# Risk and Technology Review -

Analysis of Socio-Economic Factors for Populations Living Near Marine Vessel Loading 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 Assessment Group Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, North Carolina 27514

August 6, 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.

## 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 10iv1 

## 1. Introduction

This document describes the approach used to evaluate the potential cancer risks that may affect different social, demogr aphic, and economic groups within the populations living near marine vessel loading facilities associated with inhalation expo sures to hazardous air pollutants (HAP) emitted by these facilities. This wo rk was carried out in support of the U.S. Environmental Protection Agency ’s Residual Risk and Technol ogy Review (RTR) for marine vessel loading emissions subject to Maxi mum Available Control Technology (MACT) requirements under 40 CFR 63 Subpart Y.

In the RTR analysis, risks due to the inha lation of HAP were modeled for the populations residing within 50 kilometers of each marine ve ssel loading facility using the Human Exposure Model, Version 3 (HEM3). 1,2 HEM3 estimates cancer and non cancer risks at the level of census blocks using the AERMOD state-o f-the-art air dispersion model de veloped 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 an d Decorative Chromium Electroplating and Chromium Anodizing Tanks; Group I Polymers and Resins; Marine Tank Vessel Loading Operations; Pharmaceuticals Production; The Pr inting and Publishing Industry; and Steel Pickling--HCl Process Facilities and Hy drochloric Acid Regeneration Plants rulemaking where a memo to the docket is provided, coveri ng the inputs and specific assumptions, and addressing uncertainties specific to each category.

In the current analysis, cancer risk pred ictions from the marine vessel loading HEM3 modeling effort were linked to detailed census data in order to evaluate the distributio n of risks for different social, demogra phic and economic groups. The following population categories were studied:

 Total population

 White

 Minority

 African American (or Black)

 Native Americans

 Other races and multiracial

 Hispanic or Latino

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  Children 18 years of age and under

 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 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 sources at the facilities containing the source category (i.e., “facility-wide”); and 2) nationwid e distributions of each of the demographics groups. The “facility-wide” and nationwide inha lation risks were obtained from the final National-scale Air Toxics Assessment (NATA) for 2005, which estimates the risks associated with HAP emissions from all stationary source s, onroad and nonroad mob ile sources, dispersed area sources, and the background due to long- range transport and natural emissions. 3 Two separate analyses of the risk distributions were performed. One focused 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 w ithin 5 kilometers of a marine vessel loading 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 marine vessel loading source category. We also computed the 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 marine vessel loading. For comparison, distri butions of risk and average risks were also computed for all emission sources at the facility (including marine vessel loading) (e.g., “facilitywide”), 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 mari ne vessel loading 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 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 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.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 $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 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 $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.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 for different racial and ethnic groups among the pop ulation living near ma rine vessel loading facilities is shown in Table 2. For comparison, Table 2 provides the distributions of inhalation risks for the population exposed to emissions fr om all source categories at the marine vessel loading facility (i.e., facility -wide) and for the nationwid e demographic breakdown (i.e., nationwide). The facility-wide and nationwide risks were obtained from the final 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 longrange 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 pres ented in Table 2 show that for those with cancer risk greater than one in a million due to the marine vessel loading source category, risks may be significantly higher for the “Hispanic or Latino” demographic group and somewhat higher for the “Other and Multiracial” demogra phic group than we would normally expect, based on the typical distribution of those demographic groups across the U.S. The cancer risk for the remaining demographic groups is very close to or slightly lower th an the typical U.S. distribution. The results of the demographic analysis for the faci lity-wide emissions show that with the exception of the “Minority” and “Afr ican American demographic groups, which are somewhat higher than the source category and the typical U.S. distribution, the remaining demographic groups are similar to the results of the source category.9Table 2. Summary of Demographic Assessment Results for the Marine Vessel Loading Source CategoryPopulation With Risk Greater Than 1 in 1 millionEmissions BasisMaximumRisk(in 1million)Total MinorityAfricanAmericanOther andMultiracialHispanicor LatinoNativeAmericanAges 0to 18Ages 19to 64Ages 65and upBelowthePovertyLevelOver 25Withouta HSDiplomaSourceCategory20 64,579 29% 7% 21% 38% 0.6% 31% 57% 11% 15% 19%Facility-wide 200 814,872 38% 18% 19% 34% 0.5% 32% 59% 10% 18% 18%NationwideDemographicBreakdownn/a 285,339,128 25% 12% 12% 14% 0.9% 27% 60% 12% 13% 13%Notes:Source Category, Facility-wide, and Nationwide emissions are based on the 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.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 exposure and in dose response relationships that are associated with our source category risk estimates. 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 inform RTR decisions.A-1 

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

0 to 1 6,164,710 3,367,081 1,365,464 43,625 1,388,540 1,335,970 1 to 5 59,920 42,237 4,636 342 12,705 22,213 5 to 10 3,661 2,855 29 36 741 1,863 10 to 20 604 390 13 5 196 420 20 to 30 394 242 13 4 135 275 Total number 6,229,289 3,412,805 1,370,155 44,012 1,402,317 1,360,741

0.06 0.06 0.03 0.05 0.06 0.12

0 to 1 5,414,417 2,908,577 1,221,126 39,861 1,244,853 1,085,927 1 to 5 364,024 234,800 90,681 1,490 37,053 57,776 5 to 10 267,026 165,434 40,118 1,503 59,971 109,304 10 to 20 129,137 73,786 13,700 794 40,857 72,244 20 to 30 31,391 16,548 3,443 247 11,153 20,602 30 to 40 10,743 5,742 542 52 4,407 6,370 40 to 50 5,122 3,405 165 27 1,525 3,432 50 to 100 5,594 3,435 361 27 1,771 3,551 100 to 150 1,147 666 11 7 463 967 150 to 200 682 406 8 4 264 562 200 to 250 6 6 0006 Total number 6,229,289 3,412,805 1,370,155 44,012 1,402,317 1,360,741

