Risk and Technology Review -

Analysis of Socio-Economic Factors for Populations 

Living Near Ferroalloys Facilities

Prepared by:

EC/R Incorporated

501 Eastowne Drive, Suite 250

Chapel Hill, NC 27514

EPA Contract No. EP-W-12-011

Work Assignment No. 3-07

Prepared for:

Air Toxics Assessment Group

Health and Environmental Impacts Division

Office of Air Quality Planning and Standards

U.S. Environmental Protection Agency

Research Triangle Park, North Carolina 27711

April 9, 2015
ii

Disclaimer

Although the analysis described in this document has been funded 

wholly or in part by the United States Environmental Protection 

Agency contract EP-W-12-011 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.
iii

Contents

1. Introduction 1

2. Census Data 2

3. Calculation Methods 3

3.1 Racial, Ethnic and Age Categories and the Total Population 4

3.2 Level of Education 5

3.3 Household Income 5

3.4 Poverty Level 6

3.5 Linguistic Isolation 7

4. Results 7

5. Uncertainty Discussion 9

Appendix A A-0
iv
1

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 economic groups within the population living near

ferroalloys production facilities in the United States. This work was carried out in support of the 

U.S. Environmental Protection Agency’s Residual Risk and Technology Review (RTR) for 

Ferroalloys Production emissions subject to Maximum Available Control Technology (MACT) 

requirements under 40 CFR 63 Subpart XXX. 

In the RTR analysis, the Human Exposure Model, Version 3 (HEM-3)

1,2,3 was used to 

estimate cancer and noncancer risks due to the inhalation of HAP for the populations residing 

within 50 kilometers of each Ferroalloys facility in the country. HEM-3 estimates cancer and 

noncancer risks at the level of census blocks using the AERMOD 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 for Hazardous Air Pollutant Emissions: Ferroalloys 

Production Operations rulemaking. The docket provides a report covering the inputs and 

specific assumptions, and addressing uncertainties.

In the current analysis, cancer and noncancer risk estimates from the Ferroalloys HEM-3

modeling effort were linked to detailed census data in order to evaluate the distribution of risks 

for different demographic groups (including racial, ethnic, age, economic, educational, and 

linguistically isolated population categories). 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

 

1. EC/R. January 2014. Modeling for the Residual Risk and Technology Review Using the Human Exposure 

Model 3 – AERMOD Version. Technical Support Document prepared by EC/R Incorporated for the U.S. 

Environmental Protection Agency, Research Triangle Park, NC. 

2. EC/R. April 2014. The HEM-3 User’s Guide. Prepared by EC/R Incorporated for the U.S. Environmental 

Protection Agency, Research Triangle Park, NC. 

http://www2.epa.gov/sites/production/files/2014-04/documents/hem3_users_guide.pdf

3. EC/R. April 2014. Multi HEM-3 and RTR Summary Programs User’s Guide. Prepared by EC/R 

Incorporated for the U.S. Environmental Protection Agency, Research Triangle Park, NC. 

http://www2.epa.gov/sites/production/files/2014-04/documents/multi_hem-3_users_guide.pdf
2

 Children 17 years of age and under

 Adults 18 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

 Linguistically isolated people

The HEM-3 results for a particular census block reflect the estimated level of cancer risk that 

would be experienced by an individual residing within the block boundaries for 70 years, and the 

estimated noncancer hazards experienced by an individual residing in the block due to chronic 

exposure. In this analysis, the demographic composition of the population estimated to 

experience a risk greater than or equal to 1 in 1 million or a hazard index greater than 1 as a 

result of Ferroalloys Production emissions is compared to the demographic composition of the 

overall nationwide population.

The census data used in this analysis is described in Section 2. The algorithms used to 

compute the distributions of risk and exposure are 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 the analysis, showing the source of each 

dataset and the level of geographic resolution. Race, ethnicity and age data are provided by the 

Census Bureau at the census block level. Distributions regarding household income and 

linguistic isolation are provided at the block group level. Distributions regarding educational 

status and poverty status are at the tract level. A census block contains about 50 people on 

average; and a block group contains about 28 blocks on average, or about 1,400 people. A census 

tract is larger than a block group, with each tract containing an average of 3 block groups, or 

about 4,300 people.

