Potential Adverse Impacts Under the Definition of Solid Waste
Exclusions (Including Potential Disproportionate Adverse Impacts
to Minority and Low-Income Populations)
Volume 2 - Assessment of Disproportionate Adverse Impacts
December 2014
Office of Solid Waste and Emergency Response
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue
Washington D.C. 20460
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Table of Contents
1 Identification of Potentially Affected Communities 2
1.1 Notification Facilities 3
1.2 Damage Case Facilities 4
1.3 Hazardous Waste Facilities 5
1.3.1 Facilities Currently Generating Recyclable Hazardous Wastes 5
1.3.2 Facilities Currently Managing Recyclable Hazardous Wastes Received from
OffSite 8
1.4 Non-Hazardous Industrial Waste 10
1.5 Commercial Disposal and Treatment Facilities 11
1.5.1 Landfill, Surface Impoundment, Land Application, Incineration, and Energy
Recovery Facilities 12
1.5.2 Underground Injection and Fuel Blending Facilities 14
2 Analysis of Demographics of Potentially Affected Communities 15
2.1 Demographic Data Sources 15
2.2 Methodol ogy 18
2.2.1 Selection of EJ Characteristics for Analysis 18
2.2.2 Areal Apportionment Method 18
2.2.3 Comparison of Demographic Characteristics of Affected Population versus
Comparison Population 20
2.2.4 Statistical Analysis 20
2.3 Statistical Comparison of Demographic Characteristics of Affected Population
versus Comparison Population 20
2.4 Results of Demographic Analysis 22
2.4.1 Notification Facilities 23
2.4.2 Damage Case Facilities 28
2.4.3 Hazardous Waste Facilities 32
2.4.4 Non-Hazardous Industrial Waste Facilities 36
3 Comparison of Hazardous Waste Facilities to Commercial Hazardous Waste Treatment and
Disposal Facilities That Do Not Recycle 40
4 Sensitivity Analysis 42
5 Other Factors that Affect Vulnerability in Communities 45
5.1 Overview of Factors that Affect Vulnerability 45
5.1.1 Susceptible Populations 45
5.1.2 Multipl e and Cumul ative Effects 45
5.1.3 Unique Exposure Pathways 47
5.1.4 Ability to Participate in Decision-Making Process 47
5.1.5 Physical Infrastructure 48
5.2 Summary of Analysis of Factors that Affect Vulnerability for 61 Notification
Facilities 49
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6 Summary of Results: Assessment of Disproportion Adverse Impacts 54
6.1 Community-level and Population-level Impacts 54
6.2 Underlying Vulnerabilities Traditionally Associated with Minority and Low-
Income Communities Pose the Potential to Exacerbate Potential Adverse Impacts
of the DSW Rule 57
6.3 Preventative and Mitigative Steps That Address the Potential Adverse Impacts to
Minority and Low-Income Communities 59
6.3.1 Implementation Measures 61
Attachment A. Methodology for Identifying Potentially Recyclable Hazardous Wastes A-l
Attachment B. Statistical Calculations B-2
Attachment C. Acronyms and Abbreviations C-l
Attachment D. Glossary D-l
Attachment E. State, Urban and Rural Analyses E-l
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Purpose and Organization of Document
This report is Volume 2 of EPA's environmental justice analysis for the Definition of
Solid Waste rule. Volume 1: Hazard Characterization analyzes the potential for adverse
impacts to all potentially affected communities from the 2008 DSW rule.
The purpose of Volume 2 is to analyze the potential for disproportionate impacts to
minority and/or low-income community.
The report is organized as follows:
Section 1 identifies and characterizes facilities that could be affected by the DSW
rule.
Section 2 presents an analysis of demographic data about the communities
surrounding the facilities identified in Section 1. EPA performed the analysis by
examining the demographics of the community surrounding each facility,
including race, income level, and children under five years old. EPA then
compared the demographics of each community to those at the national and state
levels, and by urban and rural communities, to identify communities that may
potentially have EJ concerns.
Section 3 performs a baseline analysis comparing hazardous waste facilities to
commercial hazardous waste treatment and disposal facilities.
Section 4 presents a sensitivity analysis done on the communities in close
proximity to notification facilities.
Section 5 describes other factors that could affect the vulnerability of
communities, such as populations susceptible to DSW hazards, multiple and
cumulative effects of releases and contamination, and unique exposure pathways.
Section 6 summarizes the conclusions from analysis described in this report.
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1 Identification of Potentially Affected Communities
This section identifies the facilities potentially affected by the DSW rule that may adversely
impact the adjacent community. There are three general categories of DSW facilities that are
recycling, or may in the future recycle under the rule:
1. Facilities that have notified that they are operating under the 2008 DSW rule exclusion
(hereafter referred to as "notification facilities"). These are the facilities most clearly
linked with the DSW rule because they are actually operating under the 2008 DSW rule.
However, these "early adopters" of the DSW exclusion are unlikely to be representative
of the full universe of facilities that would operate under the DSW exclusions once they
are fully implemented. The notifiers are only located in the small number of states that
have adopted the 2008 DSW rule. However, once the revised final rule goes into effect,
EPA expects that a much larger universe of facilities will adopt the rule, greatly
expanding the potential universe of facilities. Also, the regulatory uncertainty has likely
led to the fact that all off-site recycling under the 2008 DSW transfer-based exclusion has
been at RCRA permitted facilities, who already have the infrastructure to recycling the
materials.
2. Facilities that are currently managing regulated hazardous waste, but may find it
economical to participate under the DSW rule in the future once the rule is fully
implemented. These facilities include RCRA permitted facilities that are managing
recyclable hazardous secondary materials and facilities that generate recyclable
hazardous secondary materials at large enough quantities to make it economically
justifiable will switch to on-site reclamation under the DSW rule (hereafter referred to as
"hazardous waste facilities") because these facilities are located nation-wide, their
inclusion helps address the state location bias in the notification facilities.
3. Newly established recycling facilities that are not currently managing hazardous waste or
hazardous secondary materials that may choose to begin reclaiming hazardous secondary
materials under the DSW rule. While EPA has location data on the first two categories,
the locations for the third set of facilities is unknown. However, these are also the types
of facilities most likely to adversely impact adjacent communities because (unlike the
first two categories) they have never had a RCRA permit or otherwise been subject to
RCRA regulations. To help model the potential distributional impacts of this category of
facility, EPA has selected two data sets to act as surrogates for these "new" recycling
facilities.
F acilities in EPA's An Assessment of Environmental Problems Associated with
Recycling of Hazardous Secondary1 Materials, many of which operated under
exclusions or reduced regulations (hereafter referred to as "damage case
facilities");
1 This document, also known as the "Environmental Problems Study" or "study," contains information about
environmental damage cases and the types of potential hazards from the mismanagement of the HSMs. The
document was originally published in January 2007 in support of the 2008 DSW Final Rule. Since the
Environmental Problems Study was published in 2007, EPA has continued to assess new reports of environmental
problems associated with the recycling of HSMs and, based on this information has updated the study on several
occasions. The latest version of the Environmental Problems Study is dated May 3, 2012.
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Facilities currently recycling non-hazardous industrial waste (e.g., antifreeze) that
could most easily switch or expand to recycling under the current DSW
exclusions (hereafter referred to as "non-hazardous industrial waste facilities").
These two sets of industrial recycling facilities were selected because they were subject
to the same type of local siting restrictions and other political and social pressures as
future DSW recycling facilities will also be subject to, and therefore the demographics
surrounding these facilities are likely to be similar. The "damage case" facility list is
EPA's most comprehensive set of information about hazardous secondary materials
recyclers. However, EPA acknowledges that the fact that these are damage case
recycling facilities could also impact the demographics. Therefore the non-hazardous
industrial recycling facilities were chosen in order to balance the use of the damage case
recycling facilities. Because these facilities have similar industrial processes, any
difference between the demographics surrounding the two classes of facilities may be
attributable to the difference in environmental damage. Therefore, the demographic
results are presented separately in order to provide the most complete information on
potential demographics at these facilities.
It is important to note that for the hazardous waste facilities, the damage case facilities and the
non-hazardous industrial waste facilities, EPA is not predicting that these specific facilities
would recycle under the DSW rule but rather that their demographics reflect the types of
facilities that would recycle in the future. Moreover, by including the damage case facilities,
EPA is not stating that the same types of damages would automatically occur under the DSW
rule. Instead, these data sets are surrogates to determine the types of communities where future
facilities that would recycle under the DSW exclusion would likely be located.
In addition, this section identifies commercial disposal and treatment facilities. These facilities
represent the "baseline" waste management scenario and may be affected by the DSW
exclusions as hazardous waste disposal switches to recycling.
Detailed information on each set of facilities is found below.
1.1 Notification Facilities
As of February 27, 2012, 61 facilities submitted notifications to EPA that they would manage
their HSM under the current DSW exclusions. These include facilities from Idaho, Iowa, New
Jersey, Pennsylvania, Puerto Rico and the Virgin Islands. Because the current DSW exclusions
are deregulatory in nature, they are only effective in states and territories that are not authorized
to implement their own RCRA base programs, and those states with authorized programs that
modify their programs to adopt it. As of February 27th Idaho, Illinois, New Jersey, and
Pennsylvania have adopted the 2008 DSW final rule. The RCRA hazardous waste programs in
Iowa, Puerto Rico, and the Virgin Islands are not authorized to implement the 2008 DSW final
rule.
This report examines the 61 facilities that notified as of February 27, 2012 that they are
following the current DSW exclusions. EPA maintains an updated list of notification facilities at
http://www.epa.gov/epawaste/hazard/dsw/notifv-sum.pdf. For each of the 61 notification
facilities, EPA compiled information from data sources, such as their notification forms and
other environmental reporting data sources, such as the RCRA Subtitle C Site Identification (Site
ID) Forms and the most recent Hazardous Waste Report (also known as the "Biennial Report" or
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"BR") filed by the facility between 2001 and 2007. If the facility did not file a 2001-2007 BR,
EPA obtained information from the Handler Module in RCRAInfo or from the Facility Registry
System (FRS) database in Envirofacts (at
http://www.epa.gov/enviro/html/fii/fii query iava.html).
From these data sources, EPA compiled the following information:
Facility EPA identification (ID) number;
Facility name; and
Facility location address (i.e., street address, city, state, and zip code);
EPA then compiled information on facility location coordinates (i.e., latitude and longitude)
from the FRS database in Envirofacts. Where such data were not available from these sources,
EPA used the facility address and publicly available mapping software (i.e. Google Earth) or
geocoding software to identify the facility latitude and longitude.
EPA recognizes that facility addresses and location coordinate information sometimes are not the
same as the location in which HSM generation, storage, or reclamation activities might occur.
For example, the FRS may have location information for a corporate headquarters rather than
production and processing facilities. However, given the national level of analysis, as well as the
uncertainties inherent in the analysis in predicting future facility locations, EPA has determined
that using facility address information is adequate for general rulemaking purposes, and that any
additional refinement based on physical verification would not merit the additional resources
needed.
EPA further determined whether any of the notification facilities were one of the 250 damage
cases included in the Environmental Problems Study. Based on this review, none of the 61
notification facilities is a damage case facility.
1.2 Damage Case Facilities
The Environmental Problems Study examines the 250 facilities in which environmental damage
of some kind occurred from some type of recycling activity, and that appeared to clearly fit
within the scope of the study. In this context, EPA used the term "environmental damage"
broadly to include leaks, spills, dumps or other types of releases of hazardous substances into the
environment that were serious enough to require some type of cleanup action. The term also
includes situations in which materials were abandoned (e.g., in warehouses) without having been
actually released into the environment, but which posed potential threats and thus required
removal actions that were conducted by one or more government agencies, and involved
expenditure of public funds.
For each of the 250 damage case facilities, EPA compiled the following information:
Facility EPA ID number;
Facility name; and
Facility location address (i.e., street address, city, state, and zip code).
EPA then compiled information on facility location coordinates (i.e., latitude and longitude)
from the FRS database in Envirofacts. EPA recognizes that facility addresses and location
coordinate information sometimes are not the same as the location in which the environmental
damage occurred. For example, the FRS may have location information for a corporate
headquarters rather than production and processing facilities. However, field investigation of
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potentially thousands of facility locations to verify and correct GIS coordinates was beyond the
scope of this analysis.
1.3 Hazardous Waste Facilities
EPA identified the facilities that are currently generating or managing recyclable hazardous
wastes that may be likely to begin operating under the current DSW exclusions. EPA assumed
that these facilities may choose to operate under this rule, regardless of whether the state has
adopted the rule.2 This assessment was made based on a review of hazardous waste generation
and management activities conducted at each of the facilities as reported in the BR, which
contains the most comprehensive information available about such activities. For this analysis,
EPA assumed that facilities that currently generate or manage recyclable hazardous wastes at
large enough quantities to make it economically justifiable would switch to recycling under the
current DSW exclusions.3'
1.3.1 Facilities Currently Generating Recyclable Hazardous Wastes
Facilities that currently generate recyclable hazardous wastes may begin recycling them under
the generator-based exclusion of the current DSW exclusions. However, not all facilities that
currently generate recyclable hazardous wastes will choose to begin recycling them under the
current DSW exclusions. EPA believes that facilities will primarily choose to do so when it is
less expensive to recycle the hazardous wastes under the current DSW exclusions than to manage
them under the hazardous waste regulations. For purposes of this analysis, EPA made the
following assumptions:
All facilities currently generating and managing (onsite or offsite) their recyclable
hazardous wastes through recycling will continue to do so under the current DSW
exclusions. Because these facilities would not experience a change in their hazardous
waste management activities under the current DSW exclusions, EPA did not include
them in the analysis.
For facilities currently generating and managing their recyclable hazardous wastes onsite
through other management methods (e.g., incineration, solidification/stabilization), EPA
assumed that the expense associated with replacing the existing hazardous waste
management units with on-site recycling units would not be economically justifiable.
Therefore, EPA did not include these facilities in the analysis.
For facilities currently generating and shipping their recyclable hazardous wastes offsite
for management through other management methods, EPA identified which facilities
may choose to operate under the current DSW exclusions based on the amount of
recyclable hazardous waste generated by the facility. Facilities that generate more than a
truckload (25 tons) of solvent waste annually are assumed to begin managing that waste
by recycling under the current DSW exclusions. Facilities that generate less than a
truckload (25 tons) of solvent waste annually are assumed to be unlikely to conduct
activities under the current DSW exclusions.
