# Risk and Technology Review -

Analysis of Socio-Economic Factors for Populations Living Near Steel Pickling 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. 3-14

Prepared for:

Terri Hollingsworth, Work Assignment Manager Sector Based Analysis Group Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27514

August 10, 2010ii 

### 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.iii 

## 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 6 3.5 Poverty Level 7 4. Results 8 5. Uncertainty Discussion 10iv1 

## 1. Introduction

This document describes the approach used to evaluate the potential chronic noncancer risks that may affect differen t social, demographic and economi c groups within the populations living near steel pickling fac ilities associated with inhala tion exposures to hazardous air pollutants (HAP) emitted by these fa cilities. This work was carried out in support of the U.S. Environmental Protection Agency ’s Residual Risk and Techno logy Review (RTR) for steel pickling emissions subject to Maximum Ava ilable Control Technology (MACT) requirements under 40 CFR 63 Subpart CCC.

In the RTR analysis, risks due to the inha lation of HAP were modeled for the populations residing within 50 kilometers of each steel pi ckling facility using the Human Exposure Model, Version 3 (HEM3). 1,2 HEM3 estimates cancer and noncancer risks at the level of census blocks using the AERMOD state-of-the-art air dispersion model devel oped under the direction of the American Meteorological Society (AMS) / EPA Regulatory Model Improvement Committee (AERMIC). Each census block typically include s 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: Hard and Decorative Chromium Electroplating and Chromium Anodizing Tanks; Group 1 Polymers and Resins; Marine Tank Vessel Loading Operations; Pharmaceuticals Pr oduction; the Printing and P ublishing Industry; and Steel Pickling – HCl Process Facilities and Hy drochloric Acid Regeneration Plants rulemaking where a memo to the docket is provided, for the steel pickling sour ce category, covering the inputs and specific assumptions, and addressing uncertainties specific to the category.

In the current analysis, cancer risk pred ictions from the steel pickling HEM3 modeling effort were linked to detailed cen sus data in order to evaluate the distribution of risks for different social, demographic and economic gr oups. The following popul ation categories were studied:

 Total population

 White

 African American (or Black)

 Native Americans

 Other races and multiracial

 Hispanic or Latino

 Children 18 years of age and under

 Adults 19 to 64 years of age

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.gov /ttn/fera/human_hem.html#guide2  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 bloc k reflect the level of risk that would be experienced by an individual residing in the bl ock for 70 years. In addition, the HEM3 risk estimates are not adjusted for commuting patte rns or for the difference between indoor and outdoor pollutant concentrations.

The distributions of source category risks across the vari ous demographic groups were compared to: 1) those associated with HAP at the facilities containing the source category (i.e., “facility-wide”); and 2) nationwide distributio ns of each of the demographic groups. The “facility-wide” and nationwide inhalation risks we re obtained from the final National-scale Air Toxics Assessment (NATA) for 2005, which estimates the risks associated with HAP emissions from all stationary sources, onroad and nonroad mobile sources, dispersed area sources, and the background due to long-range tr ansport and natural emissions. 3 Two separate analyses of the risk distributions were performed. One focu sed on the demographics of those individuals projected to experience a risk of 1 in a million or greater. The other focused on the demographics of those individuals living within 5 kilometers of a steel pickling facility, regardless of the projected risk.

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. EPA. 2009. National Air Toxics Assessments. U.S. Environmental Protection Agency, Research Triangle Park, NC. http://www.epa.gov/ttn/atw/natamain/3 Table 1. Summary of Census Data usedto Analyze Risks for Different Socioeconomic Groups

Type of population category 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. 4 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. 5

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. 6 SF3 data for Puerto Rico were obtai ned from the Census Department website, 7 and data for the Virgin Islands were retrieved from similar tables in the Virgin Islands Summary File. 5

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

4. 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.

