# Risk and Technology Review -

Analysis of Socio-Economic Factors for Populations Living Near Secondary Lead Smelting Facilities

Prepared by:

EC/R Incorporated 501 Eastowne Drive, Suite 250 Chapel Hill, NC 27514

EPA Contract No. EP-D-06-119 Work Assignment No. 4-02

Prepared for:

Terri Hollingsworth, Work Assignment Manager Sector Based Assessment Group Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27711

April 2011ii 

### Disclaimer

Although the analysis de scribed in this document has been funded wholly or in part by the United States Environmental Protection Agency contract EP-D-06-119 to EC/R Incorporated, it has not been subject to the Agency's review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred.

## Contents

1. Introduction 1 2. Census Data 2 3. Calculation Methods 4 3.1 Racial and Ethnic Categories and the Total Population 4 3.2 Age Categories 5 3.3 Level of Education 6 3.4 Household Income 7 3.5 Poverty Level 8 4. Results 8 5. Uncertainty Discussion 111 

## 1. Introduction

This document describes the approach used to evaluate the potential cancer and noncancer risks associated with inhalation and air-related exposures to hazardous air pollutants (HAP) in different social, demographic, and eco nomic groups within the population living near secondary lead smelting facilities in the United States. This work was carried out to identify demographic groups that could potentially be a ffected by the proposed ru le presented in the document: National Emission Standards for Hazardous Air Pollutants: Secondary Lead Smelting. It was developed in support of the U.S. Envi ronmental Protection Agency’s Residual Risk and Technology Review (RTR) for secondary lead smelting operations emissions subject to Maximum Available Control Technology (MACT) requirements under 40 CFR 63 Subpart X.

In the RTR analysis, the Human Exposure Model, Version 3 (HEM3) 1,2 was used to estimate cancer and noncancer risks due to the inhalation of HAP for the populations residing within 50 kilometers of each secondary lead sm elting facility in the c ountry. HEM3 estimates cancer and noncancer risks at the level of censu s blocks using the AERM OD state-of-the-art air dispersion model developed under the direction of the American Meteorological Society (AMS) / EPA Regulatory Model Improvement Committee (AERMIC). Each census block typically includes about 50 people. Additional information on the risk analysis is available in the docket for the proposed National Emission Standards fo r Hazardous Air Pollutant Emissions: Secondary Lead Smelting rulemaking where a report is provided, covering the inputs and specific assumptions, and addressing uncertainties.

In the current analysis, cancer and noncan cer risk estimates from the secondary lead smelting HEM3 modeling effort were linked to de tailed census data in order to evaluate the distribution of risks for diffe rent social, demographic and economic groups. The following population categories were included in this analysis:

 Total population

 White

 Minority

 African American (or Black)

 Native Americans

 Other races and multiracial

 Hispanic or Latino

 Children 18 years of age and under

1. EC/R. 2006. Modeling for the Residual Risk and Technology Review Using the Human Exposure Model 3 – AERMOD Version. Prepared by EC/R Incorpor ated for the U.S. Enviro nmental Protection Agency, Research Triangle Park, NC.

2. EC/R. 2008. HEM-3 User’s Guide. Prepared by EC/R Incorporated for the U.S. Environmental Protection Agency, Research Triangle Park, NC. http://www.epa.g ov/ttn/fera/human_hem.html#guide2  Adults 19 to 64 years of age

 Adults 65 years of age and over

 Adults without a high school diploma

 Households earning under the national median income

 People living below the poverty line

The HEM3 results for a particular census bl ock reflect the estimated level of cancer risk that would be experienced by an individual re siding in the block for 70 years, and/or the estimated noncancer hazards experienced by an i ndividual residing in the block due to chronic exposure. In this case, the latter includes the development of chronic hazard quotients for lead which are derived from estimated maximum 3-m onth rolling average exposures divided by the National Ambient Air Quality Standard (NAAQS) for lead.

The distributions of sour ce category risks across the va rious demographic groups are normally compared to those associated with HAP sources at the facilities containing the source category (i.e., “facility-wide”). However, for th e secondary lead source category, the “facilitywide” risks are equivalent to the source category ri sks (because all emissions at the facilities are associated with the source category), so no such comparisons are provided.