Data on race, ethnicity, and age were obtained from tables in the 2010 Census Summary 

File 1 (SF1).4 SF1 gives a breakdown for the population of each census block among different 

racial classifications, including: White, African American or Black, American Indian or Native 

Alaskan, Asian, Native Hawaiian or other South Pacific Islander, other race, and two or more 

races. In the current analysis, the Asian, Native Hawaiian or other South Pacific Islander, and 

other race categories were combined into a single category. The SF1 database also indicates the 

number of people in each tract that are of Hispanic or Latino ethnicity. SF1 covers the 50 states, 

the District of Columbia, and Puerto Rico. Data for the Virgin Islands, American Samoa, 

 

4. 2010 Census Summary File 1 – United States: http://www2.census.gov/census_2010/04-Summary_File_1/

prepared by the U.S. Census Bureau, 2011. See also Technical Documentation for the 2010 Census 

Summary File 1.
3

Northern Mariana Islands and Guam (although not needed for this analysis) can be retrieved 

from similar tables in the “Island Areas: 2010 Census Summary File”.5 

Data on education level, household income, poverty status, and linguistic isolation were 

obtained from tables in the Census’ American Community Survey (ACS) 5-year estimates for 

2005-2009.6

Table 1. Summary of Census Data used to Analyze Risks for Different 

Socio-economic Groups

Type of population category Source of data

Level of 

geographic 

resolution

Racial categories SF1 Table P3 Census block

Ethnic categories (Hispanic) SF1 Tables P4 & P7 Census block

Age groups SF1 Table P12 Census block

Level of education - adults without a high 

school diploma

ACS Table B15002 Tract

Households earning below the national 

median income

ACS Table B19001 Block group

People living below the poverty line ACS Table B17001 Tract

Linguistically isolated people ACS Table B16002 Block group

3. Calculation Methods

The HEM-3 models the cancer risk and noncancer hazard at a point near the geographic 

center of each census block and (optionally) at model user-defined receptors representing 

populations located within each 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 

HEM-3 modeling results for each block to the appropriate census statistics. This allowed us to 

estimate the numbers of people falling into different population categories within each block. We 

then analyzed the distribution of estimated inhalation risks within each population category, 

given the numbers of people within the category that are exposed to different risk levels. Each 

distribution involved a tabulation of all the census blocks modeled for the ferroalloys source

category. We also computed the average risk for all individuals in each population category. 

 

5. Census 2010 Data for the U.S. Virgin Islands http://www2.census.gov/census_2010/11-

Island_Areas_PUMS/Virgin_Islands/ prepared by the U.S. Census Bureau.

6. 2009 Five-year American Community Survey – 2005-2009, United States: 

http://www2.census.gov/acs2009_5yr/summaryfile/ prepared by the U.S. Census Bureau, 2011. 

7. HEM-3 generally uses the coordinates given by the census for the internal 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.
4

Distributions of risk and average risks were computed for the raw HEM-3 model results 

for the ferroalloys source category. For comparison, the nationwide demographic composition 

(i.e., population percentage in each demographic group for the country as a whole, based on the 

2010 Census) is also provided in the results table. 

Section 3.1 describes the calculation method used for categories where block-level data 

were available from the Census Bureau – racial, ethnic and age categories and the total 

population. Sections 3.2 through 3.5 describe calculation methods for categories where blocklevel data had to be estimated from tract or block group data provided by the Census Bureau –

education status, household income, poverty status, and linguistic isolation. 

3.1 Racial, Ethnic and Age Categories and the Total Population

Since race, ethnicity and age data are available at the census block level, the calculation 

of risk distributions for these categories involved a simple block-by-block accumulation of the 

people in each category. We began by identifying 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 ferroalloys source category:

H(Rab,s) = ∑i

(Ra≤Ri<Rb) [N(s,i)] (1)

where:

H(Rab,s) = the population count for risk bin Rab, which is between Ra and Rb for population 

subgroup “s”

Ri = the modeled risk level in block “í” (estimated lifetime cases of cancer per 

million population or noncancer hazard index)