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

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

7. Census. 2008. SF3 Data for Puerto Rico. U.S. Census Bureau, Washington, D.C. www.factfinder.census.gov4 each census block group. Table P37 analyzes the level of education attained by men and women 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 risk at a poi nt near the geographi c center of each census block. 8 For the current analysis, this risk estim ate was assumed to appl y to all individuals residing in the block. We used block identification codes to link the HEM3 modeling results for each block to the appropriate census statistics. This allowed us to estimate the numbers of people falling into different population subcategor ies within each block. We then analyzed the distribution of estimated inhala tion risks within each population subcategory, giving the numbers of people within the subcategory that are exposed to different ri sk levels. Each distribution involved a tabulation of all the census blocks modeled for the st eel pickling source category. We also computed the average risk for all i ndividuals in each population subcategory.

Distributions of risk and average risks we re computed for the raw HEM3 model results for steel pickling. For comparison, distributions of risk and aver age risks were also computed for all emission sources at the fa cility (including steel pickling) (e.g., “f acility-wide”), and in the country as a whole.

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 steel pickling 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”

8 HEM3 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.5 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 populat ion. The average risk for a given population subcategory or for the total population wa s 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 blocks “í” modeled for the emission source category N(s,i) and R i were defined above

It must be noted that in the overall NATA ri sk analysis, only stat ionary sources were modeled at the census block level. Risks due to onroad and nonroad mobile emissions sources, dispersed area sources, and ambient background levels of HAP were analyzed at the census tract level instead of the block level. EPA chose this larger scale of analysis for these categories for two reasons. First, the locations of these sources are not known definitively. Rather, the geographic distribution of emissi ons for these categories has been estimated from county level emissions data. Second, emissions from these categories are believed to be more uniformly distributed within a given county or census tract. Therefore, in the current analysis, we have assumed that the NATA risks for mobile sources , area sources, and background pollutant levels are the same for all blocks within a given census tract. As note d above, stationary source risk estimates were available at the census block level.



### 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:6 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” 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.



### 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 $5000 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 incomes7 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 $49,000 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 me dian 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 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.



### 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:8 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 pollutants emitted from the steel pickling process are hydrogen chloride and chlorine. Neither of these pollutants have a cancer dose-response value, so estimated lifetime inhalation cancer risks were not calculated for the source category, so these demographic analyses are based on noncancer risks, or hazard indices (HI). The dist ribution of maximum HIs above 1 for different racial and ethnic groups among the population livin g near steel pickling facilities is shown in Table 2. For comparison, Table 2 provides th e distributions of HIs for the population exposed to emissions from all source cat egories at the steel pickling facility (i.e., facility-wide) and for the nationwide demographic breakdown (i.e., nationwide). The facilitywide and nationwide HIs were obtained from th e final NATA for 2005, which estimates the risks associated with HAP emissions from all stationa ry sources, onroad and nonroad mobile sources, dispersed area sources, and the background due to long-range transport and natural emissions. For the detailed demographic analysis used to create Table 2, see Appendix A of this document.

The results of the demographic analysis presen ted in Table 2 show th at for those with HI greater than 1 due to the stee l pickling source category, HIs may be lower for all demographic groups, with the exceptio n of the “Ages 19 to 64” and the “Ages 65 and up” demographic groups, than we would normally expect, based on the typical distribution of those demographic groups across the U.S. The results of the demogr aphic analysis for the facility-wide emissions show that for those with HI greater than 1 due to the facility-wide emissions, HIs may be significantly higher for the “African American” demographic group and somewhat higher for the “Minority” demographic group than we would norma lly expect based on th e typical distribution of those demographic groups across the U.S.9Table 2. Summary of Demographic AssessmentResults for the Steel Pickling Source CategoryPopulation With RespiratoryHazard Index Greater Than 1EmissionsBasisMaximumRespiratoryHazardIndexTotal MinorityAfricanAmericanOther andMultiracialHispanicor LatinoNativeAmericanAges 0to 18Ages 19to 64Ages 65and upBelowthePovertyLevelOver 25Withouta HSDiplomaSourceCategory2 45 0% 0% 0% 9% 0% 26% 63% 11% 6% 9%Facility-wide 10 1,657 41% 34% 6% 1% 0.2% 25% 62% 13% 11% 13%NationwideDemographicBreakdownn/a 174,737,524 32% 16% 15% 16% 0.6% 27% 61% 12% 13% 13%Notes:Source Category, Facility-wide, and Nationwide emissionsare based on the final 2005 NATA, dated May 2010.Minority population is the total population minus the white population.Population figures are for the population residing within 5 km of these facilities.The percentage of the minority population experiencing HI greater than 1 from the source category could be greater than 0% as 4hispanic/latino people are double counted inthis analysis.10 