The census data used in this analysis is de scribed in Section 2. The algorithms used to compute the distributions of risk and exposure ar e presented in Section 3. The results of this analysis are presented in Section 4.



## 2. Census Data

Table 1 summarizes the census data used in this analysis, showing the source of each dataset and the level of geogra phic resolution. All of the data are from the 2000 Decennial census. Race and ethnicity data were obtained at the census block level. Age distributions, data on educational status, and economic data were obtai ned at the block group level. A census block contains about 50 people on average; and a block group contains about 26 bl ocks on average, or about 1,350 people. (For comparison, a census tract is larger than a block group, with each tract containing an average of 3 bloc k groups, or about 4,300 people.)3 Table 1. Summary of Census Data usedto Analyze Risks for Different Socioeconomic Groups

Type of population cat egory Source of data Level of geographic resolution Racial and ethnic categori es Landview® Census block Age groups SF3 Table P8 Block group Level of education - adults without a high school diploma SF3 Table 37 Block group

Households earning below the national median income SF3 Table 52 Block group

People living below the poverty line SF3 Table P87 Block group

Data on race and ethnicity were obtaine d primarily from the Landview® database compiled by the Census Department. 3 Landview® gives a breakdown for the population of each census block among different raci al classifications, including: White, African American or Black, American Indian or Native Alaskan, As ian, Native Hawaiian or other South Pacific Islander, other race, and two or more races. In the current anal ysis, the Asian, Native Hawaiian or other South Pacific Islander, and other race cate gories were combined into a single category. The Landview® database also indicates the number of people in each tract that are of Hispanic or Latino ethnicity. Landview® co vers the 50 states, the District of Columbia, and Puerto Rico, but does not cover the Virgin Islands. Race a nd ethnicity data on the Virgin Islands were obtained from the Virgin Islands Summary File. 4

Data on age distributions, pove rty status, household incomes, and education level in the U.S. and Puerto Rico were obtained from th e 2000 Census of Populati on and Housing Summary File 3 (SF3) Long Form. For the U.S. this file was accessed on a DVD version prepared by GeoLytics. 5 SF3 data for Puerto Rico were obtai ned from the Census Department website, 6 and data for the Virgin Islands were retrieved from similar tables in the Virgin Islands Summary File. 4

The SF3 data set consists of over 800 separa te tables, each providing information on a different subject. For the current analysis, da ta were obtained from Tables P8, P37, P52, and P87. Table P8 gives the estimated numbers of men and women in different age categories for each census block group. Table P37 analyzes the level of education attained by men and women

3. Census. 2002. LandView 5 on DVD [electronic reso urce] : a viewer for EPA, Census and USGS data and maps. U.S. Census Bureau, Washington, D.C.

4. Census. 2008. Virgin Islands Summary File. U.S. Census Bureau, Washington, D.C. www.factfinder.census.gov

5. Census. 2004. Census DVD 2000 Long Form SF3, Release 2.2. Geolytics, Inc., East Brunswick, NJ. www.geolytics.com

6. Census. 2008. SF3 Data for Puerto Rico. U.S. Census Bureau, Washington, D.C. www.factfinder.census.gov4 over 25 years of age (e.g. some high school but no high school diploma, high school graduate, some college, etc.). Table P52 gives information on household income in 1999, and Table P87 estimates the number of people living be low the poverty line in each block group.



## 3. Calculation Methods

The HEM3 models the cancer and noncancer ri sk at a point near th e geographic center of each census block. 7 For the current analysis, this risk estimate was assumed to apply to all individuals residing in the block. We used block identification codes to link the HEM3 modeling results for each block to the a ppropriate census statistics. This allowed us to estimate the numbers of people falling into different populati on subcategories within each block. We then analyzed the distribution of estimated inhalati on risks within each popul ation subcategory, giving the numbers of people within the subcategory that are exposed to different risk levels. Each distribution involved a tabulati on of all the census blocks mo deled for the secondary lead smelting source category. We also computed th e average risk for all individuals in each population subcategory.