∑i

(Ra≤Ri<Rb) refers to the summation over all blocks i where Ri falls in bin Rab, between Ra

and Rb

N(s,i) = the number of people within population subcategory s, in block i

The same approach was used for the total population. The average risk for a given population 

category or for the total population was then calculated using the following equation:

A(S) = ∑i [N(s,i) × Ri] ∕ ∑i [N(s,i)] (2)

where:

A(s) = the average risk for population subgroup “s” (estimated lifetime cases of cancer

per million population or noncancer hazard index)

∑i refers to the summation over all blocks “í” modeled for the emission source 

category

N(s,i) and Ri were defined above
5

3.2 Level of Education

Table B15002 of the 2005-2009 ACS dataset specifies the education status for men and 

women age 25 and older for each census tract, 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 people 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 4th

grade, up to the numbers of males and females who have completed some high school but not 

received a high school degree.

The number of adults without a high school degree as a fraction of the total population 

was assumed to be the same for each block in the tract. Thus, the number of adults without a 

high school degree in each block was computed as follows:

N(nhs,b/tc) = N(t,b/tc) × N(nhs,tc) ∕ N(t,tc) (3)

where:

N(nhs,b/tc) = number of adults without a high school diploma, in block “b” of tract “tc”

N(t,b/tc) = total number of people in block “b” of tract “tc”

N(nhs,tc) = number of adults without a high school diploma in tract “tc”

N(t,tc) = total number of people in tract “tc”

Equation (1) was then used to generate risk distributions based on the block-level results, and 

Equation (2) was used to compute the average risk for adults without a high school diploma. 

3.3 Household Income

Table B19001 of the 2005-2009 ACS dataset estimates the numbers of households in 

each block group with income for the year 2009 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 

2009 was about $50,000 per year. Therefore, in order to determine the number of households 

with incomes under the median income, we added the estimates for the ranges below that level. 

The following equation was used to estimate the fraction of households below the national 

median income within each census block group:

F(nm,bg) = [C<10 + C10-15 + .... + C35-40 + C40-45 + C45-50] ∕ CT (4)

where:

F(nm,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

C10-15 = number of households with incomes from $10,000 to $14,999

C35-40 = number of households with incomes from $35,000 to $39,999

C40-45 = number of households with incomes from $40,000 to $44,999
6

C45-50 = number of households with incomes from $45,000 to $49,999

CT = 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(nm,b/bg) = F(nm,bg) × N(t,b/bg) (5)

where:

N(nm,b/bg) = number of people in block “b” of block group “bg” living in households below 

the national median income

F(nm,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 distributions based on the block-level results, and 

Equation (2) was used to compute the average risk for people living in households below the 

national median income. It must be noted that this approach neglects any potential relationship 

between household size and income level within a particular block group. However, it is 

expected to provide a reasonable indication of the risk level of people living below the national 

median income, relative to the population as a whole. 

3.4 Poverty Level

Table B17001 of the 2005-2009 ACS dataset estimates the total number people in each 

census tract living below the poverty level, as well as the numbers of people below the poverty 

level in different age groups. The current study did not include an analysis of poverty status by 

age group, only of the total population below the poverty line. The fraction of people below the 

poverty line was assumed to be the same for each block in the census tract. Thus, the population

below the poverty line in each block was computed as follows:

N(p,b/tc) = N(T,b/tc) × N(p,tc) ∕ N(T,tc) (6)

where:

N(p,b/tc) = number of people below the poverty line in block “b” of tract “tc”

N(T,b/tc) = total number of people in block “b” of tract “tc”

N(p,tc) = number of people below the poverty line in tract “tc”

N(T,tc) = total number of people in tract “tc”

Equation (1) was then used to generate risk distributions based on the block-level results, and 

Equation (2) was used to compute the average risk for people living below the poverty level. 
7

3.5 Linguistic Isolation

Table B16002 of the 2005-2009 ACS dataset estimates the fraction of households in 

linguistic isolation in each block group. For this analysis, the fraction of people living in 

linguistic isolation for each block within the block group was assumed to be the same as the 

fraction of households in linguistic isolation for the block group. Thus, the population of 

linguistically isolated people in each block was computed as follows:

N(li,b/bg) = F(li,bg) × N(t,b/bg) (7)

where:

N(li,b/bg) = number of people in block “b” of block group “bg” living in linguistically 

isolated households

F(li,bg) = fraction of households in block group “bg” in linguistic isolation

N(t,b/bg) = total number of people in block “b” of block group “bg”

Equation (1) was then used to generate risk distributions based on the block-level results, and 

Equation (2) was used to compute the average risk for people living in linguistic isolation.