## 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 expo sure, and in dose response relationships that are associated with our source category risk estima tes. The degree of uncertainty associated with facility-wide risk estimates, based on the 2005 NAT A, dated May 2010, is generally greater than for source categories because emissions data fo r source categories not currently undergoing an RTR review may be incomplete.

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 in form RTR decisions.A-1 

### Appendix ATotal population White African American Native American Other and multiracial Hispanic or
Latino c

0 to 0.2 2,430,795 1,295,667 823,486 10,623 301,019 296,779 0.2 to 1 1,476 1,417 5 3 51 74

1 to 1.5 13 13 0 0 0 0
1.5 to 2 32 32 0004 Total number 2,432,316 1,297,129 823,491 10,626 301,070 296,857
0.0018 0.0025 0.0011 0.0012 0.0008 0.0011

0 to 0.2 2,319,606 1,220,276 803,609 9,837 285,884 276,794 0.2 to 1 111,053 75,869 19,314 785 15,085 20,041

1 to 1.5 1,260 758 400 4 98 17
1.5 to 2 355 215 13 7035

2 to 5 40 11 29 0 0 0
5 to 10 0 0 0 0 0 0 10 and over 2 0 2000 Total number 2,432,316 1,297,129 823,491 10,626 301,070 296,857 0.04 0.0453 0.0329 0.0464 0.0358 0.0431

Notes: Numbers of people in different ranges for respiratory hazard indices b

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 Respiratory 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 respiratory
hazard index a

Average HI

b Distributions by race are based on demographic information at the census block level. Risks from steel pickling emissions were modeled at the block level, as were other NATA stationary source emissions. Mobile sources, area sources, and background risks were analyzed at the census block level in NATA. Modeled risk from the steel pickling category

Modeled risk from facilities containing steel pickling source category

Average HI

A

‐ 2Total population Ages 0 thru 18 Ages 19 thru 64 Ages 65 and
up

0 to 0.2 2,430,795 714,793 1,398,059 317,943 0.2 to 1 1,476 381 923 172

1 to 1.5 13 3 9 1
1.5 to 2 32 8 20 4 Total number 2,432,316 715,186 1,399,011 318,120
0.0018 0.0017 0.0019 0.0018

0 to 0.2 2,319,606 680,226 1,333,166 306,214 0.2 to 1 111,053 34,538 64,825 11,691

1 to 1.5 1,260 329 786 146 1.5 to 2 355 85 209 61

2 to 5 40 9 23 8
5 to 10 0 0 0 0 10 and over 2010 Total number 2,432,316 715,186 1,399,011 318,120
0.04 0.0405 0.0401 0.038

Notes: Table A-2. Distribution of Respiratory Hazard Indices for Different Age Groups

Modeled risk from the steel pickling category

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

Average HI

a Modeled hazard indices are for a 70-year lifetime, based on the predicted outdoor concentration Modeled risk from facilities containing steel pickling source category

Average HI

A

‐ 3Total population Total number 25 and older Number 25 and older without a high school diploma