Distributions of risk and average risks we re computed for the raw HEM3 model results for secondary lead smelting operations. For comp arison, distributions of risk and average risks were also computed for all emission sources at the facility including secondary lead smelting (i.e., “facility-wide”). For the secondary lead smelting source category, the facility-wide risk distribution was identical to the source cate gory risk distribution (and was therefore not separately presented in the results). A na tionwide demographic brea kdown (i.e., population percentage in each demographic group) based on the 2000 Census is also provided in the results tables for comparison.

Section 3.1 describes the calcu lation method used for categor ies where block-level data were available -- racial and et hnic categories and the total pop ulation. Sections 3.2 through 3.5 describe calculation methods for age categories, education status, household income, and poverty status, respectively.



### 3.1 Racial and Ethnic Categories and the Total Population

Since race and ethnicity data were available at the census bl ock level, the calculation of risk distributions for these categories involve d a simple block-by-block accumulation of the people in each subcategory. We began by identifyi ng a set of bins reflecting the level of risk. The population of each block was then assigned to the appropriate risk bin based on the modeled risk level in the block. The numbers of people in each risk bin were then added together for all of the blocks modeled for the secondary lead smelting source category:

H(R ab ,s) = ∑ i (Ra ≤ Ri<Rb) [N(s,i)] (1)

7. HEM3 generally uses the coordina tes given by the census for the in ternal point, or “centroid” of each block. However, when the footprint of an industrial facility includes the block centroid, the model is designed to identify the highest-risk point outside of the facility’s footprint.5 where: H(R ab ,s) = the population count for risk bin R ab , which is between R a and R b for population subgroup “s” R i = the modeled risk level in block “í” (e stimated lifetime cases of cancer per million population or noncancer hazard index) ∑ i (Ra ≤ Ri<Rb) refers to the summation over all blocks i where R i falls in bin R ab , between R a and R b N(s,i) = the number of people within population subcategory s, in block i

The same approach was used for the total populat ion. The average risk for a given population subcategory or for the total population wa s calculated using th e following equation:

A(S) = ∑ i [N(s,i) × R i ] ⁄ ∑ i [N(s,i)] (2)

where: A(s) = the average risk for population subg roup “s” (estimated lifetime cases of cancer per million population or noncancer hazard index) ∑ i refers to the summation over all bloc ks “í” modeled for the emission source category N(s,i) and R i were defined above



### 3.2 Age Categories

Age data were retrieved from the Table P8 of the census SF3 Table, which contains data on the numbers of males and females of different ages in each census block group. In processing the age data, we began by aggregating the catego ries in the census to the broader age groups studied in this analysis. For in stance, the total number of children 18 years of age and under was calculated by adding together the number of gi rls under 1 year, the number of boys under 1 year, the number of 1-year-old girls, the number of 1-year-old boys, and so on up to and including 18- year-old girls and boys. In this way, we calcu lated the number of children age 18 and under, the number of adults from 18 to 64, and the numbe r of adults 65 and older in each census block group.
The next step was to estimate the numbers of people in each age group at the block level. To make this calculation, we assumed that the fr action of people in each age group was the same for all blocks in a given block group. Thus, th e number of people in a particular age group and within a particular census bloc k was estimated as follows:

N(a,b/bg) = N( t,b/bg) × N(a,bg) ⁄ N(t,bg) (3)

where: N(a,b/bg) = number of people within age group “a”, in block “b” of block group “bg” N(t,b/bg) = total number of people in block “b” of block group “bg” N(a,bg) = number of people within age group “a” in block group “bg”6 N(t,bg) = total number of people in block group “bg”

Equation 1 was then applied to th e block-level population estimates to generate risk distributions for different age groups, and Equation 2 was used to compute the average risk for each age group.



### 3.3 Level of Education

Table P37 of the SF3 dataset specifies the education status for men and women age 25 and older for each census block group, based on the last grade completed. To obtain the total number of adults without a high school degree, we added together the numbers who had completed grades below a high school senior. Thus, the number of peopl e without a high school degree equals the sum of the number of males with no schooling, the number of females with no schooling, the numbers of males and females who have completed nursery school through 4 th grade, up to the numbers of males and female s who have completed some high school but not received a high school degree.