4. Results

The distribution of estimated lifetime inhalation cancer risks greater than or equal to 1 in 

a million and noncancer hazard indices greater than 1 for different demographic groups among

the population living near Ferroalloys facilities is shown in Table 2. For comparison purposes, 

Table 2 also provides the nationwide percentages of these various demographic groups. Detailed 

demographics data and analyses used to create Table 2 can be found in Appendix A of this 

document.

The results of the demographic analysis presented in Table 2 indicate that there are 

approximately 40,750 people exposed to a cancer risk greater than or equal to 1-in-1 million and 

approximately 1,350 people exposed to noncancer hazard index greater than 1. The demographic 

results for those impacted by source category emissions are below or similar to (i.e., within a 

couple percentage points of) their corresponding national percentages for all racial, ethnic, 

economic, educational, and linguistically isolated groups, as well as for most age groups. With 

respect to the “ages 65 and up” category potentially affected by Ferroalloys emissions, there is a 

modest percentage increase – of 5 percentage points for the cancer results and 6 percentage 

points for the noncancer results – compared to the corresponding national percentage for this 

demographic (13%). Overall, the demographic results do not indicate significant environmental 

justice concerns for the Ferroalloys source category for cancer risks and noncancer hazards.

 
8

Table 2. Summary of Demographic Assessment of Risk Results for the Ferroalloys Source Category

Emissions 

Basis

Demographic Group

Total Minority2

African 

American

Other and

Multiracial

Hispanic

or 

Latino

Native 

American

Ages 0 

to 17

Ages 18

to 64

Ages 65 

and up

Below the 

Poverty 

Level

Over 25 

Without a 

HS 

Diploma

Linguistic 

Isolation

Nationwide 

Demographic 

Breakdown

(2010 Census)

n/a 312,861,265 28% 13% 14% 17% 1.1% 24% 63% 13% 14% 15% 6.5%

Maximum 

Risk 

(in 1 

million)

Population With Cancer Risk Greater Than or Equal to 1 in 1 million 3

Source 

Category1 20 40,748 3% 1% 2% 1% 0.3% 21% 62% 18% 15% 11% 1%

Maximum 

Hazard 

Index

Population With Noncancer Hazard Index Greater Than 1 3

Source 

Category1 4 1,348 1% 0.2% 1% 0.7% 0.1% 22% 59% 19% 6% 10% 0%

Notes:

1Source Category emissions were estimated based on 2014 RTR data.

2Minority population is the total population minus the white population.

3Population figures are for the population residing within 50 km from the center of these facilities whose cancer risks are estimated to be greater 

than or equal to 1 in a million, or whose noncancer hazard indices are estimated to be greater than 1.
9

5. Uncertainty Discussion

Our analysis of the distribution of risks across various demographic groups is subject to 

the typical uncertainties associated with census data (e.g., errors in filling out and transcribing 

census forms), which are generally thought to be small, as well as the additional uncertainties 

associated with the extrapolation of census tract level data (e.g., education status and poverty 

status) and census block group data (e.g., income level and linguistic isolation) down to the 

census block level. 

The uncertainties in these risk estimates include 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 for environmental justice analyses. We present these 

analyses, with their associated uncertainties, to EPA decision makers and the public as additional 

analyses to inform RTR decisions.
10

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A-0

Appendix A
A-1

Total 

population White

African 

American

Native 

American

Other and 

multiracial

Hispanic or 

Latinoc

0 to 1 339,194 324,747 5,122 855 8,470 2,879

1 to 5 38,503 37,186 318 101 898 305

5 to 10 2,153 2,117 5 3 28 14

10 to 20 79 79 0 0 0 0

20 to 30 13 13 0 0 0 0

30 to 40 0 0 0 0 0 0

Total number 379,942 364,142 5,445 959 9,396 3,198

0.4517 0.4541 0.3489 0.4258 0.4197 0.4303

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

aModeled 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)

bDistributions by race are based on demographic information at the census block level. Risks from 

ferroalloys emissions were modeled at the census block level. 