2 EPA, Draft Environmental Justice Methodology for the Definition of Solid Waste Final Rule, January 13, 2010, P.
18. Available online at: http://www.epa.gov/osw/hazard/dsw/ei-meth.pdf.
3 Id. P 17
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Transporters haul materials in many different types of vehicles, including tankers, 18-
wheel box and flatbed trucks, and vacuum tankers. DOT regulations specify that trucks
must weigh less than 80,000 pounds, which, when the weight of the tractor is factored in,
leaves a maximum of 50,000 pounds, or 25 tons, for material. For liquid shipments,
tanker trucks have a capacity of 7,000 gallons, which (depending on the density of the
liquid), translates to roughly 24 tons. Based on this, EPA assumed that a full truckload of
hazardous waste would contain about 25 tons of waste. However, the actual amount of
hazardous waste in a full truckload will vary based on factors such as the density of the
waste, the packaging, and other factors.
Based on the above assumptions, EPA assumed that facilities that are currently generating and
shipping more than a truckload (25 tons) of solvent wastes offsite for management through other
management methods may switch to recycling under the current DSW exclusions.
To identify and collect information about facilities currently generating recyclable hazardous
waste that may begin managing them under the generator-based exclusion of the current DSW
exclusions, EPA performed the following steps:
1. Compiled information on hazardous wastes generated by facilities. To compile
information on hazardous wastes generated by facilities and on the off-site
management methods associated with each of these materials, EPA collected
information from Section 1 (Generation) and Section 3 (Off-site Shipment) of the
Generation and Management (GM) Forms of the 2007 BR. From these data sources,
EPA compiled the following information:
Reporting year;
EPA ID of facility generating the waste;
Name of facility generating the waste;
BR form (i.e., GM);
Page and subpage number;
Source code;
Source code description;
Form code;
Form code description;
EPA hazardous waste codes representing the waste;
Waste description;
Quantity of hazardous waste generated;
Management method code;
Management method code description;
Quantity of recyclable hazardous waste managed, by management method code;
Indicator of whether the waste was managed through recycling activities
(i.e., recycled); and
Indicator of whether the waste is considered a "recyclable hazardous waste."
For purposes of this analysis, "recycling" activities are those associated with the
management of wastes using one of the following management methods: metals
recovery (BR management method code HO 10), solvents recovery (BR management
method code H020), and other recovery (BR management method code H039).
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In determining whether a waste is considered a "recyclable hazardous waste," EPA
used the methodology developed for the Regulatory Impact Analysis (RIA) of the
2011 DSW proposed rule.4 This methodology was designed to identify waste
quantities that may be physically and chemically sufficient for potential future
switchover to recycling under the DSW rule exclusions. In particular, the
methodology relies on some of the data reported in the BR (e.g., BR form codes, BR
source codes, EPA hazardous waste codes) to determine if a waste is a recyclable
hazardous waste. Each recyclable hazardous waste is categorized within a
"commodity group" according to each of the three BR recycling methods: metals
recovery, solvent recovery, and other recovery. Attachment A describes the RIA
methodology. Note that this methodology was only applied to hazardous wastes
managed through methods other than recycling (i.e., methods other than metals
recovery, solvents recovery, and other recovery).
2. Identifiedfacilities that currently generate recyclable hazardous wastes that may
begin recycling them under the generator-based exclusion of the current DSW
exclusions. EPA identified facilities currently generating and shipping offsite more
than a truckload (25 tons) of solvent wastes annually for management through
methods other than recycling as those that would begin recycling under the generator-
based exclusion of the current DSW exclusions. Facilities were identified by
referring to data compiled under Step 1.
3. Compiled information about location coordinates. EPA then compiled information
on facility location coordinates (i.e., latitude and longitude) from the FRS database in
Envirofacts. Where such data were not available, EPA used the facility address and
geocoding software to identify the facility latitude and longitude. EPA recognizes
that facility addresses and location coordinate information sometimes are not the
same as the location in which HSM generation, storage, or reclamation activities
might occur. For example, the FRS may have location information for a corporate
headquarters rather than production and processing facilities. However, field
investigation of potentially thousands of facility locations to verify and correct GIS
coordinates was beyond the scope of this analysis. The success rate of the geocoding
is dependent on the quality of the location address data. The most accurate
coordinates were obtained when street addresses could be recognized and located by
the geocoding software. Generally, about 70 to 80 percent of the addresses can be
recognized and located by the geocoding software. In instances in which addresses
could not be geocoded (e.g., inaccurate or missing street addresses, PO boxes or rural
routes), EPA used Internet searches of company Web sites or Internet business
listings to obtain more accurate facility location addresses or facility coordinates.
4. Excludedfacilities that submitted notification to EPA indicating that they would be
managing hazardous secondary materials under the 2008 DSWfinal rule. From the
list of facilities developed under Steps 2 and 3, EPA identified and excluded facilities
that already notified EPA that they would be managing HSMs under the 2008 DSW
4 EPA, Regulatory Impact Analysis of EPA's 2011 Proposed Revisions to the Industrial Recycling Exclusions of the
RCRA Definition of Solid Waste, June 30, 2011. Available online at:
http://www.regulations. gov/#!documentDetail:D=EPA-HQ-RCRA-2010-0742-0002.
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final rule, since these facilities are being analyzed under Section 2.4.1 of this
document ("Notification Facilities").
5. Excludedfacilities included in the Environmental Problems Study. From the list of
facilities developed under Steps 2 and 3, EPA identified and excluded those facilities
included in the Environmental Problems Study, since these facilities are being
analyzed under Section 2.4.2 of this document ("Damage Case Facilities").
1.3.2 Facilities Currently Managing Recyclable Hazardous Wastes Received from
OffSite
Facilities that currently manage recyclable hazardous wastes received from offsite may begin
recycling them under the transfer-based exclusion of the current DSW exclusions. However, not
all facilities that currently manage recyclable hazardous wastes received from offsite will choose
to begin recycling them under the current DSW exclusions. EPA believes that facilities will
primarily choose to do so when it is less expensive to recycle the hazardous wastes under the
current DSW exclusions than to manage them under the hazardous waste regulations. For
purposes of this analysis, EPA made the following assumptions:
All facilities that are currently managing recyclable hazardous wastes received from
offsite through recycling will continue to manage those wastes by recycling under the
DSW exclusion. Because these facilities would not experience a change in their
hazardous waste management activities under the current DSW exclusions, EPA did not
include them in the analysis.
For facilities currently managing recyclable hazardous wastes received from offsite
through other management methods (e.g., incineration, solidification/stabilization), EPA
identified which facilities may choose to operate under the current DSW exclusions based
on the amount of recyclable hazardous waste managed by the facility. Facilities that
manage more than a truckload (25 tons) of annually are assumed to begin managing that
waste by recycling under the current DSW exclusions. Facilities that manage less than a
truckload (25 tons) of recyclable hazardous waste annually are assumed to be unlikely to
conduct activities under the current DSW exclusions.
Transporters haul materials in many different types of vehicles, including tankers, 18-
wheel box and flatbed trucks, and vacuum tankers. DOT regulations specify that trucks
must weigh less than 80,000 pounds, which, when the weight of the tractor is factored in,
leaves a maximum of 50,000 pounds, or 25 tons, for material. For liquid shipments,
tanker trucks have a capacity of 7,000 gallons, which (depending on the density of the
liquid), translates to roughly 24 tons. Based on this, EPA assumed that a full truckload of
hazardous waste would contain about 25 tons of waste. However, the actual amount of
hazardous waste in a full truckload will vary based on factors such as the density of the
waste, the packaging, and other factors.
Based on the above assumptions, EPA assumed that facilities currently managing more than a
truckload (25 tons) of recyclable hazardous wastes received from offsite through other
management methods may switch to recycling under the current DSW exclusions.
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To identify and collect information about facilities currently managing recyclable hazardous
wastes that may begin managing them under the transfer-based exclusion of the current DSW
exclusions, EPA conducted the following steps:
1. Compiled information on hazardous wastes managed by facilities. To compile
information on hazardous wastes received from offsite for management through
methods other than recycling, EPA collected information from Waste Received from
Off-site (WR) Forms of the 2007 BR. From this data source, EPA compiled the
following information, as applicable:
Reporting year;
EPA ID of facility managing the waste;
Name of the facility managing the waste;
BR form (i.e., WR);
Page and subpage number;
Form code;
Form code description;
EPA hazardous waste codes representing the waste;
Waste description;
Management method code;
Management method code description;
Quantity of hazardous waste managed, by management method code;
Indicator of whether the hazardous waste was managed through recycling
activities (i.e., recycled); and
Indicator of whether the waste is considered a "recyclable hazardous waste."
For purposes of this analysis, "recycling" activities are those associated with the
management of wastes using one of the following management methods: metals
recovery (BR management method code HO 10), solvents recovery (BR management
method code H020), and other recovery (BR management method code H039).
In determining whether a waste is considered a "recyclable hazardous waste," EPA
used the methodology developed for the RIA of the 2011 DSW proposed rule.5 This
methodology was designed to identify waste quantities that may be physically and
chemically sufficient for potential future switchover to recycling under the DSW rule
exclusions. In particular, the methodology relies on some of the data reported in the
BR (e.g., BR form codes, BR source codes, EPA hazardous waste codes) to determine
if a waste is a recyclable hazardous waste. Each recyclable hazardous waste is
categorized within a "commodity group" according to each of the three BR recycling
methods: metals recovery, solvent recovery, and other recovery. Attachment A
describes the RIA methodology. Note that this methodology was only applied to
hazardous wastes managed through methods other than recycling (i.e., methods other
than metals recovery, solvents recovery, and other recovery).
5 EPA, Regulatory Impact Analysis of EPA's 2011 Proposed Revisions to the Industrial Recycling Exclusions of the
RCRA Definition of Solid Waste, June 30, 2011. Available online at:
http://www.regulations. gov/#!documentDetail:D=EPA-HO-RCRA-2010-0742-0002.
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2. Identified facilities that currently manage recyclable hazardous wastes and may
begin recycling them under the transfer-based exclusion of the current DSW
exclusions. EPA identified facilities currently managing more than a truckload (25
tons) of recyclable hazardous wastes received from offsite through other management
methods as those that would begin recycling under the current DSW exclusions.
Facilities were identified by referring to data compiled under Step 1.
3. Compiled information about location coordinates. EPA then compiled information
on facility location coordinates (i.e., latitude and longitude) from the FRS database in
Envirofacts. Where such data were not available, EPA used the facility address and
geocoding software to identify the facility latitude and longitude. EPA recognizes
that facility addresses and location coordinate information sometimes are not the
same as the location in which HSM generation, storage, or reclamation activities
might occur. For example, the FRS may have location information for a corporate
headquarters rather than production and processing facilities. However, field
investigation of potentially thousands of facility locations to verify and correct GIS
coordinates was beyond the scope of this analysis. The success rate of the geocoding
is dependent on the quality of the location address data. The most accurate
coordinates were obtained when street addresses could be recognized and located by
the geocoding software. Generally, about 70 to 80 percent of the addresses can be
recognized and located by the geocoding software. In instances where addresses
could not be geocoded (e.g., inaccurate or missing street addresses, PO boxes or rural
routes), EPA used internet searches of company websites or internet business listings
to obtain more accurate facility location addresses or facility coordinates.
4. Excludedfacilities that submitted notification to EPA indicating that they would be
managing hazardous secondary materials under the 2008 DSWfinal rule. From the
list of facilities developed under Steps 2 and 3, EPA identified and excluded those
facilities that already notified EPA that they would be managing HSMs under the
current DSW exclusions, since these facilities are being analyzed under Section 2.4.1
of this document ("Notification Facilities")
5. Excludedfacilities included in the Environmental Problems Study. From the list of
facilities developed under Steps 2 and 3, EPA identified and excluded those facilities
included in the Environmental Problems Study, since these facilities are being
analyzed under Section 2.4.2 of this document ("Damage Case Facilities").
6. Excludedfacilities that may begin recycling their recyclable hazardous wastes under
the generator-based exclusion of the current DSW exclusions. From the list of
facilities developed under Steps 2 and 3, EPA identified and excluded those facilities
that may begin recycling their recyclable hazardous wastes under the generator-based
exclusion of the current DSW exclusions, since these facilities are being analyzed
under Section 2.4.3.1 of this document ("Facilities Currently Generating Recyclable
Hazardous Wastes").
1.4 Non-Hazardous Industrial Waste
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In addition to facilities currently generating or managing hazardous waste, some facilities that do
not currently generate or manage hazardous waste may begin recycling HSM under the current
DSW exclusions. Non-hazardous industrial recycling facilities were used to represent these
types of facilities in the demographic analysis not because EPA predicts that any one of these
facilities would begin recycling under the DSW rule, but rather because, as a class, these
industrial recycling facilities were subject to the same type of local siting restrictions and other
political and social pressures as future DSW recycling facilities will also be subject to, and
therefore the demographics surrounding these facilities are likely to be similar.
In addition, these industrial recycling facilities were chosen in order to balance the use of the
damage case recycling facilities. Because these facilities have similar industrial processes, any
difference between the demographics surrounding the two classes of facilities may be
attributable to the difference in environmental damage. Therefore, the demographic results are
presented separately in order to provide the most complete information on potential
demographics at these facilities.
EPA identified commercial non-hazardous industrial waste recycling facilities by identifying
non-hazardous industrial waste recycling facilities in the following data sources:
EPA databases (e.g., Wastewise Database, Toxics Release Inventory (TRI));
Department of Energy's report entitled "Used Oil Re-Refining Study to Address
Energy Policy Act of 2005 Section 1838;"
Chartwell's "Directory & Atlas of Solid Waste Disposal Facilities;"
Waste Business Journal Databases;
Hazardous Waste Consultant; and
Internet research (e.g., state Web sites, company Web sites).
EPA then excluded:
Facilities that submitted notification to EPA indicating that they would be
managing HSMs under the current DSW exclusions;
Facilities that reported generating or managing hazardous wastes in 2007 to the
BR; and
Facilities that appeared to conduct only physical separation and processing, such
as scrap metal recyclers.
EPA then compiled general information about the facilities from the data sources listed above.