The number of adults without a high school de gree as a fraction of the total population was assumed to be the same for each block in the block group. Thus, the number of adults without a high school degree in each block was computed as follows:

N(nhs,b/bg) = N( t,b/bg) × N(nhs,bg) ⁄ N(t,bg) (4)

where: N(nhs,b/bg) = number of adults without a high school diploma, in block “b” of block group “bg” N(t,b/bg) = total number of people in block “b” of block group “bg” N(nhs,bg) = number of adults without a high school diploma in block group “bg” N(t,bg) = total number of people in block group “bg”

Equation 1 was then used to generate risk dist ributions based on the block-level results, and Equation 2 was used to compute the average risk for adults without a high school diploma.7 

### 3.4 Household Income

Table P52 of the SF3 dataset estimates the numbers of households in each block group with income for the year 1999 in various ranges, generally divided into $5,000 increments (e.g. $10,000 to $14,999, $15,000 to $19,999, etc.). The median national income for 1999 was about $42,000 per year. Therefore, in order to dete rmine the number of households with incomes under the median income, we added the estimates fo r the ranges below that level. We assumed that the household incomes in the $40,000 to $44,999 increment we re evenly distributed over this range. Therefore, 40% of the househol ds in the $40,000 to $44,999 income range were assumed to be below the national median income of about $42,000. The following equation was used to estimate the fraction of households below the national medi an income within each census block group:

F(sm,bg) = [C <10 + C 10-15 + .... + C 35-40 + (0.4×C 40-45 )] ⁄ C T (5)

where: F(sm,bg) = fraction of households in block group “bg” with incomes below the median national income C <10 = number of households with incomes under $10,000 C 10-15 = number of households w ith incomes from $10,000 to $14,999 C 35-40 = number of households w ith incomes from $35,000 to $39,999 C 40-45 = number of households w ith incomes from $40,000 to $44,999 C T = total number of households in block group “bg”

The fraction of people living in households below the median income for each block within the block group was assumed to be the same as the fraction of households below the median income for the block group.

N(sm,b/bg) = F(sm,bg) × N(t,b/bg) (6)

where: N(sm,b/bg) = number of people in block “b” of block group “bg” livi ng in households below the national median income F(sm,bg) = fraction of households in block group “bg” below the national median income N(t,b/bg) = total number of people in block “b” of block group “bg”

Equation 1 was then used to generate risk dist ributions based on the block-level results, and Equation 2 was used to compute the average risk for adults without a high school diploma. It must be noted that this approach neglects a ny potential relationship be tween household size and income level within a particular block group. Ho wever, it is expected to provide a reasonable indication of the risk level of people living belo w the national median income, relative to the population as a whole.8 

### 3.5 Poverty Level

Table P87 of the SF3 dataset estimates the total number people in each block group living below the poverty level, as well as the numbers of people below th e poverty level in different age groups. The current study did not include an anal ysis of poverty status by age group, only of the total population below the poverty line. The fraction of peopl e below the poverty line was assumed to be the same for each block in the block group. Thus, the population below the poverty line in each block was computed as follows:

N(p,b/bg) = N(T,b/bg) × N(p,bg) ⁄ N(T,bg) (7)

where: N(p,b/bg) = number of people below the povert y line in block “b” of block group “bg” N(T,b/bg) = total number of people in block “b” of block group “bg” N(p,bg) = number of people below th e poverty line in block group “bg” N(T,bg) = total number of people in block group “bg”

Equation 1 was then used to generate risk dist ributions based on the block-level results, and Equation 2 was used to compute the average risk for adults without a high school diploma.



## 4. Results

The distribution of estimated lifetime inha lation cancer risks a bove 1 in a million or noncancer hazard indices above 1 for different racial and ethnic groups among the population living near secondary lead smelting facilities is shown in Table 2. For comparison purposes, Table 2 provides the nationwid e percentages of the various demographic groups. As noted above, for the secondary lead smelting source ca tegory, the facility-wide emissions and risk distribution are equivalent to th e source category emissions and risk distribution, thus a separate demographic analysis based on facility-wide em issions was not performed. Moreover, for HAP other than lead, there were no estimated noncance r HI values greater th an 1, thus we did not perform a demographic analysis on noncancer ri sks for any pollutants other than lead. The demographic noncancer results for lead are pres ented in Table 2 as “Population with Ambient Lead Concentrations Exceeding the NAAQS,” rather than as population with HI greater than 1, because lead concentrations were compared to the NAAQS rather than to a reference concentration. Detailed demogra phics data and analyses used to create Table 2 can be found in Appendix A of this document.