Numbers of people in different ranges for lifetime cancer riskb

Modeled risk from the 

Ferroalloys source category
A-2

Total 

population

Ages 0 thru 

17

Ages 18 thru 

64

Ages 65 and 

up

0 to 1 339,194 70,773 214,612 53,809

1 to 5 38,503 7,880 23,748 6,875

5 to 10 2,153 475 1,283 395

10 to 20 79 15 45 19

20 to 30 13 2 7 4

30 to 40 0 0 0 0

Total number 379,942 79,145 239,695 61,102

0.4517 0.4526 0.4434 0.4834

Notes:

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

bDistributions by age are based on modeled risk and age data at the census block level.

Range of lifetime individual 

cancer risk (chance in one 

million)a

Numbers of people in different ranges for lifetime cancer 

riskb

Average risk (chances in one 

million)

aModeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and 

not adjusted for exposure factors.

Modeled risk from the Ferroalloys 

source category
A-3

Total 

population

Total number 

25 and older

Number 25 and older 

without a high school 

diploma

0 to 1 339,194 228,731 36,419

1 to 5 38,503 26,817 3,022

5 to 10 2,153 1,527 182

10 to 20 79 62 10

20 to 30 13 11 2

30 to 40 0 0 0

Total number 379,942 257,148 39,635

0.4517 0.4628 0.3931

Notes:

Table A-3. Distribution of Risk for Adults with and without a High School 

Diploma

bDistributions by education level are based on modeled risk at the census block level, and 

education data at the census tract level. All census blocks in a tract 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 riskb

Average risk (chances in one 

million)

aModeled risks are for a 70-year lifetime, based on the predicted outdoor concentration 

and not adjusted for exposure factors.

Modeled risk from the Ferroalloys 

source category
A-4

Total 

population

People living in 

households below 

the national median 

incomec

People living 

below the 

poverty line

0 to 1 339,194 214,228 71,197

1 to 5 38,503 22,213 5,899

5 to 10 2,153 1,300 217

10 to 20 79 54 13

20 to 30 13 9 2

30 to 40 0 0 0

Total number 379,942 237,804 77,328

0.4517 0.4343 0.3752

Notes:

c

The median income is the national median household income in 2009, about $50,000.

Average risk (chances in one 

million)

aModeled risks are for a 70-year lifetime, based on the predicted outdoor concentration 

and not adjusted for exposure factors.

bDistributions by income and poverty status are based on modeled risk at the census block 

level, income data at the block group level, and poverty status at the census tract level. 

All census blocks in a block group or tract are assumed to have the same income 

distribution or poverty status, respectively.

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 riskb

Modeled risk from the Ferroalloys 

source category
A-5

Total 

population

People living in 

linguistic isolation

0 to 1 339,194 1,831

1 to 5 38,503 206

5 to 10 2,153 0

10 to 20 79 0

20 to 30 13 0

30 to 40 0 0

Total number 379,942 2,037

0.4517 0.4065

Notes:

aModeled risks are for a 70-year lifetime, based on the predicted 

outdoor concentration and not adjusted for exposure factors.

bDistributions of linguistic isolation are based on modeled risk at the 

census block level, and linguistic isolation data at the block group 

level. All census blocks in a block group are assumed to have the 

same linguistic isolation population distributions.

Table A-5. Distribution of Risk for People Living in 

Linguistic Isolation

Range of lifetime individual 

cancer risk (chance in one 

million)a

Numbers of people in different 

ranges for lifetime cancer riskb

Average risk (chances in one 

million)

Modeled risk from the Ferroalloys 

source category
A-6

Total 

population White

African 

American

Native 

American

Other and 

multiracial

Hispanic or 

Latinoc

0 to 0.2 315,932 302,367 4,858 799 7,908 2,654

0.2 to 1 61,199 59,024 578 157 1,440 530

1 to < 2 1,463 1,422 6 1 34 4

2 to 3 1,138 1,119 3 2 14 6

3 to 4 210 210 0 0 0 4

4 to 5 0 0 0 0 0 0

Total number 379,942 364,142 5,445 959 9,396 3,198

0.1018 0.1024 0.0753 0.0969 0.0955 0.1004

Notes:

cThe 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-6. Distribution of Inhalation Hazard Indices for Racial and Ethnic Groups

aModeled 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 indexa

Average hazard index

bDistributions by race are based on demographic information at the census block level. Hazard Indices from 

ferroalloys emissions were modeled at the census block level. 

