# Risk and Technology Review - Analysis of Socio-Economic Factors for Populations Living Near Primary Aluminum 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. 1-03

Prepared for: Regina Chappell, Work Assignment Manager Community and Tribal Programs Group Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27711

July 24, 2014ii 

### 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-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 Categor ies and the Total Population 4 3.2 Level of Education 4 3.3 Household Income 5 3.4 Poverty Level 6 3.5 Linguistic Isolation 6 4. Results 7 5. Uncertainty Discussion 9 Appendix A A-1iv1 

## 1. Introduction

This document describes the approach used to evaluate the potential cancer risks associated with inhalation and air-related e xposures to hazardous ai r pollutants (HAP) in different social, demographic, and economic gr oups within the population living near primary aluminum facilities in the United States. This work was carried out in support of the U.S. Environmental Protection Agency ’s Residual Risk and Technol ogy Review (RTR) for primary aluminum source category emissions subject to Maximum Availa ble Control Technology (MACT) requirements under 40 CFR 63 Subpart LL. In the RTR analysis, the Human Exposure Model, Version 3 (HEM-3) 1,2,3 was used to estimate cancer risks due to the inhalation of HAP for the populations residing within 50 kilometers of primary aluminum facilities in the U.S. HEM-3 estimates can cer risks at the level of census blocks using the AERMOD state-of-t he-art air dispersion model developed under the direction of the American Mete orological Society (AMS) / EP A Regulatory Model Improvement Committee (AERMIC). Each census block typi cally includes about 50 people. Additional information on the risk analysis is available in the docket for the National Emission Standards for Hazardous Air Pollutant Emissions for Primary Aluminum Reduction Plants rulemaking. The docket provides a report coveri ng the inputs and specific assumptions, and addressing uncertainties. In the current analysis, cancer risk estimates from the primary aluminum HEM-3 modeling effort were linked to detailed census data in order to evaluate the distributio n of risks for different demographic groups (including racial, ethnic, ag e, economic, educational, and linguistically isolated populati on categories). The following popul ation categories were included in this analysis:

 Total population

 White

 Minority

 African American (or Black)

 Native Americans

 Other races and multiracial

1. EC/R. January 2014. Modeling for the Residual Risk and Technology Review Using the Human Exposure M odel 3 – AERMOD Version. Technical Support Document prepared by EC/R Incorporated for the U.S

. Env ironmental Protection Agency, Research Triangle Park , NC. 2. EC/R. April 2014. The HEM-3 User’s Guide. Prepar ed by EC/R Incorporated for the U.S. Environmen tal Pro tection Agency, Research Triangle Park, NC. h ttp://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 I ncorporated for the U.S. Environmental Pr otection Agency, Research Tr iangle Park, NC. h ttp://www2.epa.gov/sites/production/files/2 014-04/documents/multi_hem-3_users_guide.pdf2  Hispanic or Latino

 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 re flect the estimated level of cancer risk that would be experienced by an indi vidual residing within the block boundaries for 70 years. In this analysis, the demographic composition of the popul ation estimated to experience a risk greater than 1 in 1 million as a result of primary alum inum emissions is compared to the demographic composition of the overa ll nationwide population. 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 the analysis, showing the source of each dataset and the level of geogra phic 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. Dist ributions regarding educational status and poverty status are at the tract level. A censu s block contains about 50 people on average; and a block group c ontains about 28 blocks on aver age, or about 1,400 people. A census tract is larger than a bl ock group, with each tract containi ng an average of 3 block groups, or about 4,300 people. Data on race, ethnicity, and age were obtai ned 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 P acific Islander, other race, and two or more races. In the current analysis, the Asian, Nativ e 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 ethni city. SF1 covers the 50 states, the District of Columbia, and Pu erto Rico, but does not cover th e Virgin Islands. Data for the Virgin Islands can be retrieved from similar tables in the Virgin Islands Summary File. 5

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. 5. Census 2010 Data for the U.S. Virgin Islands h ttp://www2.census.gov/census_2010/11- Island_Areas_PUMS/Virgin_Islands/ prepared by the U.S. Census Bureau

.3 Data on education level, household income, poverty status, and lingui stic 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 us ed to Analyze Risks for Different Socio-economic Groups

Type of population cat egory 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 povert y line ACS Table B17001 Tract Linguistically isolated peopl e ACS Table B16002 Block group


## 3. Calculation Methods

The HEM-3 models the cancer risk and non cancer 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 identifi cation codes to link the HEM-3 modeling results for each block to the appropr iate census statistics. This allowed us to estimate the numbers of people falling into diffe rent 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 primary aluminum source category. We also computed the aver age risk for all individuals in each population category. Distributions of risk and average risks we re computed for the raw HEM-3 model results for the primary aluminum 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 and 2009 ACS) is al so provided in the results table.