The information compiled included the types of waste recycled and facility address. EPA then
performed geocoding using facility location address information. EPA recognizes that facility
addresses and location coordinate information sometimes are not the same as the location in
which HSM generation, storage, or reclamation activities might occur. For example, the FRS
may have location information for a corporate headquarters rather than production and
processing facilities. However, field investigation of potentially thousands of facility locations
to verify and correct GIS coordinates was beyond the scope of this analysis.
1.5 Commercial Disposal and Treatment Facilities
EPA identified disposal and treatment facilities that offer management services to other entities
(i.e., "commercial" disposal and treatment facilities) versus disposal and treatment facilities that
11
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exclusively manage waste generated at the same facility or received from another facility under
the same organization or parent company (i.e., "non-commercial" disposal and treatment
facilities).
For purposes of this analysis, "disposal and treatment facilities" include facilities that manage
hazardous wastes in the following types of units:
Landfill;
Surface impoundment;
Land application;
Underground injection;
Incineration; and
Energy Recovery (includes thermal treatment units and fuel blending).
Information on commercial landfill, surface impoundment, land application, incineration, and
energy recovery facilities (i.e., all of the above types of facilities with the exception of
underground injection and fuel blending facilities) was available from a previous effort
undertaken by EPA in September 20106, and is used in this analysis. Information on
underground injection and fuel blending facilities was compiled as part of this effort. The
following sections describe the methodologies used in each of these efforts.
1.5.1 Landfill, Surface Impoundment, Land Application, Incineration, and Energy
Recovery Facilities
For purposes of this methodology, commercial landfill, surface impoundment, land application,
incineration, and energy recovery facilities are those that:
Reported management of hazardous waste by the corresponding management method in
the BR;
Have an operating unit that is actively managing RCRA hazardous waste as indicated in
the RCRAInfo7 Permit Module; and
Use that unit for commercial purposes as indicated in the RCRAInfo Permit Module.
A facility that meets all of the above criteria for a particular management method is considered to
be commercial. Otherwise, the facility is non-commercial. Under this methodology, a facility
may be commercial for one type of management (e.g., landfill) and non-commercial for another
type of management (e.g., incineration). A description of the approach for identifying
commercial landfill, surface impoundment, land application, incineration, and energy recovery
facilities is provided below.
6 Work performed under EPA Contract No. EP-W-07-003, Work Assignment No. 3-01.
7 The Resource Conservation and Recovery Act Information (RCRAInfo) system is a national program
management and inventory system used by EPA to track entities regulated under Subtitle C of the Resource
Conservation and Recovery Act (RCRA).
12
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In identifying commercial landfill, surface impoundment, land application, incineration, and
energy recovery facilities, EPA first verified that managers had the unit necessary to perform the
reported management in the BR, using Process Code8 data in the RCRAInfo Permit Module. For
example, if a manager reported incineration in the BR, we verified that the manager had an
incineration unit in the RCRAInfo Permit Module. The following table presents a crosswalk
between the Management Method Codes in the BR and the Process Codes in the RCRAInfo
Permit Module:
Biennial Report Management Method Code
RCRAInfo Process Code
DivliiiMil 1 nil-.
HI32 Landfill or surface impoundment
that will be closed as landfill
D80 Landfill
D83 Surface impoundment disposal
H131 Land treatment or application
D81 Land application
1 hernial Irralmriil 1 nil"
H040 Incineration
T03 Incinerator
H050 Energy recovery at this site - use
as fuel (includes onsite fuel
blending)
T80 Boiler
T81 Cement kiln
T82 Lime kiln
T83 Aggregate kiln
T84 Phosphate kiln
T85 Coke oven
T86 Blast furnace
T88 Titanium dioxide chloride process oxidation reactor
T89 Methane reforming furnace
T91 Combustion device used in the recovery of sulfur values from spent sulfuric acid
T92 Halogen acid furnace
T93 Other industrial furnaces
XO1 Subpart X open burning/open detonation
X03 Subpart X thermal unit
In addition to verifying that a facility had the hazardous waste management unit, EPA verified
that the unit was operating and actively managing hazardous waste. In doing so, we reviewied
information on the unit's Legal/Operating Status Code9 in the RCRAInfo Permit Module. A unit
was considered to be operating and actively managing RCRA hazardous waste if it has one of the
following Legal/Operating Status Codes:
l« UMiiImI rual anil Oprralinu ^laln- < mle- ( niioiilrivil Wliu-
ISOP
Interim status/operating, actively managing RCRA-regulated waste
PIOP
Permitted/operating, actively managing RCRA-regulated waste
PMOP
Pre-mod authorization/operating, actively managing RCRA-regulated waste
For each hazardous waste management unit that was operating and actively managing hazardous
waste, we also reviewed information on its commercial status. For purposes of this analysis, the
commercial status of a unit is determined as follows:
8 RCRAInfo code used to describe the unit's waste treatment, storage, or disposal process.
9 RCRAInfo code used to indicate programmatic (operating and legal status) conditions that reflect RCRA program
activity requirements of a unit.
13
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( lllllllllTli;ll Millil-
< iilrniil \
l« U\IiiIm< ommcmiil SIjiUi- < ode
Commercial
1 Accepts uasle li'om oll'sile generators
3 Accepts waste from limited oll'sile generators by special arrangement agreement
Non-Commercial
0 Does not accept waste from offsite generators
2 Accepts waste only from related, "captive" offsite generators, i.e., offsite
generators under the same organization or parent company
Once a draft list of commercial and non-commercial facilities was developed, EPA sought input
from EPA Regions and states on the draft list. Based on their input, the list of commercial
facilities was finalized.
1.5.2 Underground Injection and Fuel Blending Facilities
RCRAInfo does not contain complete information on underground injection and fuel blending
units. As a result, a methodology based on reported BR data was used to identify commercial
underground injection and fuel blending facilities. A description of the approach used to identify
these facilities is provided below.
In identifying commercial underground injection and fuel blending facilities, EPA first identified
facilities that reported one of the following Management Method Codes in their BR:
liicllllhil Uc|>miI \l:iii;i!irmrnl Mil hi id ( nilc
DiMiiplinii
H134
Deepwell or underground injection
H061
Fuel blending prior to energy recovery at another site (waste generated
either on site or received from off site)
In addition to identifying facilities that reported management of hazardous wastes using the
above management method codes, EPA obtained the facility name of: (1) the facilities that
managed the wastes and (2) the facilities that shipped or generated the wastes. We then used the
facility name information to identify facilities that offer management services to other entities
(i.e., "commercial" facilities) versus facilities that exclusively manage waste generated at the
same facility or received from another facility under the same organization or parent company
(i.e., "non-commercial" facilities).
14
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2 Analysis of Demographics of Potentially Affected Communities
EPA analyzed the demographics of the potentially affected communities identified through the
activities described in Section 1 of this report. The demographics analyzed include racial
minorities (all races except non-Hispanic white), children under five years of age, American
Indian and Alaskan Natives, and people with income below 200% of the poverty level. EPA
determined the demographics for the population within a 3 km radius around each facility and
compared these demographics to national and state-specific population demographics .
2.1 Demographic Data Sources
U.S. EPA collected demographic data from the U.S. Census Bureau's 2010 Decennial Database
and the 2006-2010 American Community Survey (ACS) 5-year estimates database.. The 2010
decennial database provides information at the most precise level available to the public, the
block level. Each block is approximately the size of a city block. The ACS database, which
replaced the Summary File 3 (SF3) database in 2006, provides data at the next most precise
level, the block group level. Each block group is comprised of several blocks. Decennial data is
based on data collected from all persons and households within the block. This data is a sample
data of generally 1 in 6 households within a block group that includes information about more
characteristics of the people and households surveyed. EPA conducted its analysis using the
most precise data set available for the characteristics analyzed. Decennial data was used for the
following demographics:
Population;
Population density;
Minority population;
American Indian and Alaska Native (AIAN) population; and
Children under five years of age
Decennial data does not include data on the number of Americans below 200% poverty.
According to the U.S. Census persons below 200% poverty "includes all those described in
poverty under the official definition, plus some people who have income above poverty but less
than 2 times their poverty threshold." Therefore ACS data was used for analysis of this
demographic characteristic. Because ACS data for county populations and population density
can be different than decennial data for the same location, EPA also used ACS population and
population density information for analyses related to the poverty level.
All demographic variables were further divided into urban and rural populations. The U.S.
Census Bureau defines urban in several ways. EPA used their most general and easily applicable
definition, which is, "all territory, population and housing units in urbanized areas and in places
of more than 2,500 persons outside of urbanized areas." This encompasses all regions with a
population density greater than 1,000 people per square mile with a minimum residential
population of 50,000 people. All areas that meet these criteria are considered urban for this
analysis, and all other areas are considered rural (See Attachment E).
When determining what defined minority population, EPA first identified the population with the
Census racial category "White alone, not Hispanic or Latino." The minority population was then
calculated by subtracting this number from the total population. The American Indian and
Alaska Native (AIAN) population is based on Census data for those with this category alone or
in combination with any other category.
15
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16
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Table 2-1 Data Source Files from the 2010 U.S. Census Used for the DSW EJ Analysis
2010 Decennial Data
American Community Survey 2006-2010
Data
Total
Populatio
n
Populatio
n Density
Minority
Populatio
n
American
Indian
and
Alaska
Native
Populatio
n
Childre
n Under
Five
Total
Population
Population
Density
Population
Below 200%
Poverty
Level
National Total
X
X
X
X
X
X
X
X
National
Urban
X
X
X
X
X
X
X
X
National Rural
X
X
X
X
X
X
X
X
State Total
X
X
X
X
X
X
X
X
State Urban
X
X
X
X
X
X
X
X
State Rural
X
X
X
X
X
X
X
X
17
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2.2 Methodology
This section describes the methodology used to develop the EJ Analysis for the current DSW
exclusions, including selection of the EJ characteristics for analysis, using the areal
apportionment method to determine the characteristics of the communities surrounding each
facility, and conducting a statistical analysis of these results to determine how the demographic
characteristics compare to those on a state and national level.
2.2.1 Selection of EJ Characteristics for Analysis
EPA selected the following population demographics for the analysis: racial minority (all races
other than non-Hispanic white), American Indian and Alaska Native, children under five, and
persons below 200% of the poverty level. These demographics were selected based on the Sierra
Club petition, comments received in response to this petition and during public forums
discussing the 2008 DSW final rule and EJ analysis, comments from the external peer review,
comments on the 2011 proposed rule, and a review of past EJ analyses conducted by EPA and
other entities, including:
* EPA's "Environmental Justice Smart Enforcement Assessment Tool" (EJ SEAT);
* EPA's "Toolkit for Assessing Potential Allegations of Environmental Justice" (EJ Toolkit);
and=
* Chapter 3 of "Toxic Wastes and Race at Twenty - 1987-2007: Grassroots Struggles to
Dismantle Environmental Racism in the United States," prepared by the United Church of
Christ, document the work by Dr. Paul Mohai and Dr. Robin Saha.
2.2.2 Areal Apportionment Method
In order to perform the analysis of the demographic makeup of potentially affected communities,
EPA used the ESRI geospatial software ArcMap version 10.0. Geographic coordinate points
(latitude, longitude) were imported into the program using the North American Datum 1983
Geographic Coordinate System and projected onto a U.S. map using a North America
Equidistant Conic projection, which is a standard projection used for national maps of the
conterminous United States.. The underlying data used in the ArcMap program was the 2010
U.S. Census data, as described in Section 2.1. Once the buffers were created around each facility,
data was extracted at the block group level for 2010 decennial data for the total population,
minority population, American Indian/Alaska Native (AIAN) population, and children under
five, and at the block group level for American Community Survey (ACS) 2006-2010 data for
population below 200% poverty. To extract all the relevant demographic data, decennial and
ACS census data were converted to feature layers on top of a national map. In addition to the
U.S. Census data, the U.S. National Atlas Water Feature Areas layer was used to represent the
water feature areas such as bays, glaciers, lakes, and swamps, of the United States. All inland
water except those identified as dry lakes and swamp or marsh were used in the analysis. Once
the map was created, a model was created from the ModelBuilder application in ArcToolbox to
create the algorithm for the analysis.
For the Environmental Justice analysis, EPA used a three-kilometer buffer for each facility
(notification, damage case, hazardous waste, and non-hazardous waste) as an approximation of
the potential area that could be affected by an acute release scenario (such as a fire or explosion)
at a reclamation facility. While some EJ analysis use other buffer distances, such as 1- or 2-km
buffers, assessment of multiple buffers is beyond the scope of this analysis. EPA did perform an
additional analysis on a 1-km buffer for the notification facilities to perform a sensitivity
analysis. The results of the analysis can be found in Section 6. For each facility, EPA used
ArcMap to draw a 3-km radius around the facility, and determined the demographic
18
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characteristics of the communities within that circle. Each 3-km radius encompassed discrete or
partial census block groups, and some census block groups were only partially within the circle.
EPA estimated the demographics of the population within each circle using the Areal
Apportionment Method (AAM) also known as the area-weighted method. For areas with inland
water bodies (e.g., lakes, ponds) found within the 3-km radius, water bodies were removed from
the analysis in order to accurately calculate population and population density for the potentially
affected community. In the instances where multiple facilities could affect the same persons
within a population, as is the case for generator and transfer-based exclusion facilities,
overlapping radii were extracted and the affected sub-population was counted once to increase
accuracy of the potentially affected community numbers used in the analysis.
The population numbers for each demographic category were not a simple sum of the population
contained in every block group intersected by the buffer. It was a weighted sum in which the
population in the block group was multiplied by the proportion of area contained with the buffer
region. For example, if 100% of the block group was contained within the buffer region than
100% of the population was tallied; however, if 50% of the block group was contained within the
buffer then only 50% of that population was tallied. If the buffer contained three block groups,
one completely contained and the others partially contained the calculation would be the
following:
Block group 1: Total population of 50, 100% contained in buffer
Block group 2: Total population 50, 50% contained in buffer
Block group 3: Total population 30, 30% contained in buffer
Total population for the buffer = (1 * 50) + (0.5 * 50) + (0.3 * 30) = 84
The degree of hazards presented by HSM generation and management activities are typically
related to the distance of receptors from the HSM. EPA used the areal apportionment method
because it provides an estimate of the socioeconomic characteristics close to specific locations,
such as facilities addresses. The Census data used for this analysis is based on administratively
determined boundaries including census block groups. The Census block groups can vary
significantly in size and shape. When used for EJ analyses, they may provide inaccurate results,
particularly when they are large or irregularly shaped, resulting in inclusion of populations that
are not within the 3-km radius EPA used for this analysis.