Modeled neurological hazard index from the 

Ferroalloys source category

Numbers of people in different ranges for lifetime hazard indicesb
A-7

Total 

population

Ages 0 thru 

17

Ages 18 thru 

64

Ages 65 and 

up

0 to 0.2 315,932 66,038 200,628 49,266

0.2 to 1 61,199 12,506 37,382 11,311

1 to < 2 1,463 307 891 265

2 to 3 1,138 255 665 218

3 to 4 210 39 129 42

4 to 5 0 0 0 0

Total number 379,942 79,145 239,695 61,102

0.1018 0.1017 0.0995 0.1111

Notes:

Table A-7. Distribution of Hazard Indices for Different Age Groups

Modeled neurological hazard index from the 

Ferroalloys source category

bDistributions by age are based on modeled hazard index and age data at the census block 

level.

Range of lifetime individual hazard 

indexa

Numbers of people in different ranges for lifetime hazard 

indicesb

Average hazard index

aModeled 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 0.2 315,932 211,959 34,518

0.2 to 1 61,199 43,166 4,905

1 to < 2 1,463 1,049 114

2 to 3 1,138 813 77

3 to 4 210 161 21

4 to 5 0 0 0

Total number 379,942 257,148 39,635

0.1018 0.1049 0.0851

Notes:

Table A-8. Distribution of Hazard Indices for Adults with and without a High 

School Diploma

Modeled neurological hazard index from the 

Ferroalloys source category

bDistributions by education level are based on modeled hazard index at the census block level, 

and education data at the census tract level. All census blocks in a tract are assumed to 

have the same education level distribution.

Range of lifetime individual hazard 

indexa

Numbers of people in different ranges for lifetime 

hazard indicesb

Average hazard index

aModeled 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 

incomec

People living 

below the 

poverty line

0 to 0.2 315,932 201,333 67,655

0.2 to 1 61,199 34,922 9,428

1 to < 2 1,463 777 160

2 to 3 1,138 647 75

3 to 4 210 125 10

4 to 5 0 0 0

Total number 379,942 237,804 77,328

0.1018 0.0962 0.0815

Notes:

c

The median income is the national median household income in 2009, about $50,000.

Modeled neurological hazard index from the 

Ferroalloys source category

Average hazard index

aModeled hazard indices are for a 70-year lifetime, based on the predicted outdoor 

concentration and not adjusted for exposure factors.

bDistributions by income and poverty status are based on modeled hazard index at the 

census block level, income data at the block group level, and poverty status at the census 

tract level. All census blocks in a block group or tract are assumed to have the same 

income distribution or poverty status, respectively.

Table A-9. Distribution of Hazard Indices for People Living in Households 

below the National Median Income and Below the Poverty Line

Range of lifetime individual 

hazard indexa

Numbers of people in different ranges for lifetime 

hazard indicesb
A-10 Total 

population

People living in 

linguistic isolation

0 to 0.2 315,932 1,737

0.2 to 1 61,199 300

1 to < 2 1,463 0

2 to 3 1,138 0

3 to 4 210 0

4 to 5 0 0

Total number 379,942 2,037

0.1018 0.0969

Notes:

aModeled hazard indices are for a 70-year lifetime, based on the 

predicted outdoor concentration and not adjusted for exposure 

bDistributions of linguistic isolation are based on modeled hazard 

index at the census block level, and linguistic isolation data at the 

block group level. All census blocks in a block group are assumed 

to have the same linguistic isolation population distributions.

Table A-10. Distribution of Hazard Indices for People 

Living in Linguistic Isolation

Range of lifetime individual 

hazard indexa

Numbers of people in different 

ranges for lifetime hazard 

indicesb

Modeled neurological hazard index from the 

Ferroalloys source category

Average hazard index