6. 2009 Five-year American Community Survey – 2005-2009, United States: h ttp://www2.census.gov/ acs2009_5yr/summaryfile/ prepared by the U.S. Census Bureau, 201 1. 7. HEM-3 generally uses the coordinates given by the census for the internal point, or “centroid” of eac h block. However, when the footprint of an industrial facility includes the block centroid, the mode l is designed to identify the highest-risk point outside of the facility’s footprin t.4 Section 3.1 describes the calcu lation method used for categor ies where block-level data were available from the Census Bureau – ra cial, 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 pr ovided by the Census Bureau – education status, household income, povert y status, and linguistic isolation.


### 3.1 Racial, Ethnic and Age Categor ies and the Total Population
Since race, ethnicity and age data are availa ble at the census block level, the calculation of risk distributions for these categories involved a simple bl ock-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 th en added together for all of the blocks modeled for the primary aluminum source category: H(R ab ,s) = ∑ i (Ra ≤ Ri<Rb) [N(s,i)] (1)
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) ∑ 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 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) × 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) ∑ 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 Level of Education
Table B15002 of the 2005-2009 ACS dataset specifi es the education status for men and women age 25 and older for each census tract, ba sed on the last grade completed. To obtain the total number of adults without a high school de gree, 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 no5 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 th e tract. Thus, the number of adults without a high school degree in each bloc k 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 withou t 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 ri sk for adults without a high school diploma.



### 3.3 Household Income

Table B19001 of the 2005-2009 ACS dataset es timates 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 or der 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 th e fraction of households below the national median income within each census block group: F(nm,bg) = [C <10 + C 10-15 + .... + C 35-40 + C 40-45 + C 45-50 ] ⁄ C T (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 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 45-50 = number of households w ith incomes from $45,000 to $49,999 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.6 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” livi ng 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 inhouseholds 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 livi ng below the national median income, relative to the population as a whole.



### 3.4 Poverty Level

Table B17001 of the 2005-2009 ACS dataset es timates the total number people in each census tract living below the poverty level, as we ll 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 bl ock 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 pove rty line in block “b” of tract “tc” N(T,b/tc) = total number of peopl e in block “b” of tract “tc” N(p,tc) = number of people belo w 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 ri sk for people living below the poverty level.


### 3.5 Linguistic Isolation

Table B16002 of the 2005-2009 ACS dataset estim ates the fraction of households in linguistic isolation in each bl ock group. For this analysis, th e fraction of people living in linguistic isolation for each blo ck within the bl ock group was assumed to be the same as the fraction of households in lingui stic isolation for the block group. Thus, the population of linguistically isolated people in e ach block was computed as follows: N(li,b/bg) = F(li ,bg) × N(t,b/bg) (7)7 where: N(li,b/bg) = number of people in block “b” of block group “bg” liv ing in linguistically isolated households F(li,bg) = fraction of hous eholds 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 ri sk for people living in linguistic isolation.


## 4. Results

The distribution of estimated lifetime inhalation cancer risks greater th an or equal to 1 in a million for different demographic groups amon g the population living near primary aluminum is shown in Table 2. For comparison purposes, Ta ble 2 also provides the nationwide percentages of these various demographic groups. Detailed de mographics data and anal yses used to create Table 2 can be found in Appendix A of this document. The results of the analysis presented in Table 2 indicate that there are approximately 880,000 people exposed to a cancer risk greater than or equal to 1-in-1 million as a result of primary aluminum emissions. The specific demogra phic results indicate that the percentage of the population potentially impacted by primary alumin um emissions is less than or equal to its corresponding national per centage for every demographic cate gory shown in Table 2. The results reveal no disproportionate impacts on the demographi c categories examined in this analysis.8Table 2. Summary of Demographic Assessment of Risk Results for the Primary Aluminum Source CategoryEmissionsBasisDemographic GroupTotal Minority2AfricanAmericanOther andMultiracialHispanicorLatinoNativeAmericanAges 0to 17Ages 18to 64Ages 65and upBelow thePovertyLevelOver 25Without aHSDiplomaLinguisticIsolationNationwideDemographicBreakdown(2010 Census;2009 ACS)n/a 312,861,265 28% 13% 14% 17% 1.1% 24% 63% 13% 14% 15% 6.5%MaximumRisk(in 1million)Population With Cancer Risk GreaterThan or Equal to 1 in 1 million3SourceCategory170 881,307 20% 13% 6% 5% 0.9% 24% 63% 13% 14% 14% 1.6%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 kmfrom the center of these facilities whose cancer risks are estimated to be greaterthan or equal to 1 in a million.9 