While AAM will not provide the exact characteristics of the populations within the 3-km radius,
it provides an adjustment for the limitations of available census data and the geographic
boundaries provided by the census. EPA considered other methods, such as including the entire
population of all census block groups where any part of it was contained within the 3-km radius,
and including only those where the entire area of the block group was contained within the 3-km
radius. However, these methods do not adjust for census block groups that cross the 3-km
boundary and have areas (and associated populations) both inside and outside the 3-km radius,
some of which could be potentially large. In addition, the AAM approach used by EPA for this
analysis is consistent with other EJ tools and analyses, including those discussed in Section 2.2.1.
AAM assumes that all populations are equally distributed within a block group. An accurate
analysis of the impact of this assumption could not be conducted with the information available
from the sources used for this analysis.
19
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2.2.3 Comparison of Demographic Characteristics of Affected Population versus
Comparison Population
The demographics of the population within a 3 km radius of each facility were compared to its
defined population cohort at a national and state level. The potentially affected community
population is defined as the minority, persons below 200% poverty, American Indian and Alaska
Native, and children under age five cohorts residing within 3km radius of a facility. The
national-level comparison is intended to capture any regional disproportionality (for example, if
the potentially affected communities are all located in states with minority and/or low-income
populations that are higher than the national average). The state-level comparison is intended to
capture any disproportionality occurring within the state. (In most cases, the RCRA program is
implemented by the state.)
In addition, comparisons were done for urban and rural populations to check if the tendency to
locate industrial facilities in urban populations was a factor. . Most facilities analyzed were not
in areas with large AIAN populations. EPA neither analyzed facilities on tribal lands as a
separate category nor explicitly factor in the capacity of local government to oversee HSM
facilities.
2.2.4 Statistical Analysis
The next section describes the statistical analysis approach used for defining the affected and
comparison populations for the demographic groups (i.e. minorities, American Indian/Alaska
Native, persons below 200% poverty or children under five) within a 3 km radius around each
facility, and for comparing the demographic characteristics of the affected and comparison
populations.
The affected populations are those within the 3 km radius around the facilities analyzed. The
comparison population is the population selected for comparison with the affected population to
evaluate whether there is a significant difference between them with respect to demographic
characteristics. This implies that it is a group of people that could have been equally likely to be
affected if the facility was in alternative location. The comparison populations used in this
analysis were the national population and the state population in which each facility was located.
The data for hazardous waste facilities was adjusted for the statistical analyses to avoid double
counting persons who were affected by two or more facilities due to the large number of
facilities analyzed and the resulting overlap of some facility populations. As a result, the total
state affected population was a count of all persons in the state who were affected by at least one
facility, instead of a sum of the individual facility populations in the state. The total national
affected population was a sum of the state affected populations.
2.3 Statistical Comparison of Demographic Characteristics of Affected Population
versus Comparison Population
As described above, the goal of this disparity analysis was to assess two comparisons:
a) Whether there was a substantially greater probability of members in a population group
(e.g., minority populations) being affected than members of a comparison population
group (i.e., non-Hispanic White), and
b) Whether members of the population group of interest (e.g., minority population)
comprised a substantially greater proportion of the affected population than of the non-
affected population in the selected buffer regions.
20
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This document refers to comparison (a) as the "Affected Population Ratio" and comparison (b)
as the "Demographic Ratio." The methodology for calculating these ratios is described in
Attachment B. .
EPA tested these comparisons for statistical significance to identify the probability that the
observed differences could have arisen due to chance. A statistical significance test result can be
expressed either as a probability (p-value) that an outcome could have been the result of chance,
or as the number of standard deviations from the mean value. For individual states and the nation
as a whole, EPA conducted two statistical tests for significance, the Kendall test and Fisher's
Exact test. The Kendall test is the standard test for large samples.10 Fisher's Exact test is
conditional on the total numbers of affected, non-affected, demographic group G, and non-
demographic group G populations (Kendall and Stuart, 1973 sections 33.19 and 33.20).11
Attachment B. includes the methodology used to calculate the results of these tests.
For variables with a normal distribution, approximately 95% of the values are within two
standard deviations of the mean, so this indicates that there would be only a 5% or less
probability of a value outside this range.12 EPA also calculated the corresponding number of
standard deviations (SD) based on each test. Attachment B includes the methodology used to
calculate the number of standard deviations. The SD indirectly provides a statistical test since
the SDs have a standard normal distribution under the hypothesis of homogeneity (i.e., no ethnic
group disparity), for large samples (i.e., when n is large).
Fisher's Exact test tests whether there is a difference between Group G and other people in their
probability of being inside the boundary area. The smaller the p-value (i.e., the closer to zero),
the stronger the difference, also shown is the equivalent number of standard deviations based on
a standard normal distribution13. In some cases the Fisher's Exact test p-values are too small to
compute readily (e.g., below 10"300), which in turn prevents the computation of "equivalent" SD
values. Kendall test results are provided when Fisher's Exact test cannot be calculated. The
Kendall test results provide a close approximation of the Fisher's Exact test results. These
statistics provide information about the statistical significance of any observed disparity.
To summarize and evaluate the disparities for different states, two additional statistical
procedures were used. As detailed in Attachment B. , the Mantel-Haenszel method was used to
estimate a common Affected Population Ratio (APR) and a common Demographic Ratio (DR),
under the assumption that all states have the same underlying ratios. These ratios are weighted
averages of the state-specific ratios. They differ from the nationwide Affected Population Ratio
and Demographic Ratio because they only include states that have at least one facility and
because the statistical calculation is different. As detailed in Attachment B. , the Cochran-
Mantel-Haenszel test, a generalization of the standard chi-square test, was used to test the null
hypothesis of no disparity in every state against the alternative hypothesis of a disparity in one or
more states. The p-value for this test is provided.
10 Apart from the very small bias adjustment factor of n/(n-l), the Kendall test is mathematically equivalent to a
standard chi-square test.
11 The Kendall and the chi-square tests are approximations to the Fisher Exact test.
12 Consistent with several court-approved precedents in Title VII discrimination cases, a 2-sided significance test is
used, i.e., EPA test the hypothesis that the population ratio prl/pr2 = 1 against the alternative hypothesis that prl/pr2
4- 1. This alternative hypothesis means that either demographic group G populations are more adversely affected
(prl/pr2 > 1) or non-affected demographic group G populations are more adversely affected (prl/pr2 < 1). If,
instead, the goal of the analysis were to test only whether demographic group G populations were more adversely
affected, then the alternative hypothesis would be prl/pr2 > 1 and the probabilities of chance occurrence (p-values)
would be halved (assuming that the estimated ratio prl/pr2 exceeds 1).
13 The "equivalent" number of standard deviations for Fisher's Exact test do not exactly equal SD but they are
approximately equal.
21
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EPA selected these standard statistical analyses and tests based on technical literature and their
historical use in EJ analyses and discrimination cases14' '15\ EPA Office of Civil Rights used the
same Affected Population Ratio (referred to as "Relative Ratio"), Kendall test, and Fisher Exact
Test, and a similar Demographic Ratio (referred to as "Population Ratio") in a past Title VI
analysis and investigation guidance document16'17'. EPA Office of Civil Rights also used the
same statistical analyses for a recent Title VI disparity analysis18. In addition, there are numerous
applications of these same statistical methods19 in Title VII court cases20'21.
2.4 Results of Demographic Analysis
This section contains the results of the demographic analyses for the four groups of facilities in
the DSW EJ analysis:
1. Results for notification facilities (presented in Section 2.4.1).
2. Results for damage case facilities (presented in Section 2.4.2).
3. Results for hazardous waste facilities (presented in Section 2.4.3).
4. Results for non-hazardous industrial waste facilities (presented in Section 2.4.4).
Results of the analyses for each set of facilities are presented in bar charts, demographic
comparison tables, and statistical analysis tables.
The bar charts are histograms of the percent in each demographic category of the population
within a 3 km radius around each group of facilities. For example, Figure 2.1 shows the percent
of notification facilities with different levels of demographic groups (minority, persons below
200% poverty, American Indian and Alaskan Native, and children under the age of 5) in the
surrounding population; About 30% of notification facility populations were 0 to 10% minority,
24% were 11 to 20% minority, 15% were 21 to 30% minority, 8% were 31 to 40% minority,
13% were 41 to 50 % minority, and 10% were 51 to 100% minority.
The demographic comparison tables present the analyses discussed in Section 2.2.3. For
example, Table 2-2 Table 3.2 compares the percent of the population of each demographic group
within a 3-km radius around the notification facilities to the percent of each demographic group
in the national population. This table shows that of the 60 notification facilities22, 16 had a
14 Biddle, Richard E. "Disparate Impact Reference Trilogy for Statistics", 46 Labor Law J 651. November 1995.
15 US Department of Justice, Civil Rights Division. 2001. Title VI Legal Manual. January 11, 2001.
http://www.justice.gov/crt/cor/coord/vimanual.php
16 EPA Office of Civil Rights, "Draft Revised Investigation Guidance", Federal Register, Vol 65. No. 124, June 27,
2000, pp. 39667ff http://www.epa.gov/civilrights/docs/frn_t6_pub06272000.pdf
17 EPA Office of Civil Rights 1998. Title VI Administrative Complaint re: Louisiana Department of Environmental
Quality; Permit for Proposed Shintech Facility; Draft Revised Demographic Information. April, 1998.
http ://www. epa. gov/civilrights/shinfileapr98. htm
18 EPA Office of Civil Rights 2011. Exposure Assessment and Disparity Analysis for Administrative Complaint
16R-99-R9. April, 2011. http://www.epa.gov/ocr/TitleVIcases/exposure-disparity-analysis-20110421.pdf
19 For employment discrimination the probability ratio (referred to as the "Impact Ratio" or "Selection Ratio" is
usually defined as P (selection | minority) / P(selection | non-minority), and corresponds to the Affected Population
Ratio used here. In this case, a low ratio is evidence towards disparate impact. Statistical significance tests include
the "Z-test," or "Number of standard deviations," which is mathematically the same as the Kendall test, and, more
recently, the Fisher Exact Test.
20 Peresie, Jennifer L. "Towards a Coherent Test for Disparate Impact Discrimination". 84 Indiana Law J 773. July
2009.
21 United State District Court, District of Connecticut. Civil Action No. 3:08-CV-0826 (JCH). Ruling Re: Plaintiffs
Motion for Summary Judgment (Doc. No. 106) and Defendant's Motion for Summary Judgment (Doc. No. 113).
May 2011.
22 Excluding the notification facility located in the Virgin Islands.
22
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greater percent minority population than the national population, 44 had a lower percent
minority population than the national population, and none had the same percent minority
population. The mean difference between the percent minority population in the national
population and the percent minority population in notification facility populations was -11.84%
(meaning that, on average, the percent minority population around notification facilities was
11.84% less than the national average) and the median difference was -18.97.
Statistical analysis tables present the results from the analyses discussed in Section 2.2.4 and are
located below the demographic comparison tables. For example, Table 2-3 Table 3.3shows the
statistical analysis results of the national demographic comparison for notification facilities and
Table 3.5 shows results at the state level. Values that could not be computed are represented as
"N/A"; for a description of why some values could not be computed, please see Section 2.2.4
and Attachment B.
Attachment E contains further demographic analysis results for each group of facilities. Each
group of facilities has demographic comparison tables that compare the percent of the population
of each demographic group within a 3-km radius around each facility to the national and state
level.
Data for facilities located in Puerto Rico were included in the bar charts and demographic
comparison tables but were excluded from the statistical analyses. There were 22 total facilities
located in Puerto Rico (1 notification facility, 3 damage case facilities, 18 hazardous waste
facilities, and no non-hazardous industrial waste facilities).
2.4.1 Notification Facilities
This section presents the demographic results for the 60 of the 61 notification facilities as of
February 27, 2012. This includes facilities in Iowa, Idaho, Illinois, New Jersey, Pennsylvania,
and Puerto Rico. The demographics for the one notification facility in the Virgin Islands were
not reviewed for this report.
EPA acknowledges that a selection bias may exist for the notification facilities. The statistical
analyses focus on whether the population demographics near each group of facilities are different
from the population demographics elsewhere in the same state or in the US as a whole. The
factors that influence whether a facility chooses to be a "notification" facility, or whether a
facility becomes a damage case, might include the population demographics near the facility, but
might also include other factors such as the state or region, the type or size of the facility, or
other factors. EPA did not investigate these additional factors that might influence whether
facilities become notification facilities. EPA analyzed the notification facilities separately from
other facility categories, in part, to isolate factors that might result in a selection bias.
23
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Figure 2.1 Demographics for Notification Facilities
100%
90%
80%
70%
a>
¦g 60%
u
ro
ai
Q.
50%
40%
30%
20%
10%
0%
II
¦
11
11
H
B
R
E
t
0-10%
11-20% 21-30% 31-40% 41-50% 50-100%
Percent of Population in Demographic
Minority (all except
non-Hispanic whites)
l Persons 200% below
poverty
American Indians and
Alaska Natives
I Children under age 5
24
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Table 2-2 National Demographic Comparison for Notification Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
16
44
0
-11.84%
-18.97%
Below 200%
Poverty Level
31
29
0
1.17%
0.73%
American Indians
or Alaska
Natives
13
47
0
-0.52%
-0.95%
Children under
age 5
24
36
0
-0.14%
-0.22%
25
-------
Table 2-3 National Demographic Comparison Analysis of Statistical Significance for Notification Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact Test
P-value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall
Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic
whites)
0.832528802
0.885798957
N/A
N/A
0.003154776
84.476352
~o
Persons below 200% poverty
0.997628352
0.998372693
2.76E-01
1.088600737
0.003154776
1.0892051
2.76E-01
American Indians and Alaska
Natives
0.538212053
0.540998022
N/A
N/A
0.003154776
54.399087
~0
Children under age 5
0.99203719
0.992536947
5.08E-02
1.952793488
0.003154776
1.9542705
5.07E-02
26
-------
Table 2-4. State Demographic Comparison for Notification Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
29
31
0
0.23%
-0.94%
Below 200%
Poverty Level
41
19
0
5.25%
4.89%
American
Indians or
Alaska Natives
25
35
0
0.27%
-0.13%
Children under
age 5
32
28
0
0.24%
0.21%
Table 2-5. State Demographic Comparison Analysis of Statistical Significance for Notification Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Cochran-Mantel-
Haenszel P-value
Minority (all except non-Hispanic whites)
1.38648607
1.25762176
~0
Persons below 200% poverty
1.305166262
1.212958074
~0
American Indians and Alaska Natives
1.252372909
1.262561834
2.16E-87
Children under age 5
1.062016336
1.060169958
1.54933E-50
27
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2.4.2 Damage Case Facilities
This section presents the demographic results for the 250 damage case facilities.
