e uppe r ai r way s tha t i s eventuall yingested , an d the respectiv e absorptio n rate s fo r depositio n i n th e lowe r ai r way s an d fo r ingeste d lead . Poin t estimate s o f eac ho f thes e rate s wer e utilize d i n the sampl e calculation . Th e dat a may indicat e a distributio n ofrate s mayb e mor e appropriat e fo r an ygive n populatio n group . Th e appropriatenes s o f suc hassumption s shoul d b e carefull yappraise d b yexperts . I f a distributio n i s used , thi s woul d resul t i n a distributio n o f lead absorptio n fo r an ygive n population . RETENTIONAND EXCRETIO NRATE S Th e same type s o f comment s a s abov e pertai n t o the excretio n an d retentio n rate s fo r lead i n the blood . LEA D EQUILIBRIU

MINTH E BODY Assumption s ar e necessaryabou t wher e lea d i s "stored " i n th e bod yan d th e amoun t tha t i s stored . Th e criteri a documen t ha s a good dea l o f physiologica l informatio n o n this , althoughexper t opinio n woul d b e veryhelpfu l t o complemen t tha t data . I f poin t estimate s ar e mad e o f variable s sucha s th e manne r i n whic h lead i s take n fromthe bloo d an d store d i n th e bones , w e wil l ge t poin t esti

mate s o f the bloo d lead concentration s fo r an ygive n se t o f absorptio n rate s i n th e previou s informatio n leading t o bloo d lead . However , on e maywis ht o mak e probabilisti c assumptions , base d o n physiologica l dat a an d exper t judgment , abou t th e physiologica l propertie s o f a give n populatio n grou p wit h respec t t o storag e o f lead i n the body . I f so , probabilisti c distributio n o f bloo d lead concentration s woul d resul t fo r an ygive n se t o f variable s leading t o initia l bloo d lead absorption .P.1 8 1 7 RELATIONSHIP S BUIL T O NCORRELATE D DATA Wit hthe correlationa l approach , th e sampl e calculation s assume d linea r deterministi c relationship s betwee n bloo d lead an d inhale d lead an

d betwee n bloo d lead an

d ingeste d lead fromfoo d an d wate r source s an

d fromdus t sources . Althoughther e i s muc huncertaint yabou t the data , thes e relationship s ar e deterministic . Mor e appropriat e model s mayaccoun t fo r the uncertaintie s inheren t i n ou r informatio n abou t thes e relationships , whic har e perhap s partiall ydu e t o inheren t difference s betwee n the physiolog yo f differen t individual s i n a give n populatio n group . ADDITIVE RELATION S FOR BLOOD LEA D CONCENTRATION S Th e sampl e calculatio n assume d tha t th e contributio n t o bloo d lead from inhale d air , food an d wate r sources , an d dus t source s wer e additive . Thi s mayb e a significan t assumptio n an d shoul d b e carefull yappraise d b yth e experts . Th e criteri a documen t allude s t o th e possibilit ytha t ther e ar e natura l mechanism s t o reduc e th e bloo d lead conten t (e.g. , b ystoring lead i n bone ) whe n exposur e t o lead i s high . I f suc hi s the case , th e additiv e approac ht o bloo d lead woul d ten d t o overestimat e the likelihoo d o f highcon centration s o f bloo d lead and underestimat e lo wconcentration s becaus e o f th e compensatoryaction s o f th e body . Th e developmen t o f reasonabl e model s o f thes e compensatoryrelationship s woul d likel yheavil yrel yo n the judgmen t o f experts . CALCULATION S O F DISTRIBUTION S O F BLOO D LEA D Give n al l th e discussio n abou t assumption s i n th e section , on e coul d se e tha t the calculation s o f distribution s fo r bloo d lead fo r a give n populatio n grou p coul d b e verytime-consuming . Basically , i f uncertaintie s ar e accounte d fo r i n eac ho f th e variable s tha t ar e importan t fo r influencing bloo d leadP.1 9 