## 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 extrapolati on 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 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.10 This page intentionally left blankA-1 

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

0 to 1 1907630 1568926 212516 14190 111998 125999 1 to 5 707102 559406 101449 4776 41471 33664 5 to 10 109685 92577 9802 1611 5695 3543 10 to 20 38547 33044 2375 996 2132 1653 20 to 30 17749 14887 1434 523 905 732 30 to 40 6302 5415 536 68 283 188 40 to 50 1449 1203 42 157 47 32 50 to 100 473 460 1 3 9 13 100 to 150 0 0 0000 Total number 2,788,937 2,275,918 328,155 22,324 162,540 165,824

1.3759 1.38 1.306 2.4835 1.3079 1.0439 Notes:

c The Hispanic or Latino population is double-counted in this analysis, since different individuals within the cate g or y

ma y classif y

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 primary aluminum emissions were modeled at the census block level. Modeled risk from the Primary Aluminum source category Numbers of people in different ranges for lifetime cancer risk bA-3 Total population Ages 0 thru 17 Ages 18 thru 64 Ages 65 and up

0 to 1 1907630 432201 1202973 272456 1 to 5 707102 169400 446759 90943 5 to 10 109685 27131 67764 14790 10 to 20 38547 10015 23790 4742 20 to 30 17749 4404 11064 2281 30 to 40 6302 1529 3864 909 40 to 50 1449 377 871 201 50 to 100 473 102 305 66 100 to 150 0 0 0 0 Total number 2,788,937 645,159 1,757,390 386,388

1.3759 1.4389 1.3656 1.3176 Notes: Table A-2. Distribution of Risk for Different Age Groups

Modeled risk from the Primary Aluminum source category

b Distributions 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 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 1907630 1270395 202645 1 to 5 707102 465947 67549 5 to 10 109685 73667 8345 10 to 20 38547 25279 3021 20 to 30 17749 11927 1497 30 to 40 6302 4248 618 40 to 50 1449 971 134 50 to 100 473 337 49 100 to 150 0 0 0 Total number 2,788,937 1,852,771 283,858

1.3759 1.3752 1.2484 Notes: Table A-3. Distribution of Risk for Adults with and without a High School Diploma

Modeled risk from the Primary Aluminum source category

b Distributions 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 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 1907630 1065243 314833 1 to 5 707102 390017 101832 5 to 10 109685 50903 10483 10 to 20 38547 19128 4298 20 to 30 17749 7780 1980 30 to 40 6302 3065 650 40 to 50 1449 669 217 50 to 100 473 218 41 100 to 150 0 0 0 Total number 2,788,937 1,537,023 434,334

1.3759 1.3052 1.1729 Notes:

c The median income is the national median household income in 2009 , about $50 , 000. Modeled risk from the Primary Aluminum source category

Average risk (chances in one million)

a Modeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and not ad j usted for ex p osure factors. b Distributions 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 risk bA-6 Total population People living in linguistic isolation

0 to 1 1907630 34287 1 to 5 707102 11926 5 to 10 109685 1345 10 to 20 38547 387 20 to 30 17749 148 30 to 40 6302 24 40 to 50 1449 4 50 to 100 473 0 100 to 150 0 0 Total number 2,788,937 48,121

1.3759 1.1162 Notes:

a Modeled risks are for a 70-year lifetime, based on the predicted outdoor concentration and not ad j usted for ex p osure factors. b Distributions 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 risk b

Modeled risk from the Primary Aluminum source category

Average risk (chances in one million)