Figure 2.2 Demographics for Damage Case Facilities
100%
90%
80%
70%
60%
50%
40%
30%
20%
L
1
1
1
1
1
I 1
I
.
l
1
¦ L , J
~
t
II IT!
~
1 1
t
0-10%
11-20% 21-30% 31-40% 41-50% 50-100%
Percent of Population in Demographic
Minority (all except
non-Hispanic whites)
I Persons 200% below
poverty
American Indians and
Alaska Natives
I Children under age 5
28
-------
Table 2-6 National Demographic Comparison for Damage Case Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
131
119
0
6.97%
2.38%
Below 200%
Poverty Level
170
80
0
8.65%
8.77%
American Indians
or Alaska
Natives
65
185
0
-0.14%
-0.57%
Children under
age 5
135
115
0
0.18%
0.10%
29
-------
Table 2-7 National Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities
Demographic Group
Affected
Population Ratio
Demographic
Ratio
Fisher
Exact
Test P-
value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall Test
Statistic
Kendall Test
P-Value
Minority (all except non-Hispanic whites)
2.454957933
1.636984709
~0
N/A
0.026930687
1336.7438
~0
Persons below 200% poverty
1.601149695
1.358164374
~0
N/A
0.026930687
685.40726
~0
American Indians and Alaska Natives
0.856035499
0.854435181
N/A
N/A
0.026930687
-49.92378
~0
Children under age 5
0.994547714
0.994766533
7.53E-05
3.959039252
0.026930687
-3.9564542
7.61 E-05
30
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Table 2-8. State Demographic Comparison for Damage Case Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
131
119
0
7.20%
0.86%
Below 200%
Poverty Level
178
72
0
8.98%
8.33%
American Indians
or Alaska
Natives
111
139
0
0.00%
-0.09%
Children under
age 5
143
107
0
0.26%
0.28%
Table 2-9. State Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Cochran-Mantel-
Haenszel P-value
Minority (all except non-Hispanic whites)
2.278778605
1.490322666
~0
Persons below 200% poverty
1.75523922
1.464551275
~0
American Indians and Alaska Natives
1.004158185
1.004347597
1.76E-01
Children under age 5
1.002331559
1.002305546
0.087053808
31
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2.4.3 Hazardous Waste Facilities
This section presents the demographic results for 2,115 facilities that reported generating or
managing hazardous wastes in 2007 that may choose to operate under the current DSW
exclusions ("hazardous waste facilities"). .
Figure 2.3 Demographics for Hazardous Waste Facilities
100%
90%
80%
70%
.a 60%
s 50%
a>
ai 40%
a.
30%
20%
10%
0%
i' i n
J
Minority (all except non-
Hispanic whites)
I Persons 200% below
poverty
American Indians and
Alaska Natives
I Children under age 5
0-10% 11-20% 21-30% 31-40% 41-50% 51-100%
Percent of Population in Demographic
32
-------
Table 2-10 National Demographic Comparison for Hazardous Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
989
1126
0
1.37%
-2.98%
Below 200%
Poverty Level
1262
853
0
4.27%
4.19%
American Indians
or Alaska
Natives
458
1657
0
-0.24%
-0.68%
Children under
age 5
1129
986
0
0.24%
0.15%
33
-------
Table 2-11 National Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities
Fish
er
Exac
Equival
ent No.
t
of
Kend
Test
Standar
Probabili
all
Affected
P-
d
ty
Kendall
Test
Demographic Group
Populatio
n Ratio
Demograp
hie Ratio
valu
e
Deviatio
ns (SD)
(Affected
)
Test
Statistic
P-
Value
Minority (all except non-
Hispanic whites)
1.680615
321
1.4172884
25
~0
N/A
0.121226
233
1709.4322
97
~0
1.261363
1.1921192
~0
N/A
0.121226
731.38959
~0
Persons below 200% poverty
882
76
233
33
American Indians and Alaska
Natives
0.729979
194
0.7067524
36
N/A
N/A
0.121226
233
209.43092
48
~0
1.051925
1.0553574
~0
N/A
0.121226
83.804669
~0
Children under age 5
362
77
233
57
34
-------
Table 2-12. State Demographic Comparison for Hazardous Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
1131
984
0
5.07%
1.30%
Below 200%
Poverty Level
1278
837
0
4.37%
4.10%
American Indians
or Alaska
Natives
818
1297
0
0.00%
-0.18%
Children under
age 5
1194
921
0
0.32%
0.30%
Table 2-13. State Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Cochran-Mantel-
Haenszel P-value
Minority (all except non-Hispanic whites)
1.407514066
1.217556699
~0
Persons below 200% poverty
1.091250847
1.06015238
8.7085E-214
American Indians and Alaska Natives
0.834668652
0.834863239
3.35E-29
Children under age 5
1.05262912
1.049306306
1.92595E-22
35
-------
2.4.4 Non-Hazardous Industrial Waste Facilities
This section presents the demographic results for 25 facilities not currently generating or
managing hazardous wastes that may choose to begin reclaiming HSM under the current DSW
exclusions (non-hazardous industrial waste facilities).
Figure 2.4 Demographics for Non-Hazardous Waste Facilities
a>
u
*_
a>
a.
100.00%
90.00%
80.00%
70.00%
60.00%
50.00%
40.00%
30.00%
I Persons 200% below
poverty
American Indians and
Alaska Natives
I Children under age 5
0-10% 11-20% 21-30% 31-40% 41-50% 50-100%
Percent of Population in Demographic
36
-------
Table 2-14 National Demographic Comparison for Non-Hazardous Industrial Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
9
16
0
-4.00%
-10.69%
Below 200%
Poverty Level
12
13
0
-0.08%
-1.03%
American Indians
or Alaska
Natives
2
23
0
-0.76%
-0.80%
Children under
age 5
11
14
0
-0.18%
-0.31%
37
-------
Table 2-15 National Demographic Comparison Analysis of Statistical Significance for Non-Hazardous Industrial Waste Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher Exact
Test P-value
Equivalent No. of
Standard
Deviations (SD)
Probability
(Affected)
Kendall Test
Statistic
Kendall Test
P-Value
Minority (all except non-Hispanic whites)
1.23230635
1.137215001
~0
N/A
0.001828514
77.2778184
~0
Persons below 200% poverty
1.1307444
1.085980217
~0
N/A
0.001828514
43.83506903
~0
American Indians and Alaska Natives
0.474107255
0.477235781
N/A
N/A
0.001828514
-47.17615327
~0
Children under age 5
1.037831425
1.035306009
2.41E-12
7.008352197
0.001828514
7.042585889
1.89E-12
Table 2-16. State Demographic Comparison for Non-Hazardous Industrial Waste Facilities
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Number of
Facilities with
Facilities with
Demographic
Group
%
Demographics
Less Than Area
%
Demographics
Equal to Area
Mean
Difference
Median
Difference
Comparison
Comparison
Minority (all
except non-
Hispanic whites)
11
14
0
-0.82%
-1.99%
Below 200%
Poverty Level
11
14
0
-0.73%
-1.75%
American
Indians or
8
17
0
-0.14%
-0.21%
Alaska Natives
Children under
age 5
13
12
0
-0.05%
0.06%
38
-------
Table 2-17. State Demographic Comparison Analysis of Statistical Significance for Non-Hazardous Industrial Waste Facilities
Demographic Group
Affected Population
Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-value
Minority (all except non-Hispanic whites)
1.407514066
1.217556699
~0
Persons below 200% poverty
1.091250847
1.06015238
8.7085E-214
American Indians and Alaska Natives
0.834668652
0.834863239
3.35E-29
Children under age 5
1.05262912
1.049306306
1.92595E-22
39
-------
3 Comparison of Hazardous Waste Facilities to Commercial Hazardous Waste
Treatment and Disposal Facilities That Do Not Recycle
In response to comments on the 2011 DSW proposed rule, EPA compared existing commercial
hazardous waste treatment and disposal facilities that do not recycle (commercial hazardous
waste facilities that do not recycle) to the hazardous waste facilities identified as potentially
operating as recyclers under the current DSW exclusions (hazardous waste facilities). The
treatment and disposal facilities that do not recycle represent the "baseline" waste management
practices absent the DSW rule.
One expected outcome of the rule is that hazardous wastes will be managed in different
locations, including changing waste management from the commercial hazardous waste facilities
that do not recycle to management onsite at hazardous waste facilities. Therefore, EPA compared
the population demographics of commercial hazardous waste facilities that do not recycle to
hazardous waste facilities, to illustrate the potential change in population demographics affected
by the handling of hazardous waste under the current DSW exclusions.
Table 3-1 is similar to the demographic comparison tables presented in Attachment E; it
compares the percent of the population of each demographic group within a 3 km radius around
facilities to the percent of each demographic group in the state in which each facility is located. It
shows the demographic comparison for both the commercial hazardous waste facilities that do
not recycle and the hazardous waste facilities, and calculates the difference from the former to
the latter. For example, 58.56% of commercial hazardous waste facilities that do not recycle
have a greater percent minority population than the corresponding state minority populations,
while 53.48% of hazardous waste facilities have a greater percent minority population than the
corresponding state minority populations. The resulting difference shows that there are 5.08%>
fewer hazardous waste facilities compared to commercial hazardous waste facilities that do not
recycle with a greater percent minority than the corresponding state minority populations.
Figure 3.1 shows the comparison from Table 3-1 in a bar chart for just those facilities with
greater percent population demographics than the corresponding state population demographics.
The results of the demographic analysis of commercial hazardous waste facilities that do not
recycle can be found in Attachment E.
40
-------
Table 3-1 Comparison of Population Demographics at a State Level Between Commercial Disposal and Treatment Facilities and Hazardous Waste Facilities
Demographic
Group
% of Facilities with % Demographics
Greater than State
% of Facilities with % Demographics Less
than State
Mean Difference Between Facility and
State % Demographics
Median Difference Between Facility and
State % Demographics
Commercial
Hazardous
Waste
Facilities
that do not
Recycle
Hazardous
Waste
Facilities
Difference
Commercial
Hazardous
Waste
Facilities
that do not
Recycle
Hazardous
Waste
Facilities
Difference
Commercial
Hazardous
Waste
Facilities
that do not
Recycle
Hazardous
Waste
Facilities
Difference
Commercial
Hazardous
Waste
Facilities
that do not
Recycle
Hazardous
Waste
Facilities
Difference
Minority
(all except
non-Hispanic
whites)
58.56%
53.48%
-5.08%
41.44%
46.52%
5.08%
10.57%
5.07%
-5.50%
5.94%
1.30%
-4.63%
Below 200%
Poverty Level
67.38%
60.43%
-6.95%
32.62%
39.57%
6.95%
7.17%
4.37%
-2.80%
7.11%
4.10%
-3.01%
American
Indians or
Alaska Natives
36.90%
38.68%
1.78%
63.10%
61.32%
-1.78%
-0.01%
0.00%
0.01%
-0.24%
-0.18%
0.07%
Children
under age 5
56.42%
56.45%
0.04%
43.58%
43.55%
-0.04%
0.22%
0.32%
0.09%
0.29%
0.30%
0.01%
Figure 3.1 Comparison Between Commercial Disposal and Treatment Facilities and Hazardous Waste Facilities with Population Demographics Greater than State Population
Demographics
41
-------
80.00%
70.00%
60.00%
.2! 50.00%
u
40.00%
u
ai 30.00%
O-
20.00%
10.00%
0.00%
% Minority % Below 200 %AIAN
Poverty
PopulationDemographic
Commercial
Disposal and
Treatment
Facilities
l Generator and
Transfer-Based
Exclusion Facilities
% Children Under
5
4 Sensitivity Analysis
EPA conducted a sensitivity analysis on the notification facilities for the four demographic
cohorts. This analysis is used to demonstrate if the composition of the potentially affected
community changes significantly in regards to distance from a facility and if those changes could
present an additional burden on specific cohort within the population.
EPA evaluated population demographics within 1-km and 3-km radius from a notification
facility using the areal apportionment method referenced in Section 2.2.2 Figure 6.1. displays the
following populations percentages for minority, persons below 200% poverty, American Indian
and Alaska Native, and children under five within 1-km, 3-km, or at the national level. As
shown in Figure 6.1 below, minority populations are higher within a 1-km radius of the facility
than between one and 3-km; however, it is still under the national percentage. Populations
within 1-km of a facility had the highest percentage of persons below 200% poverty, but the
lowest percentage of American Indian and Alaska Native or children under five. National
percentages were generally higher than percentage populations within 3-km and 1-km for all
categories except persons below 200% poverty.
42
-------
The United Church of Christ report23 conducted a similar analysis focusing on the percent people
of color living near hazardous waste facilities. The authors evaluated all people of color, African
Americans, Hispanic or Latino, Asian/Pacific Islander, and Native American populations within
1-km, between 1- and 3-km, between 3- and 5-km, and beyond 5 km of a hazardous waste
facility. Despite the difference is scope, the EPA analysis did provide some similar results. The
percentages of American Indian and Alaska Native in both reports were similar. The evaluation
of minority, or people of color, was different for both reports. Although the percentage was
higher at within 1-km compared to between 1 and 3-km, the analyses differed beyond 3-km.
This could be attributed to the difference in scope (i.e. beyond 3-km versus national percentages)
and the difference in sample size, as the sensitivity analysis in this report was limited to
notification facilities.
Additional analyses, such as historical changes demographic changes, are beyond the scope of
this analysis.