The results of the demographic analysis pr esented in Table 2 indicate that there are approximately 128,000 people exposed to a cancer risk greater than 1-in-1 million, and 465 people in areas with ambient l ead concentrations above the NAAQS for lead. The demographic analysis estimates that about 42% of this population exposed to a cancer risk greater than 1-in-1 million can be classified as minority, and this minority figure is appreciably higher than the national minority percentage (of 25%). More sp ecifically, the demogra phic analysis estimates that about 56% of the population wi th excess cancer risk is classi fied as “Hispanic”, and this9 percentage is four times the national Hispanic percentage of 14%. Furthermore, 34% of the population estimated at a cancer risk greater than 1-in-1 million is classified as “Other and Multiracial”, and this figure is nearly three times the national demographic for this group (at 12%). The demographic analysis for cancer risk also estimates that 26% of the population at excess cancer risk has no high school diploma, and this is twice the national percentage for this demographic (of 13%); and 22% of the populati on at excess cancer risk is below the poverty level, a figure which is not quite double the na tional percentage for this demographic group (at 13%).

With respect to lead, the demographic re sults are below their corresponding national percentages for all racial and et hnic classifications, and similar to the national percentages for most other demographic categories. There are modest percentage incr eases (of 2%) above the corresponding national per centages with respect to those 65 y ears old and older and with respect to those without a high school diploma. However, considering that the total population affected is small (i.e., about 500 individuals in areas wi th lead concentrations above the NAAQS), this does not represent an appreciable difference.10Table 2. Summary of Demographic Assessment of Risk Results for the Secondary Lead Smelting Source CategoryEmissionsBasisDemographic GroupTotal MinorityAfricanAmericanOther andMultiracialHispanicor LatinoNativeAmericanAges 0to 18Ages 19to 64Ages 65and upBelow thePovertyLevelOver 25Without aHSDiplomaNationwideDemographicBreakdownn/a 285,339,128 25% 12% 12% 14% 0.9% 27% 60% 12% 13% 13%MaximumRisk(in 1million)Population With Risk Greater Than 1 in 1 millionSourceCategory50 128,046 42% 7% 34% 56% 0.8% 32% 59% 9% 22% 26%MaximumHazardIndexPopulation With Ambient Lead Concentrations Exceeding the NAAQSSourceCategory23 465 6% 2% 3% 5% 0.6% 26% 60% 14% 10% 15%Notes:Facility-wide emissions are equivalent to the source category emissions for secondarylead smelting; therefore a facility-widedemographic analysis was not performed.The Maximum Hazard Index refers to the ratio of the maximum estimated off-site ambient concentration to the NAAQS for lead.There are no HIs > 1 for HAPS other than lead for the secondary lead smelting category.Source Category emissions were estimated based on January 2010 NEI data.Minority population is the total population minus the white population.Population figures are for the population residing within 50 kmof these facilities whose cancer risks are estimated to be greater than or equal to 1 in a million, or whosenoncancer hazard indices are estimated to be greater than 1 (based on exceeding the NAAQS for lead).11 

## 5. Uncertainty Discussion

Our analysis of the distribution of risks acr oss various demographic groups is subject to the typical uncertainties associated with census data (e.g., errors in fil ling out and transcribing census forms), which are generally thought to be small, as well as the additional uncertainties associated with the extrapolation of census-bl ock group data (e.g., income level and education level) down to the census block level.

The uncertainties in these risk estimates incl ude the same uncertainties in emissions data sets, in air dispersion modeling, in inhalation exposure and in dose response relationships that are associated with our source category risk estimates.