### 1 8 distribution s i n a give n populatio n group , the numbe r o f calculation s i s very large . However , a s illustrate d b ythe sampl e calculation , thes e calculation s ar e no t complex . I t woul d b e reasonabl e t o hav e thes e calculation s don e o n a smal l compute r designe d fo r veryeas yinpu t o f probabilit ydistribution s o n th e variables . Prio r t o that , w e woul d sugges t tha t a sensitivit yanalysi s o f importanc e o f thos e variable s fo r bloo d lead concentration s b e conducte d using tha t compute r model . Thi s woul d likel yreduc e th e amoun t o f dat a necessaryt o ge t reasonabl e distribution s fo r bloo d lead concentration s i n a give n populatio n group . Adjustmen t fo r Change s i n Ambien t Lead Level s Th e discussio n o f our approac ht o lea d exposur e ha s bee n base d entirel y o n the us e o f historica l dat a regarding actua l ambien t lea d levels . Change s i n standard s o r i n othe r factor s (e.g. , the us e o f leade d gasoline ) woul d b e expecte d t o caus e change s i n ambien t lead levels . Thi s i n turn woul d caus e change s i n exposur e whic hwoul d b e reflecte d i n differen t distribution s o f bloo d lead levels . I n orde r t o mak e appropriat e adjustment s i n th e analysis , w e woul d nee d t o mak e some assumption s concerning expecte d change s i n ambien t lead levels . Fo r instance , wha t i f ambien t lea d level s ar e reduce d t o the poin t wher e the larges t quarterl ymea n reporte d b yan yo f th e 1 1 monitor s i s 3 exactl yequa l t o 1. 0 yg/ m? A t on e extreme , al l quarterl ymean s belo w1. 0 3 3 yg/ mmigh t remai n th e same an d al l mean s abov e 1. 0 yg/ mwoul d b e reduce d t o 3 1. 0 yg/ m. Anothe r possibilit yi s tha t al l quarterl ymeans , whethe r belo wo r

3 abov e 1. 0 yg/ m, woul d b e reduce d t o some degree . Onc e a n assumptio n i s mad e abou t th e change s i n th e quarterl ymeans , th e analysi s ca n procee d a s before . I t i s important , however , tha t carefu l though t b e give n t o possibl e change s i n ambien t lead levels . I f th e chang e i s t o a ne wstandard , pas t dat a wil l no t b e available , an d i t wil l b e necessaryt o rel yo n exper t judgment s abou t potentia l modification s i n ambien t lead levels .1 9

Th e Rol e o f Additiona l Informatio n I t i s clea r tha t the informatio n i n the criteri a documen t provide s a n excellen t starting poin t fo r a n analysi s o f lea d exposure . However , th e infor

matio n i s no t complet e i n th e sens e tha t i t doe s no t provid e dat a regarding al l populatio n group s o f potentia l interest , al l locations , al l possibl e combination s o f relevan t factors , an d s o on . Furthermore , i n man ycase s i t provide s poin t estimate s fo r parameter s o f Interes t bu t doe s no t provid e a distributio n t o reflec t the uncertaint yabou t thes e parameter s o r the variabilit y i n thes e parameter s withi n a particula r population . Thus , fo r a complet e analysi s mor e informatio n i s needed . Perhap s a detaile d analysi s o f pas t studie s wil l provid e some additiona l information , an d an yfutur e dat a collectio n coul d b e aime d a t issue s o f particula r interes t fo r a lead exposur e analysis . W e believ e tha t i t i s als o importan t t o obtai n an d us e informatio n fromexperts . Exper t judgment s regarding variabilit ywithi n a populatio n i n term s o f differen t parameters , regarding adjustment s necessaryfo r change s i n standards , an d regarding othe r factor s can b e veryvaluabl e i n a n exposur e analysis . I t i s importan t tha t an

yrelevan t dat a b e include d i n the analysi s an d tha t the expert s familiariz e themselve s wit hsuchdat a befor e providing thei r ow n judg

ment s t o augmen t the data . I n area s wher e th e dat a o r the informatio n fromthe expert s seemshaky , i t woul d b e usefu l t o conduc t a sensitivit yanalysis . I n general , o f course , sensitivit yanalysi s i s usefu l i n pinpointing aspect s o f the mode l tha t ar e particularl ycrucia l i n term s o f thei r impac t o n th e fina l output . Thi s woul d b e a n indicatio n o f th e aspect s o f th e problemcrucia l i n term s o f impac t o n fina l bloo d lead levels .P.2 1

2 0 Sectio n 4 . Summar

yan d Discussio n

A s note d i n th e introduction , ou r inten t i s t o mak e suggestion s fo r developing , implementing , an d documenting a rationa l procedur e t o obtai n esti