Table 4-1 Sensitivity Analysis for Notification Facilities Comparing Demographics within 1 km and 1 to 3 km
Compared to National Demographics
Demographic Group
Percentage of Population in Each Demographic Group
Within 1 km Radius
Around Facility
Between 1 and 3 km
Around Facility
National
Minority (all except non-
Hispanic whites)
25.31%
24.09%
36.11%
Below 200% Poverty
Level
33.11%
32.55%
31.65%
American Indians or
Alaska Natives
0.72%
0.90%
1.43%
Children under age 5
6.27%
6.48%
6.62%
23 Mohai, P. and R. Saha. 2007. Toxic Wastes and Race at Twenty - 1987-2007: Grassroots Struggles to Dismantle
Environmental Racism in the United States. United Church of Christ, pp. 175
43
-------
40%
Within 1 km Radiu
Around Notification
Facilities
I Between 1 and 3 kms
Around Notification
Facilities
National
Minority Below 200% AIAN
Poverty
Population Demographic
Children Under 5
Figure 2.1 Sensitivity Analysis for Notification Facilities Comparing Demographics within 1 km and 1 to 3 km
Compared to National Demographics
44
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5 Other Factors that Affect Vulnerability in Communities
Environmental justice means that all people, regardless of race, color, national origin, or income,
receive fair treatment and equal environmental protection, and have the opportunity for
meaningful involvement in decisions that will affect the environment and/or the health of their
community. The previous chapters of this report present a detailed analysis of a number of
indicators related to the facilities and surrounding communities that could be impacted under the
current DSW exclusions. However, because of the broad and encompassing definition of EJ,
there are many other ways to examine factors that could affect the vulnerabilities of
communities.
This chapter examines a number of additional factors that could affect the vulnerabilities of
communities under the current DSW exclusions. Section 5.1 identifies and briefly describes
some additional factors not analyzed in the previous chapters, while Section 5.2 summarizes data
that EPA has compiled on some of these factors to characterize the vulnerabilities of
communities surrounding the 61 notification facilities.
5.1 Overview of Factors that Affect Vulnerability
This section identifies additional factors that could affect a community's vulnerability under the
rule. These factors are described under four broad categories:
Susceptible Populations
Multiple and Cumulative Effects
Unique exposure pathways
Ability to Participate in the Decision-Making Process
Physical Infrastructure
While this report does not attempt to quantify all the potential factors that could affect a
community's vulnerability to environmental pollutants, the following discussion is intended to
give an overview of other considerations that may apply in some cases. The health of
community can be looked at in many ways. EPA selected specific factors for analysis based on
their relevance to the risks associated with HSM reclamation and the availability of information
about those factors from reliable information sources such as the EJView tool.
5.1.1 Susceptible Populations
Susceptible populations are groups that are at a relatively high risk of suffering the adverse
effects of environmental hazards. Certain factors may render different groups less able to resist
or tolerate an environmental stressor. These susceptibility factors may be intrinsic in nature
(e.g., based on age, sex, genetics, and race). For example, young children, pregnant women,
nursing mothers, and the elderly may be more likely to suffer health consequences from a toxic
chemical exposure than healthy adults. The proximity of children under five to facilities that
may begin operating under the current DSW exclusions is presented in Section 2, although there
are likely other types of susceptible populations in these communities as well.
5.1.2 Multiple and Cumulative Effects
Minority, low-income, and indigenous communities that have been impacted by multiple
environmental hazards may be at risk for increased adverse health consequences. Environmental
hazards can include, for example, industrial facilities, landfills, transportation-related air
pollution, poor housing, leaking underground tanks, pesticides, and incompatible land uses. An
45
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analysis of the cumulative effects from multiple stressors can provide a more complete
evaluation of a population's health risks from pollutants. For example, an analysis of discrete
stressors and effects on a population might conclude that nearby pollution sources are within
regulatory limits; however, the cumulative effects might result in a person's aggregate exposure
to a particular contaminant from multiple sources exceeding a health-based limit.
Some factors may provide data on the potential sources of cumulative stress, such as the total
number of facilities that may emit environmental pollutants. Other factors may provide data on
environmental conditions that could cause stress (e.g., transport routes, such as water or air
quality or meteorological conditions). Finally, other factors may provide data on potential or
actual human exposures to stressors, such as health data. Examples of factors include the
following:
Existing Pollution Sources
Number of facilities reporting to EPA - EPA's Envirofacts database keeps track of
regulated facility data from 14 data systems. Examples are listed below. The number of
regulated facilities within a community can indicate the number or proximity of pollution
sources.
o Resource Conservation and Recovery Act Information (RCRAInfo) - contains
information on facilities that generate, transport, treat, store or dispose of
hazardous waste. This factor is examined in Section 5.2.
o Air Facility System (AFS) - contains compliance and permit data for stationary
sources regulated by EPA, state and local air pollution agencies. This factor is
examined in Section 5.2.
o Comprehensive Environmental Response, Compensation & Liability Information
System (CERCLIS) - contains information on hazardous waste sites, potentially
hazardous waste sites and remedial activities across the nation, including sites that
are on the National Priorities List (NPL) or being considered for the NPL. This
factor is examined in Section 5.2.
Environmental Quality Factors
Non-Point Source Air Emissions - The CAA requires EPA to set National Ambient Air
Quality Standards (NAAQSs) for pollutants considered harmful to public health and the
environment. EPA has set NAAQSs for six principal pollutants, which are called
"criteria" pollutants (e.g., carbon monoxide, ozone, particulate matter). In addition, the
CAA requires EPA to identify and list all air pollutants (not already identified as criteria
pollutants) that "may reasonably be anticipated to result in an increase in mortality or an
increase in serious irreversible or incapacitating reversible illness." For each hazardous
air pollutant (HAP) identified, EPA was to then promulgate national emissions standards
for hazardous air pollutants (NESHAPs). The quantity of these pollutants in the local
atmosphere can help to indicate cumulative air hazards. This factor is examined in
Section 5.2 for a limited number of criteria pollutants and HAPs.
Health-Related Factors
Cancer - The threat of cancer can be measured based on the total cancer risk per million,
by tract or county, as determined by the 2002 National-Scale Air Toxics Assessment
(NATA). NATA is EPA's ongoing comprehensive evaluation of air toxics in the U.S.
EPA developed the NATA as a state-of-the-science screening tool for State/Local/Tribal
46
-------
Agencies to prioritize pollutants, emission sources and locations of interest for further
study in order to gain a better understanding of risks. NATA assessments do not
incorporate refined information about emission sources, but rather, use general
information about sources to develop estimates of risks which are more likely to
overestimate impacts than underestimate them. NATA provides estimates of the risk of
cancer and other serious health effects from breathing (inhaling) air toxics in order to
inform both national and more localized efforts to identify and prioritize air toxics,
emission source types, and locations which are of greatest potential concern in terms of
contributing to population risk.24 This factor is examined in Section 5.2.
Non-cancer - The threat of a non-cancer illness (neurological or respiratory) can be
measured based on the sum of hazard quotients that affect the same target organ, by tract
or county, as determined by the 2002 NATA. See above for a description of NATA.
This factor is examined in Section 5.2.
5.1.3 Unique Exposure Pathways
Other susceptibility factors may stem from unique pathways for exposure. For example, certain
lifestyle patterns may present unique exposure pathways, such as relative source contributions
for people that get a significant portion of their diet from food they grow or catch themselves.
For example, some indigenous peoples that use fishing and hunting to provide food for their
families may be more susceptible to contaminants found in the natural environment, such as
chemicals that bioaccumulate in flora or fish. Section 2 of this report includes information about
the American Indian and Alaska native populations in proximity to facilities that may generate or
manage HSM under the current DSW exclusions. While this does not automatically correspond
to individuals experiencing unique exposures pathways, it does indicate that such exposures
might occur.
5.1.4 Ability to Participate in Decision-Making Process
A key element of environmental justice is ensuring that all people have an opportunity for
meaningful involvement in decision-making. Certain groups may not have participated in
decision making historically because of economic (e.g., income), social (e.g., language barriers,
education levels, distrust of government), and structural reasons. A critical concern is whether,
and the extent to which, communities have the ability to influence the types and number of
regulated activities taking place in their community, as well as the requirements, conditions, and
parameters by which they must operate (e.g., permit conditions).
Under the current DSW exclusions, facilities claiming an exclusion must submit an initial and
biennial notification to EPA or the state, providing general facility information and describing
the HSM types and activities. Thus, under both the existing hazardous waste regulations and the
DSW rule, EJ communities have a similar ability to identify the facilities that are recycling HSM
in their communities, and the types and amounts of waste recycled.
However, the existing hazardous waste regulations require some hazardous waste recycling
facilities to get a RCRA permit. Permitted facilities are subject to public involvement during the
permitting process, and facilities and regulators are required to solicit and consider community
input into the permitting decision-making process. Under the current DSW exclusions, HSM
reclaimers may not be subject to permitting requirements, and EJ communities may not have the
same opportunities be informed about the siting and permitting of HSM reclaimers and
participate in the decision-making process. Thus, by removing the RCRA permitting
24 For additional information on NATA, go to: http://www.epa.gov/ttn/atw/natamain/.
47
-------
requirement, the current DSW exclusions also inadvertently removed one of the key provisions
allowing the community to participate in the regulatory process. Communities with lower
participation levels may experience greater adverse impacts because their input has not been
considered fully, particularly if competing interests are set forth more effectively. This effect is
most likely to occur in communities that have traditionally been excluded from the decision
making process. However, not all hazardous waste recycling facilities are required to get permits
under the hazardous waste regulations.
In addition to the permitting process, the DSW Rule requires that generators make reasonable
efforts to ensure that their hazardous secondary materials are safely and legitimately recycled.
When HSM reclaimers are located in EJ communities, and the generators of the wastes are small
businesses, the generators' ability to conduct reasonable efforts determinations may be impacted.
Not all generators will have the same ability to perform reasonable efforts audits, and the
efficacy of these efforts will depend on the ability of the generator. For example, small or
independent generators may have fewer financial resources or staff to use to conduct such audits,
and may be more likely to miss indications that reclaimers are not legitimately recycling HSM.
EPA did not analyze whether HSM reclaimers managing waste from small or independent
generators were more likely to be located in EJ communities.
There are a number of factors that can measure the ability of a community to gain access to
information or to meaningfully participate in the decision-making process. There also are factors
that can measure whether and how well the community appears to be able to participate in the
environmental decision-making process. Examples of possible factors include the following:
Education level - Persons with less education may be generally less likely to participate
in environmental decision-making. Because of less education, they may not be able to
fully understand the information in local newspapers, notices, and other written media.
They may also be less informed about events within their communities. This factor is
examined in Section 5.2.
English literacy - People who cannot speak or read English well may be less informed
about activities of interest in their community because they cannot fully understand the
information in local newspapers, broadcasts, notices, and other media, unless such
information has been translated into a language that they are comfortable with. A lack of
English literacy is an indicator that members of the community are immigrants or foreign
born25. Immigrant status, particularly new immigrants and undocumented workers and
residents may experience significant communication barriers to participating in decision
making. This factor is examined in Section 5.2.
Communication channels - Some regulations require that regulated entities issue public
announcements of their proposed actions and solicit public comments. Without such
communication channels, meaningful community involvement is less likely.
5.1.5 Physical Infrastructure
The physical infrastructure of a community can contribute to making some residents more
vulnerable to environmental hazards. Physical infrastructure can include, for example, public
buildings (proximity to hospitals), safe drinking water, sewage treatment, public transportation,
25 According to the U.S. Census 2007 American Community Survey, approximately 20% of the population spoke a
language other than English at home. About half of these speakers reported not speaking English "very well."
People speaking at a level below "very well" (ranging from well to not at all) are considered to need English
assistance in some situations. In addition, more than half of non-English language speakers were foreign born.
48
-------
and communication systems (e.g., telephones, Internet access). Access to such infrastructure
may affect a community's ability to avoid exposures to harmful pollutants or, if they are already
exposed, to detect the exposure, get proper treatment, or take other mitigating steps.
For example, some groups or communities have insufficient access to health care facilities.
Those without access may go undiagnosed and untreated. People without easy access to health
care facilities include those without health insurance and those unable to travel to health care
facilities. For example, low-income groups and some elderly and disabled individuals, with
limited or no access to private transportation, may need public transportation to access health
care facilities. If nearby public transportation does not exist, they may not be able to receive the
level of health care that they need.
Examples of possible factors include the following:
Number of hospitals - Some groups, such as inner city residents or indigenous
populations, might not live near a hospital and therefore have to travel longer distances
for medical care; this may limit the frequency and quality of care they receive.
Communities with more hospitals have a wider selection of medical resources from
which to choose; they can select the type and quality of health care appropriate for their
particular needs. This factor is examined in Section 5.2.
Medically underserved - Some groups may differ in the level and quality of health care
they traditionally receive. This may be due to cultural differences, treatment disparities
stemming from socio-economic barriers (e.g., lack of insurance) or other factors. This
factor is examined in Section 5.2.
5.2 Summary of Analysis of Factors that Affect Vulnerability for 61 Notification
Facilities
EPA has compiled data on some of the factors described above to characterize the vulnerabilities
of communities potentially affected by the DSW rule. Specifically, EPA has compiled these data
on the communities surrounding the 61 notification facilities. While EPA does not have
information to know whether or not these results would reflect or represent all of the facilities
that may eventually have claimed an exclusion under the current DSW exclusions, EPA believes
it provides preliminary information regarding the possible extent of multiple exposures to the 61
notification facilities. EPA did not analyze factors that affect vulnerability for communities
around damage case facilities because these facilities represent historical hazards, and may not
be indicative of facilities that will generate and manage HSM under the DSW rule in the future.
In addition, EPA did not analyze factors that affect vulnerability for communities around
hazardous waste facilities and non-hazardous industrial waste facilities because these analyses
were beyond the scope of this analysis. The results of this data collection are summarized in
Table 4.1.
Because of the potential for adverse impacts to communities located around DSW facilities, each
of the factors described in Section 5.1 has the potential to exacerbate those adverse impacts.
While EPA has not attempted to quantify or determining the potential disproportionality of every
possible factors, Table 4.1 does demonstrate that some communities around DSW facilities are
potentially affected by these factors.