The methodology for our demographic analyses is still evolving. While this is our best attempt to provide useful information now, our thinking is continuously advancing. EPA is in the process of developing technical guidance fo r environmental justice analyses. We present these analyses, with their associated uncertain ties, to EPA decision makers and the public as additional analyses to inform RTR decisions.A-1 

### Appendix AA-2 Total population White African American Native American Other and multiracial Hispanic or
Latino c

0 to 1 26,342,851 17,571,676 2,446,168 159,133 6,165,874 6,628,716 1 to 5 117,298 68,758 7,718 1,001 39,821 66,156 5 to 10 9,292 5,013 942 78 3,259 5,079 10 to 20 1,041 723 104 3 211 329 20 to 30 295 281 0 1 13 19 30 to 40 22 20 2 0 0 1 40 to 50 77 67 7 1 2 3 50 to 100 21 20 0 0 1 0 Total number 26,470,897 17,646,558 2,454,941 160,217 6,209,181 6,700,303

0.0489 0.0416 0.0703 0.0586 0.061 0.0806
Notes:

c The Hispanic or Latino population is double-counted in this analysis, since different individuals within the category may classify themselves as White, African American, Native American, or other. Table A-1. Distribution of Inhalation Cancer Risk for Racial and Ethnic Groups

a Modeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.

Range of lifetime individual cancer risk (chance in one million) a

Average risk (chances in one million)

b Distributions by race are based on demographic information at the census block level. Risks from secondary lead smelting emissions were modeled at the block level. Modeled risk from the secondary lead smelting category Numbers of people in different ranges for lifetime cancer risk bA-3 Total population Ages 0 thru 18 Ages 19 thru 64 Ages 65 and
up

0 to 1 26,342,851 7,401,123 16,116,848 2,824,880 1 to 5 117,298 37,929 68,811 10,559 5 to 10 9,292 2,957 5,351 984 10 to 20 1,041 318 607 116 20 to 30 295 77 179 40 30 to 40 22 5 13 4 40 to 50 77 19 42 16 50 to 100 21 5 12 4 Total number 26,470,897 7,442,432 16,191,863 2,836,602

0.0489 0.0539 0.0474 0.0443

Notes: Table A-2. Distribution of Risk for Different Age Groups

Modeled risk from the secondary lead smelting category

b Distributions by age are based on modeling data at the Census block level, and age data at the block group level. All blocks in a block group are assumed to have the same age distribution. Range of lifetime individual cancer risk (chance in one million) a Numbers of people in different ranges for lifetime cancer
risk b

Average risk (chances in one million)

a Modeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.A-4 Total population Total number 25 and older Number 25 and older without a high school diploma

0 to 1 26,342,851 16,768,611 3,703,277 1 to 5 117,298 66,208 30,722 5 to 10 9,292 5,201 2,534 10 to 20 1,041 640 203 20 to 30 295 198 41 30 to 40 22 16 3 40 to 50 77 50 15 50 to 100 21 15 3 Total number 26,470,897 16,840,939 3,736,797

0.0489 0.0456 0.0718 Notes: Table A-3. Distribution of Risk for Adults with and without a High School Diploma

Modeled risk from the secondary lead smelting category

b Distributions by education level are based on modeling data at the Census block level, and education data at the block group level. All blocks in a block group are assumed to have the same education level distribution. Range of lifetime individual cancer risk (chance in one million) a Numbers of people in different ranges for lifetime
cancer risk b

Average risk (chances in one million)

a Modeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.A-5 Total population People living in households below the national median
income c People living below the poverty line

0 to 1 26,342,851 12,039,105 3,397,389 1 to 5 117,298 75,535 25,316 5 to 10 9,292 5,889 2,211 10 to 20 1,041 564 164 20 to 30 295 145 23 30 to 40 22 10 1 40 to 50 77 50 16 50 to 100 21 11 2 Total number 26,470,897 12,121,309 3,425,121

0.0489 0.0606 0.0721 Notes: Table A-4. Distribution of Risk for People Living in Households below the National Median Income and Below the Poverty Line

Range of lifetime individual cancer risk (chance in one million) a Numbers of people in different ranges for lifetime
cancer risk b

c The median income is the national median household income in 1999, about $42,000. Modeled risk from the secondary lead smelting category

Average risk (chances in one million)

a Modeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.