1.1 1.1 0.6 0.9 1.3 2.4

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 marine vessel loading 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 marine vessel loading category

Modeled risk from facilities containing marine vessel loading source category

Average risk (chances in one million) Numbers of people in different ranges for lifetime cancer risk b

A

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

0 to 1 6,164,710 1,652,374 3,759,411 752,925 1 to 5 59,920 18,798 34,184 6,938 5 to 10 3,661 1,212 2,073 376
10 to 20 604 202 364 38 20 to 30 394 124 249 21 Total number 6,229,289 1,672,710 3,796,281 760,298

0.06 0.07 0.054 0.045

0 to 1 5,414,417 1,415,641 3,316,785 681,991 1 to 5 364,024 109,719 216,731 37,574 5 to 10 267,026 85,347 157,282 24,397 10 to 20 129,137 42,542 74,904 11,691 20 to 30 31,391 11,132 17,713 2,546 30 to 40 10,743 3,787 5,912 1,044 40 to 50 5,122 1,868 2,839 415 50 to 100 5,594 2,016 3,026 552 100 to 150 1,147 418 675 54 150 to 200 682 237 410 35 200 to 250 6240 Total number 6,229,289 1,672,710 3,796,281 760,298

1.1 1.3 1.0 0.8

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

Modeled risk from the marine vessel loading 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 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 Modeled risk from facilities containing marine vessel loading source category

Average risk (chances in one million)

A

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

0 to 1 6,164,710 3,974,795 1,075,242 1 to 5 59,920 35,930 11,208 5 to 10 3,661 2,082 822 10 to 20 604 331 175 20 to 30 394 214 105 Total number 6,229,289 4,013,352 1,087,552

0.06 0.05 0.07

0 to 1 5,414,417 3,530,843 937,318 1 to 5 364,024 224,415 52,655 5 to 10 267,026 155,047 52,347 10 to 20 129,137 73,276 30,600 20 to 30 31,391 17,019 8,338 30 to 40 10,743 5,928 2,912 40 to 50 5,122 2,774 1,378 50 to 100 5,594 3,113 1,460 100 to 150 1,147 582 343 150 to 200 682 352 198 200 to 250 6 3 2 Total number 6,229,289 4,013,352 1,087,552

1.1 0.9 1.4
Notes:

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

Modeled risk from the marine vessel loading 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 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. Modeled risk from facilities containing marine vessel loading source category

Average risk (chances in one million)

A

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

0 to 1 6,164,710 3,504,463 1,273,411 1 to 5 59,920 33,741 8,990 5 to 10 3,661 2,217 708 10 to 20 604 407 154 20 to 30 394 225 62 Total number 6,229,289 3,541,053 1,283,325

0.06 0.06 0.05

0 to 1 5,414,417 3,073,530 1,138,839 1 to 5 364,024 196,004 59,290 5 to 10 267,026 154,541 47,617 10 to 20 129,137 81,400 25,516 20 to 30 31,391 20,874 6,978 30 to 40 10,743 6,696 2,146 40 to 50 5,122 3,267 1,225 50 to 100 5,594 3,516 1,240 100 to 150 1,147 805 333 150 to 200 682 415 138 200 to 250 6 4 2 Total number 6,229,289 3,541,053 1,283,325

1.1 1.1 1.0
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

Average risk (chances in one million)

c The median income is the national median household income in 1999, about $41,000. Modeled risk from the marine vessel loading 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 age and income distribution. Modeled risk from facilities containing marine vessel loading source category

A

‐ 5A-6Table A-5. Distribution of Inhalation Cancer Riskafor Racial and Ethnic Groups, Age Groups, Adults without a High School Diploma, and PeopleLiving in Households Below the Poverty LineTotalpopulation MinoritycAfricanAmericanNativeAmericanOther andmultiracialHispanicor LatinodAges 0thru 18Ages 19thru 64Ages 65and upNumber25 andolderwithout ahighschooldiplomaPeopleliving belowthe povertylineModeled risk from the marine vessel loading categoryTotal population within 5 km offacilitiesb6,229,289 2,816,484 1,370,155 44,012 1,402,317 1,360,741 1,672,710 3,796,281 760,298 1,087,552 1,283,325Percentage of total45% 22% 0.7% 23% 22% 27% 61% 12% 17% 21%Average risk (in one million) 0.06 0.050.03 0.05 0.06 0.12 0.07 0.05 0.05 0.07 0.05Modeled risk from facilities containingmarine vessel loading source categoryTotal population within 5 km offacilitiesb6,229,289 2,816,484 1,370,155 44,012 1,402,317 1,360,741 1,672,710 3,796,281 760,298 1,087,552 1,283,325Percentage of total45% 22% 0.7% 23% 22% 27% 61% 12% 17% 21%Average risk (in one million) 1.1 1.00.6 0.9 1.3 2.4 1.3 1.0 0.8 1.4 1.0Nationwide demographic breakdownTotal populationb285,339,128 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 risks are for a 70-year lifetime, based on the predicted outdoor concentration and notadjusted for exposure factors.b Distributions by race are based on demographic information at the census block level.Distribution of other demographic groups are based on the extrapolation ofcensus block group level data to thecensus block level. Risks from marine vessel loading 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.