0 to 0.2 2,430,795 1,507,852 395,071 0.2 to 1 1,476 1,003 124

1 to 1.5 13 8 1
1.5 to 2 32 22 3 Total number 2,432,316 1,508,885 395,198
0.0018 0.0019 0.0013

0 to 0.2 2,319,606 1,441,017 372,890 0.2 to 1 111,053 66,751 22,095

1 to 1.5 1,260 841 145 1.5 to 2 355 247 59

2 to 5 40 29 8
5 to 10 0 0 0 10 and over 2 1 0 Total number 2,432,316 1,508,885 395,198 0.04 0.0399 0.0453
Notes: Table A-3. Distribution of Respirator y Hazard Indices for Adults with and without a High School Diploma

Modeled risk from the steel pickling category

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

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

Average HI

a Modeled hazard indices are for a 70-year lifetime, based on the predicted outdoor concentration and not adjusted for exposure factors. Modeled risk from facilities containing steel pickling source category

Average HI

A

‐ 4Total population People living in households below the national median
income c People living below the poverty line

0 to 0.2 2,430,795 1,426,666 432,702 0.2 to 1 1,476 585 96

1 to 1.5 13 4 1
1.5 to 2 32 13 2 Total number 2,432,316 1,427,269 432,801
0.0018 0.0015 0.0012

0 to 0.2 2,319,606 1,359,763 410,439 0.2 to 1 111,053 66,573 22,182

1 to 1.5 1,260 714 146 1.5 to 2 355 196 31

2 to 5 40 22 3
5 to 10 0 0 0 10 and over 2 1 0 Total number 2,432,316 1,427,269 432,801
0.04 0.0405 0.0425
Notes: Table A-4. Distribution of Respiratory Hazard Indices for People Living in Households below the National Median Income and Below the Poverty Line

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

Average HI

c The median income is the national median household income in 1999, about $41,000. Modeled risk from the steel pickling category

Average HI

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 age and income distribution. Modeled risk from facilities containing steel pickling source category

A

‐ 5A-6Table A-5. Distribution of Respiratory Hazard Indicesafor Racial and Ethnic Groups, Age Groups, Adults without a HighSchool Diploma, and People Living inHouseholds Below the Poverty LineTotalpopulation MinoritycAfricanAmericanNativeAmericanOther andmultiracialHispanicor LatinodAges 0thru 18Ages 19thru 64Ages 65and upNumber25 andolderwithout ahighschooldiplomaPeople livingbelow the povertylineModeled HI from the steel pickling categoryTotal population within 5 km offacilitiesb2,432,316 1,135,187 823,491 10,626 301,070 296,857 715,186 1,399,011 318,120 395,198 432,801Percentage of total47% 34% 0.4% 12% 12% 29% 58% 13% 16% 18%Average HI 0.0018 0.0010 0.0011 0.0012 0.0008 0.0011 0.0017 0.0019 0.0018 0.0013 0.0012Modeled HI from facilities containing steel pickling source categoryTotal population within 5 km offacilitiesb2,432,316 1,135,187 823,491 10,626 301,070 296,857 715,186 1,399,011 318,120 395,198 432,801Percentage of total47% 34% 0.4% 12% 12% 29% 58% 13% 16% 18%Average HI 0.040 0.034 0.033 0.046 0.036 0.043 0.041 0.040 0.038 0.045 0.043Nationwide demographic breakdownTotal population285,339,128 70,799,422 35,043,873 2,489,515 33,265,937 39,083,760 77,245,364 172,602,490 35,491,274 36,660,464 37,181,029Percentage of total25% 12% 0.9% 12% 14% 27% 60% 12% 13% 13%Notes:a Modeled HIs are for a 70-year lifetime, based on the predictedoutdoor concentration and not adjusted for exposure factors.b Distributions by race are based on demographic information at the census block level.Distributions of other demographic groups are based on the extrapolation ofcensus block group level data to thecensus block level. Risks from steel pickling emissions were modeled at the block level.c The minority population is the total population minus the white population.d 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.