b Distributions by income are based on modeling data at the Census block level, and income data at the block group level. All blocks in a block group are assumed to have the same income distribution.A-6 Total population White African American Native American Other and multiracial Hispanic or
Latino c

0 to 0.2 26,436,787 17,626,744 2,451,443 159,952 6,198,648 6,683,593 0.2 to 1 33,645 19,376 3,489 262 10,518 16,687

1 to 1.5 271 258 0 1 12 19 1.5 to 2 0 0 0 0 0 0

2 to 3 138 135 2 1 0 4 3 to 4 56 45 7 1 3 0 4 to 5 0 0 0 0 0 0 5 to 6 0 0 0 0 0 0 Total number 26,470,897 17,646,558 2,454,941 160,217 6,209,181 6,700,303

0.0037 0.003 0.0045 0.0047 0.0055 0.0068
Notes:

c The Hispanic or Latino population is double-counted in this analysis, since different individuals within the category may classify themselves as White, African American, Native American, or other. Table A-5. Distribution of Inhalation Hazard Indices for Racial and Ethnic Groups

a Modeled hazard indices are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.

Range of lifetime individual
hazard index a

Average hazard index

b Distributions by race are based on demographic information at the census block level. Risks from secondary lead smelting emissions were modeled at the block level. Modeled hazard index from the secondary lead smelting category Numbers of people in different ranges for lifetime hazard indices bA-7 Total population Ages 0 thru 18 Ages 19 thru 64 Ages 65 and
up

0 to 0.2 26,436,787 7,432,013 16,171,606 2,833,169 0.2 to 1 33,645 10,296 19,978 3,371

1 to 1.5 271 73 170 28 1.5 to 2 0 0 0 0

2 to 3 138 35 77 26 3 to 4 56 15 32 9 4 to 5 0 0 0 0 5 to 6 0 0 0 0 Total number 26,470,897 7,442,432 16,191,862 2,836,603

0.0037 0.0041 0.0036 0.0033

Notes: Table A-6. Distribution of Hazard Indices for Different Age Groups

Modeled hazard index from the secondary lead smelting category

b Distributions by age are based on modeling data at the Census block level, and age data at the block group level. All blocks in a block group are assumed to have the same age distribution. Range of lifetime individual hazard
index a Numbers of people in different ranges for lifetime hazard
indices b

Average hazard index

a Modeled hazard indices are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.A-8 Total population Total number 25 and older Number 25 and older without a high school diploma

0 to 0.2 26,436,787 16,821,756 3,728,362 0.2 to 1 33,645 18,862 8,363

1 to 1.5 271 192 35 1.5 to 2 0 0 0

2 to 3 138 94 25 3 to 4 56 35 11 4 to 5 0 0 0 5 to 6 0 0 0 Total number 26,470,897 16,840,939 3,736,797

0.0037 0.0035 0.0056 Notes: Table A-7. Distribution of Hazard Indices for Adults with and without a High School Diploma

Modeled hazard index from the secondary lead smelting category

b Distributions by education level are based on modeling data at the Census block level, and education data at the block group level. All blocks in a block group are assumed to have the same education level distribution. Range of lifetime individual hazard
index a Numbers of people in different ranges for lifetime
hazard indices b

Average hazard index

a Modeled hazard indices are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.A-9 Total population People living in households below the national median
income c People living below the poverty line

0 to 0.2 26,436,787 12,099,855 3,417,912 0.2 to 1 33,645 21,207 7,161

1 to 1.5 271 128 19 1.5 to 2 0 0 0

2 to 3 138 81 16 3 to 4 56 39 14 4 to 5 0 0 0 5 to 6 0 0 0 Total number 26,470,897 12,121,309 3,425,121

0.0037 0.0045 0.0055 Notes: Table A-8. Distribution of Hazard Indices for People Living in Households below the National Median Income and Below the Poverty Line

Range of lifetime individual
hazard index a Numbers of people in different ranges for lifetime
hazard indices b

c The median income is the national median household income in 1999, about $42,000. Modeled hazard index from the secondary lead smelting category

Average hazard index

a Modeled hazard indices are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors.

b Distributions by income are based on modeling data at the Census block level, and income data at the block group level. All blocks in a block group are assumed to have the same income distribution.