In particular, an examination of the facilities that have notified under the current DSW
exclusions shows that multiple environmental hazards are a potential concern for communities
around these facilities. All have multiple facilities reporting to EPA, either under RCRA, the
Clean Air Act (CAA), or Comprehensive Environmental Response, Compensation and Liability
49
-------
Act, (CERCLA - also known as Superfund) within a 3-km radius of the facility. Twenty-six of
the forty facilities had communities with cancer rates greater than the 80th percentile, and
twenty-seven showed a greater than the 80th percentile in neurological hazard rates. Twenty-
seven facilities also had no hospital facilities within the 3-km area.
In addition, as noted in Section 5.1, one of the specific potential impacts of the current DSW
exclusions is that facilities and regulators are not required to solicit or consider community input
into the decision-making process regarding DSW facilities, as is the case with RCRA permitted
facilities. Thus by removing the RCRA permitting requirement for facilities that manage
excluded hazardous secondary materials, the current DSW exclusions also removed one of the
key provisions for allowing communities to participate in the regulatory process (at least as it
concerns the management of the hazardous secondary materials excluded under the rule).
Communities with lower participation levels may experience greater adverse impacts from
environmental decision-making because their input has not been considered fully, particularly if
competing interests are set forth more effectively. This effect is most likely to occur in
communities that have traditionally been excluded from the decision-making process.
50
-------
Table 4.1. Other Factors that Affect Vulnerability in Communities Affected By Recycling Notification Facilities
Facility
Ability to Participate in
Decision Making Process
Physical Infrastructure
Multiple and Cumulative Effects
Percent of Population
(Within 3 km of the Facility)
Transportation and Health
Care Availability
(Within 3 km of the Facility)
Health Risks
(Persons per Million Expected to
Contract Disease Over a 70 Year Period
Within the County of the Facility)
Non-Point Source Air Emissions
(Tons Per Year Within the County of the Facility
Number of Facilities
Reporting to EPA
(Within 3 km of the
Facility)
Name
City
State
Education
Less than
High School
Diploma
Non-English
Speaking
Number of
Hospitals
Medically
Underserved
Cancer
Neurological
Hazard
Respiratory
Hazard
Carbon
Monoxide
Ammonia
Nitrogen
Oxide
Particulates
(size < 10 pm)
Particulates
(size < 2.5 pm)
Sulfur
Dioxide
Volatile
Organic
Compounds
RCRA
AFS
CERCLIS
Curries 12th St
NW Facility
IA0000362905
MASON CITY
IA
16.5%
3.8%
1
No
21.75 (70.5
Percentile)
.04 (68.5
Percentile)
1.67 (71.6
Percentile)
1,339
2,634
258
5,121
1,008
322
1,200
78
22
1
Curries 9th
Street Facility
IAD043490150
MASON CITY
IA
15.6%
4.1%
1
No
21.75 (70.5
Percentile)
.04 (68.5
Percentile)
1.67 (71.6
Percentile)
1,339
2,634
258
5,121
1,008
322
1,200
94
36
1
Diamond Vogel
Paint Co., Inc.
IAD055803423
BURLINGTO
N
IA
20.0%
3.4%
2
Yes
32.37 (90.4
Percentile)
.08 (93.4
Percentile)
1.01 (52.3
Percentile)
592
569
287
4,143
677
329
914
45
21
1
Fres-co System
USA, Inc
IAR000007013
RED OAK
IA
27.0%
4.3%
0
No
14.31 (32.6
Percentile)
.03 (40.4
Percentile)
.58 (31.1
Percentile)
137
1,367
51
2,865
499
60
261
26
9
0
Iowa Contract
Fabricators Inc
IA0000990762
RICEVILLE
IA
22.3%
7.5%
2
No
11.34 (14.2
Percentile)
.02 (17
Percentile)
.28 (14.5
Percentile)
497
2,123
70
3,424
647
71
223
3
3
0
Iowa Mold
Tooling
Company Inc
IAD005286539
GARNER
IA
11.1%
1.6%
1
No
12.42 (19.2
Percentile)
.03 (52.2
Percentile)
.41 (21.2
Percentile)
597
2,484
67
4,588
846
60
553
11
5
0
John Deere
Davenport
Works
IAD073489726
DAVENPORT
IA
8.0%
4.1%
0
No
33.17 (91.1
Percentile)
.09 (95.3
Percentile)
2.34 (81.4
Percentile)
1,071
1,964
1,037
8,066
1,251
1,040
2,990
35
11
0
John Deere
Des Moines
Works
IAD069624500
ANKENY
IA
5.4%
6.9%
1
No
26.04 (81.2
Percentile)
.2 (98.7
Percentile)
2.56 (83.7
Percentile)
2,587
1,642
1,717
16,882
2,479
3,003
7,512
18
16
1
John Deere
Dubuque
Works
IAD005269527
DUBUQUE
IA
16.9%
2.9%
0
No
23.75 (76.2
Percentile)
.05 (74.2
Percentile)
1.56 (69.3
Percentile)
2,452
4,603
561
8,248
1,477
739
2,368
7
3
2
John Deere
Engine Works
IAD000678094
WATERLOO
IA
8.8%
8.2%
1
No
27.95 (84.4
Percentile)
.04 (72.1
Percentile)
2.13 (78.6
Percentile)
2,642
2,245
687
7,244
1,351
853
3,007
25
14
0
John Deere
Waterloo Works
IAD000805168
WATERLOO
IA
19.9%
5.2%
0
No
27.95 (84.4
Percentile)
.04 (72.1
Percentile)
2.13 (78.6
Percentile)
2,642
2,245
687
7,244
1,351
853
3,007
7
5
0
Siegwerk USA
Co
IAD078096732
DES
MOINES
IA
30.7%
16.1%
2
Yes
26.04 (81.2
Percentile)
.2 (98.7
Percentile)
2.56 (83.7
Percentile)
2,587
1,642
1,717
16,882
2,479
3,003
7,512
208
141
0
Siegwerk USA
Co
IAR000007377
DES
MOINES
IA
9.0%
6.2%
0
No
26.04 (81.2
Percentile)
.2 (98.7
Percentile)
2.56 (83.7
Percentile)
2,587
1,642
1,717
16,882
2,479
3,003
7,512
34
46
1
Vogel Paint &
Wax Co Inc
IAD007276728
ORANGE
CITY
IA
16.8%
5.1%
No
20.62 (66.4
Percentile)
.04 (70.6
Percentile)
.46 (24.6
Percentile)
1,309
13,326
187
7,169
1,306
226
1,117
10
7
0
51
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Table 4.1. Other Factors that Affect Vulnerability in Communities Affected By Recycling Notification Facilities
Facility
Ability to Participate in
Decision Making Process
Physical Infrastructure
Multiple and Cumulative Effects
Percent of Population
(Within 3 km of the Facility)
Transportation and Health
Care Availability
(Within 3 km of the Facility)
Health Risks
(Persons per Million Expected to
Contract Disease Over a 70 Year Period
Within the County of the Facility)
Non-Point Source Air Emissions
(Tons Per Year Within the County of the Facility
Number of Facilities
Reporting to EPA
(Within 3 km of the
Facility)
Name
City
State
Education
Less than
High School
Diploma
Non-English
Speaking
Number of
Hospitals
Medically
Underserved
Cancer
Neurological
Hazard
Respiratory
Hazard
Carbon
Monoxide
Ammonia
Nitrogen
Oxide
Particulates
(size < 10 pm)
Particulates
(size < 2.5 pm)
Sulfur
Dioxide
Volatile
Organic
Compounds
RCRA
AFS
CERCLIS
Aleris Rolled
Products, Inc
NJD051415909
CLAYTON
NJ
19.9%
6.7%
0
Yes
32.12 (90.1
Percentile)
.05 (81.8
Percentile)
4.08 (93
Percentile)
4,428
688
797
3,015
842
389
6,882
41
5
1
Aluminum
Shapes LLC
NJD002338267
CAMDEN
NJ
22.3%
12.6%
0
No
39.26 (95.8
Percentile)
.07 (91.7
Percentile)
5.09 (95.8
Percentile)
3,166
720
1,497
2,978
670
504
6,803
187
47
12
Anadigics, Inc.
NJR000036301
WARREN
NJ
7.6%
21.2%
0
No
33.08 (90.9
Percentile)
.06 (85.4
Percentile)
4.39 (93.9
Percentile)
2,055
538
1,047
3,214
560
272
3,907
38
3
0
Melton Sales &
Service
NJD981483035
BORDENTO
WN
NJ
16.2%
9.9%
0
No
33.54 (91.7
Percentile)
.06 (87.7
Percentile)
4.94 (95.4
Percentile)
6,877
960
1,351
4,869
1,330
454
10,554
7
2
1
Melton Sales &
Service
NJR000075796
BURLINGTO
N
NJ
14.9%
11.8%
No
33.54 (91.7
Percentile)
.06 (87.7
Percentile)
4.94 (95.4
Percentile)
6,877
960
1,351
4,869
1,330
454
10,554
49
9
0
Safety-Kleen
Systems, Inc
(Linden Facility)
NJD002182897
LINDEN
NJ
22.9%
32.3%
0
No
51.24 (98.8
Percentile)
0.11 (96.1
Percentile)
7.49 (98.6
Percentile)
1,889
692
1,632
1,600
379
602
8,419
380
71
3
Sancoa
International
NJD986629491
LUMBERTO
N
NJ
8.0%
7.9%
0
No
33.54 (91.7
Percentile)
.06 (87.7
Percentile)
4.94 (95.4
Percentile)
6,877
960
1,351
4,869
1,330
454
10,554
10
2
0
Siegfried USA
Incorporated
NJD064344575
PENNSVILLE
NJ
22.5%
6.5%
0
Yes
28.42 (85.1
Percentile)
.04 (72.9
Percentile)
3.19 (88.2
Percentile)
2,366
784
226
1,583
448
156
1,481
13
3
0
Veolia ES
Technical
Solutions LLC
NJD002454544
MIDDLESEX
NJ
16.6%
29.8%
No
42.44 (97.1
Percentile)
0.08 (94
Percentile)
5.89 (97
Percentile)
2,313
1,110
2,352
4,212
624
688
11,328
207
41
8
Viking Yacht
Company
NJD002482545
NEW
GRETNA
NJ
21.2%
4.4%
0
No
33.54 (91.7
Percentile)
.06 (87.7
Percentile)
4.94 (95.4
Percentile)
6,877
960
1,351
4,869
1,330
454
10,554
2
1
0
BAE Systems,
Land &
Armaments
PAD003025418
YORK
PA
20.8%
3.5%
0
No
38.59 (95.3
Percentile)
0.09 (94.9
Percentile)
4.15 (93.3
Percentile)
10,384
3,488
1,904
17,754
3,425
1,940
8,496
9
3
0
Carpenter
Technology
Corporation
PAD002344315
READING
PA
34.6%
31.6%
Yes
39.16 (95.7
Percentile)
.08 (93.1
Percentile)
3.29 (88.7
Percentile)
8,000
4,298
1,802
14,280
2,690
2,367
10,315
156
34
0
Cherokee
Pharmaceutical
s, LLC
PAD003043353
RIVERSIDE
PA
20.1%
5.2%
0
No
23.91 (76.6
Percentile)
.08 (93.8
Percentile)
2.04 (77.3
Percentile)
3,940
1,628
409
4,675
911
800
1,785
19
5
0
Erie Plating Co
PAD005031448
ERIE
PA
22.1%
11.8%
4
No
28.53 (85.3
Percentile)
0.06 (88.9
Percentile)
1.32 (63.2
Percentile)
2,570
822
1,631
7,677
1,279
2,032
9,674
206
38
0
International
Metals
Reclamation
ELLWOOD
CITY
PA
17.6%
3.9%
0
No
26.33 (81.9
Percentile)
0.06 (84
Percentile)
1.97 (76.4
Percentile)
1,512
610
451
3,661
647
577
2,071
41
16
0
52
-------
Table 4.1. Other Factors that Affect Vulnerability in Communities Affected By Recycling Notification Facilities
Facility
Ability to Participate in
Decision Making Process
Physical Infrastructure
Multiple and Cumulative Effects
Percent of Population
(Within 3 km of the Facility)
Transportation and Health
Care Availability
(Within 3 km of the Facility)
Health Risks
(Persons per Million Expected to
Contract Disease Over a 70 Year Period
Within the County of the Facility)
Non-Point Source Air Emissions
(Tons Per Year Within the County of the Facility
Number of Facilities
Reporting to EPA
(Within 3 km of the
Facility)
Name
City
State
Education
Less than
High School
Diploma
Non-English
Speaking
Number of
Hospitals
Medically
Underserved
Cancer
Neurological
Hazard
Respiratory
Hazard
Carbon
Monoxide
Ammonia
Nitrogen
Oxide
Particulates
(size < 10 pm)
Particulates
(size < 2.5 pm)
Sulfur
Dioxide
Volatile
Organic
Compounds
RCRA
AFS
CERCLIS
Company, Inc
PAD087561015
Jerr-Dan Corp
PAD047518014
GREENCAST
LE
PA
20.1%
3.1%
0
Yes
21.25 (68.6
Percentile)
0.05 (73.7
Percentile)
1.75 (73.2
Percentile)
3,371
4,933
531
8,056
1,420
596
3,645
15
2
0
Jerr-Dan Corp
Wrecker Div
PAR000029769
GREENCAST
LE
PA
24.5%
3.8%
0
Yes
21.25 (68.6
Percentile)
.05 (73.7
Percentile)
1.75 (73.2
Percentile)
3,371
4,933
531
8,056
1,420
596
3,645
28
12
0
John Maneely
Co Wheatland
Tube Division
PAD004322863
SHARON
PA
21.0%
4.6%
0
Yes
22.01 (71.4
Percentile)
0.07 (90.1
Percentile)
1.58 (69.6
Percentile)
2,184
1,036
644
6,286
1,049
797
3,290
49
4
2
John Maneely
Co Wheatland
Tube Division
PAD004338091
WHEATLAN
D
PA
29.0%
4.4%
0
No
22.01 (71.4
Percentile)
0.07 (90.1
Percentile)
1.58 (69.6
Percentile)
2,184
1,036
644
6,286
1,049
797
3,290
39
12
1
John Maneely
Co Wheatland
Tube Division
PAR000038067
WHEATLAN
D
PA
25.4%
5.6%
0
No
22.01 (71.4
Percentile)
0.07 (90.1
Percentile)
1.58 (69.6
Percentile)
2,184
1,036
644
6,286
1,049
797
3,290
42
12
1
Johnson
Matthey
Emissions
Control
Technologies
PAD980829287
WAYNE
PA
2.9%
13.0%
0
No
39.04 (95.6
Percentile)
.08 (92.6
Percentile)
5.61 (96.5
Percentile)
3,689
337
1,902
5,456
1,144
2,034
10,014
47
6
0
Johnson
Matthey
Emissions
Control
Technologies
PAR000519322
SMITHFIELD
PA
27.6%
2.9%
0
Yes
26.6 (82.5
Percentile)
0.04 (67.6
Percentile)
1.78 (73.3
Percentile)
3,522
424
633
4,885
900
1,097
2,749
6
1
0
Piezo Kinetics
Inc
PAR000036772
BELLEFONT
E
PA
19.3%
4.0%
0
No
26.15 (81.6
Percentile)
.05 (80.1
Percentile)
1.91 (75.4
Percentile)
6,428
953
603
7,483
1,457
1,147
2,911
18
7
0
Spectrum
Control
Technology Inc
PAD043882323
STATE
COLLEGE
PA
5.0%
16.2%
0
No
26.15 (81.6
Percentile)
0.05 (80.1
Percentile)
1.91 (75.4
Percentile)
6,428
953
603
7,483
1,457
1,147
2,911
48
13
0
Triangle
Circuits
PAD981037377
OAKMONT
PA
13.8%
5.6%
0
No
63.86 (99.5
Percentile)
0.12 (96.9
Percentile)
5.34 (96.1
Percentile)
8,744
499
5,159
8,770
2,071
5,179
22,416
108
36
0
World
Resources
Company
PAD981038227
POTTSVILLE
PA
25.1%
4.7%
0
No
22.08 (71.9
Percentile)
.07 (90.9
Percentile)
1.87 (74.8
Percentile)
11,143
998
768
6,657
1,404
2,018
3,623
23
9
1
Source - EPA EJViewtool
53
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6 Summary of Results: Assessment of Disproportion Adverse Impacts
6.1 Community-level and Population-level Impacts
Disproportionality was evaluated both at the community and at the population level.