mate s o f bloo d lead concentration s i n selecte d populatio n groups . Give n the limite d effor t involved , the suggestion s shoul d b e considere d preliminaryi n nature . Th e firs t importan t questio n i n the developmen t o f a mode l fo r exposur e analysi s concern s the appropriat e leve l o f aggregation . W e fee l tha t withou t substantiall ymor e dat a (whichwoul d b e difficul t an d expensiv e t o collect) , i t i s counterproductiv e t o disaggregat e to o much , int o a larg e numbe r o f "small " step s o r submodels . O n the othe r hand , relating bloo d level s directl yt o ai r lead levels , wit hperhap s a fewothe r variable s include d i n the model , migh t represen t to o higha leve l o f aggregation , althoughI t migh t b e worthwhil e t o attemp t suc ha n analysi s fo r the sak e o f comparison . W e recommen d a n intermediat e leve l o f aggregation , wher e th e proces s i s broke n dow n int o a few , bu t no t to o many , submodels . Specifi c detail s o f th e submodel s migh t diffe r fro mour preliminaryanalysi s wit hsampl e computations , bu t tha t degre e o f aggregatio n seem s t o b e reasonable . Th e emphasi s i n thi s repor t ha s bee n o n presenting a genera l approac ht o a n exposur e analysi s fo r lead , no t o n spending ou r limite d effor t o n a n actual , detaile d analysis . Th e sampl e calculation s i n Sectio n 2 ar e designe d t o illus

trat e th e leve l o f aggregatio n w e currentl yfee l i s appropriate . Thes e calculation s ar e base d o n limite d informatio n using mainl ypoin t estimate s o f variou s parameters . Excep t fo r the singl e illustratio n using indoo r activit y time , uncertaint yabou t th e paramete r value s an d variabilit yamong th e member s o f a populatio n hav e no t bee n considere d i n th e calculations .2 1

I n Sectio n 3 w e indicat e ho wth e simpl e approac hi n Sectio n 2 ca n b e extende d t o generat e mor e realisti c estimate s o f bloo d lead concentrations . An importan t aspec t o f th e extensio n i s th e explici t consideratio n o f uncertaint y abou t the paramete r value s an d variabilit yamong th e member s o f a population . Thi s give s ris e t o probabilit ydistribution s fo r th e parameter s an d ultimatel y t o a distributio n o f bloo d lead concentration s fo r an yselecte d populatio n group . Akeyissu e her e concern s th e source s o f informatio n fromwhic hth e probabilit ydistribution s ar e determined . I n some case s dat a alread yavailabl e mayb e use d t o arriv e a t distributions . I n othe r cases , i t wil l b e necessary t o solici t exper t judgment s an d t o bas e the distribution s o n an yavailabl e dat a an d o n th e judgments . Acomplet e analysi s shoul d b e dynami c i n nature , wit hthe natur e o f the availabl e dat a an d the experts ' judgment s possibl y causing modification s i n the leve l o f aggregatio n an d i n othe r detail s o f th e model . I n conclusion , w e recommen d tha t the expert s fro mEPAwh o hav e worke d o n exposur e analysi s shoul d firs t scrutiniz e th e validit yo f our submodel s an d determin e whic hparamete r value s ca n b e reasonabl yassume d t o b e deterministic . Appropriat e expert s (demographers , healt hexperts , etc. ) ca n the n b e consulte d t o defin e range s o r probabilit ydistribution s fo r some critica l parameters . Asimpl e compute r progra mca n the n b e writte n t o obtai n bloo d lead concentration s i n selecte d populatio n group s i n a give n cit yo r localit yusin g ou r propose d approac ho r it s modifie d version .P.2 3

Ai r quality , location , age , ag e o f housing



# x k Submode l 1 LEA D CONSUMPTION 

# ¥ Dail yinhalatio n an d ingestio n o f lead b y source s (food , drinks , dust ) average d ove r a mont h



# ik i Submode l 2 BLOOD LEA

D CONTEN

T 

# V Monthl yaverag e blood lea d leve l

Figur e 1 . Genera l structur e o f mode l wit hintermediat e

leve l o f aggregatio nDail y

inhalatio n Dail y ingestio n > Mont h1 Exhale d 50 % Depositio n i n Lowe r Airway s 35 % Equilibriu mleve l o f lea d fro m previou s mont h

~ ' " " T absorptsip n Depositio n i n |7*> , , r . . .,„ . rat e IO C Uppe r Airway s 15 % 

## 2 k Tota l Lea d Ingeste d 

# 3 E Tota l Lea d absorptio n absorptio n fat e 10-30 % \ T*

-

Excretio n rat e 50-60 % Lea d Excrete d 

# V

Lea d Retaine d 

# I

Figur e 2 . Physiologica l mode lP.2 5



### a i r lea dconcentratio ni n/•g/ m(x )

z - g(x ) (step s 1-2 ) y= f(x ) (criteri a document )

lea d inhalatio n i n /vg/da y(z ) bloo d lea d leve l i n /**-g/d l (y )

Figur e 3 . Relationshi p betwee n ai r lea d and bloo d lea d