For the community-level analysis, the question is whether the communities in a facility category
had a higher or lower percentage of minority and/or low-income population as compared to the
comparison population (i.e., national or state population). In general, some communities will
have a higher percentage than the comparison population, some will have a lower percentage.
As long as these differences have a regular distribution, they would not indicate disproportionate
impact. However, if the number of communities with a higher percentage of minority and/or
low-income population is greater than that of the comparison populations, then there is a
potential for disproportionate impact. The higher the average difference between the potentially
affected communities and the comparison group, the greater the potential disproportionality.
In the chart below, the damage case facilities are the only category that consistently demonstrates
the potential for disproportionate impact on both minority and low-income communities. For
both the national and the state comparison populations, more than 50% of the damage case
facilities are located in communities with minority and low-income populations that have a
higher representation than the comparison populations. In addition, the average difference in
these cases (i.e., the average amount that the damage case facilities have a higher-than-average
percentage of minorities or low-income populations) range from 7-9%. Hazardous waste
facilities demonstrate a potential for disproportionate impacts to minority communities in the
state comparison but not the national.
Notification and hazardous waste facilities consistently demonstrate the potential for
disproportionate impact on low-income communities at both the national and state level, an
increase as compared to the results in the draft 2011 DSW environmental justice analysis, likely
attributable to the fact that EPA revised the standard for identifying "low income" community to
two times the poverty level in response to peer review and public comments.
54
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Community-Level Analysis of Potential Disproportionate Impacts
of the DSW Exclusions to Minority and Low-Income Communities
Highlighted Values Indicate Potential Disproportionate Impact
National
National
State
State
Comparison
Comparison
Comparison
Comparison
% communities
% communities
% communities
% communities
with higher
with higher low-
with higher
with higher low-
minority
income
minority
income
representation
representation
representation
representation
(average
(average
(average
(average
difference)
difference)
difference)
difference)
Notification
26.7%
51.7%
48.3%
68.3%
Facilities
(-11.84%)
(1.17%)
(0.23%)
(5.25%)
(60 total)
Damage Case
52.4%
68.0%
52.4%
71.2%
Facilities
(6.97%)
(8.65%)
(7.20%)
(8.98%)
(250 total)
Hazardous
46.8%
59.7%
53.5%
60.4%
Waste Facilities
(1.37%)
(4.17%)
(5.07%)
(4.37%)
(2,115 total)
Non-Hazardous
36.0%
48.0%
44.0%
44.0%
Industrial Waste
(-4.0%)
(-0.08%)
(-0.82%)
(-0.73%)
Facilities
(25 total)
The population-level analysis examines the demographics of the total potentially affected
population as compared to the total comparison population to determine (1) whether there is a
substantially greater probability of members in a population group of concern (minority or low-
income) being present as compared to members of the comparison population, and (2) whether
members of the population group of concern comprised a substantially greater proportion of the
potentially affected population than the comparison populations. These two comparisons are
referred to as (1) the Affected Population Ratio, and (2) the Demographic Ratio. In both cases, if
the ratio is greater than 1.0, then there is a potential for disproportionate impact to the population
of concern, and the larger the ratio, the greater the disproportionality.
55
-------
Population-Level Analysis of Potential Disproportionate Impacts
to Minority and Low-Income Communities
Highlighted Values Indicate Potential Disproportionate Impact to Population of Concern
All Results Statistically Significant (p-value <0.05)
National Comparison
Minority Population
Affected Population Ratio
National
Comparison
Low-Income
Population
State
Comparison
Minority
Population
State
Comparison
Low-Income
Population
Demographic Ratio
Affected Population
Ratio
Affected Population
Ratio
Affected
Population Ratio
Demographic Ratio
Demographic Ratio
Demographic
Ratio
Notification
0.83
1.00
1.39
1.31
Facilities
(60 total)
0.89
1.00
1.26
1.21
Damage
2.45
1.60
2.28
1.76
Case
Facilities
(250 total)
1.64
1.36
1.49
1.46
Hazardous
1.68
1.26
1.41
1.09
Waste
Facilities
(2,115
total)
1.42
1.19
1.22
1.06
Non-
1.23
1.13
1.41
1.09
Hazardous
Industrial
Waste
Facilities
(25 total)
1.14
1.09
1.22
1.06
The population-level analysis shows a greater incidence of potential disproportionate impact to
minority and low-income populations than the community-level analysis. For the population-
level analysis, the potential for disproportionate impact (i.e., ratios greater than one) occur under
all categories. This difference can occur when the populations of those communities that do
have a greater percentage of minority or low-income individuals also have a significantly higher
total population than those communities that do not.
The level of statistical significance (p-value) depends on the size of the difference as well as the
total population analyzed. Thus the same Affected Population or Demographic Ratio could be
non-significant for a small number of facilities or a small state or region, but highly significant
for a larger number of facilities or when data from multiple states are pooled. The Affected
56
-------
Population and Demographic Ratios are presented as an indicator of the statistical significance of
the results.
The analysis includes comparisons of data at county, state, and national levels to help assess the
sensitivity of the results to sample size. The notification facilities were located in only a small
number of states, and therefore EPA analyzed each individual state. For other facility types,
facilities were located in a large number of states, which presented challenges for presenting the
information concisely. While EPA conducted analyses for each state in which a facility was
located, EPA aggregated the state-level comparison data into a single table for each facility
category to streamline the presentation of the results.
In regions with few minorities, the minority population comparisons may be less important than
the comparisons of low income populations because a larger percentage of the low income
community may be White, non-Hispanics in such areas. Results for both minority and low-
income populations are presented for each analysis.
Affected Population Ratios are presented in this chapter to help readers determine the statistical
significance of the results presented. They are also used in the calculation of the Fischer's Exact
test and Kendall test.
The statistical analyses for race differences focus on comparing minority (i.e., all populations
except White, Non-Hispanic) and the minority sub-population of American Indian or Alaska
Native (ALAN) with White Non-Hispanic populations. For the notification facilities, EPA
analyzed some minority and key subpopulations, including minority, AIAN, Black or African
American, Native Hawaiian or other Pacific Islander, Hispanic or Latino, or some other race.
These race and ethnicity categories are those identified by the U.S. Census for 2010. Additional
analyses of other racial or ethnic groups for damage cases, hazardous waste facilities, and non-
hazardous industrial waste facilities are beyond the scope of this effort.
6.2 Underlying Vulnerabilities Traditionally Associated with Minority and Low-Income
Communities Pose the Potential to Exacerbate Potential Adverse Impacts of the DSW
Rule
As discussed in Section 5 of this report, other factors can increase the vulnerability in potentially
affected communities to the potential adverse impact of the current DSW exclusions.26 These
factors are described under five broad categories: (1) Susceptible Populations, (2) Multiple and
Cumulative Effects, (3) Unique Exposure Pathways, (4) Ability to Participate in the Decision-
Making Process, and (5) Physical Infrastructure.
All of these factors have the potential to exacerbate the potential for adverse impacts to minority
and low-income communities, but two of these factors are of particular concern to the current
DSW exclusions: Ability to Participate in the Decision-Making Process, and Multiple and
Cumulative Effects
Ability to Participate in the Decision-Making Process
26 U.S. EP A Interim Guidance on Considering Environmental Justice During the Development of an Action July
2010. http://www.epa.gov/environmentaljustice/resources/policy/considering-ej-in-rulemaking-guide-07-2010.pdf
57
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A key element of environmental justice is ensuring that all people have an opportunity for
meaningful involvement in decision-making which may impact them. Certain groups may not
have historically participated in decision-making because of economic (e.g., income), social
(e.g., language barriers, education levels, distrust of government), and infrastructural reasons
(e.g., access to public transportation). In addition, community groups may face higher barriers to
participation than government or private sector entities. For example, taking advantage of
existing public participation mandates may require a significant investment of community
resources or volunteer effort, while government and private sector entities may have more
resources or paid staff to perform these functions. A critical concern is whether, and the extent
to which, communities have the ability to influence the types and number of regulated activities
taking place in their community as well as the requirements, conditions, and parameters by
which such activities must operate (e.g., permit conditions). Under the current DSW exclusions,
facilities claiming an exclusion must submit an initial and biennial notification to EPA or the
state, providing general facility information and describing hazardous secondary material types
and activities under the exclusion.
However, under the current DSW exclusions this information is not made directly available to
potentially affected communities, and facilities and regulators are not required to solicit or
consider community input into the decision-making process as is the case with RCRA permitted
facilities. Thus by removing the RCRA permitting requirement for facilities that manage
excluded hazardous secondary materials, the current DSW exclusions also removed one of the
key provisions for allowing communities to participate in the regulatory process (at least as it
concerns the management of the hazardous secondary materials excluded under the rule).
Communities with lower participation levels may experience greater adverse impacts from
environmental decision-making because their input has not been considered fully, particularly if
competing interests are set forth more effectively. This effect is most likely to occur in
communities that have traditionally been excluded from the decision-making process.
Multiple and Cumulative Effects
Minority, low-income, and indigenous communities that have been affected by multiple
pollution sources may be at risk for increased health consequences. Potential sources of
pollution can include, for example, industrial facilities, landfills, transportation-related air
emissions, poor housing conditions (e.g., lead-based paint), leaking underground tanks,
pesticides, and incompatible land uses. An analysis of the cumulative effects from multiple
stressors can provide a more complete evaluation of a population's health risks from pollutants.
For example, an analysis of discrete stressors and effects on a population might conclude that
nearby pollution sources are within regulatory limits; however, an analysis of cumulative effects
might determine that a person's collective exposure to a contaminant from multiple sources
exceeds a health-based limit.
An examination of the facilities that have notified under the current DSW exclusions shows that
multiple environmental hazards are a potential concern for communities around these facilities.
All have multiple facilities reporting to EPA, either under RCRA, the Clean Air Act (CAA), or
Comprehensive Environmental Response, Compensation and Liability Act, (CERCLA - also
known as Superfund) within a three-kilometer radius of the facility. Twenty-six of the forty
facilities had communities with cancer rates greater than the 80th percentile, and twenty-seven
showed a greater than the 80th percentile in neurological hazard rates. Twenty-seven facilities
also had no hospital facilities within the three kilometer area.
58
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6.3 Preventative and Mitigative Steps That Address the Potential Adverse Impacts to
Minority and Low-Income Communities
The 2014 DSW final rule includes regulatory changes to the 2008 DSW final rule that address
the potential adverse impacts from the current DSW exclusions, including potential adverse
impacts to minority and low-income communities. As discussed in further detail in the preamble
to the 2014 DSW final rule, these changes were made according to EPA's authority under RCRA
to regulate discarded material. Because of these changes, the 2014 DSW final rule is expected to
increase the level of environmental protection for all affected populations without having any
disproportionately high and adverse human health or environmental effects on any population,
including any minority or low-income population.
Below is a summary of the major changes to the current DSW exclusions promulgated in the
2014 DSW final rule, and how they address the potential adverse impacts to human health and
the environment (including impacts to minority and low-income populations).
Replacement of the Transfer-Based Exclusion with the Verified Recvcler Exclusion
The withdrawal of the transfer-based exclusion and its replacement with the verified recycler
exclusion addresses the concerns regarding third-party recyclers. Under the new exclusion,
generators must send their hazardous secondary materials to a RCRA-permitted reclaimer or to a
verified hazardous secondary materials reclaimer who has obtained a solid waste variance from
EPA or the authorized state.
For reclaimers without a RCRA permit, in order to obtain a variance and become verified, the
third-party reclaimer must address criteria that essentially mirrors the criteria under the
reasonable efforts condition in the transfer-based exclusion. This includes: (1) demonstrate their
recycling is legitimate, (2) must have financial assurance in place to properly manage the
hazardous secondary material, (3) must not have had any formal enforcement actions for RCRA
violations in the previous three years and is not classified as a significant non-complier with
RCRA Subtitle C, or must provide credible evidence that the facility will manage the hazardous
secondary materials properly, (4) must have the proper equipment, trained personnel, and meet
emergency preparedness and response requirements to safely reclaim the material, (5) must
manage the residuals from reclamation properly, and (6) must address risk to nearby
communities from potential releases of the hazardous secondary material and in consideration of
existing environmental stressors.
Before a variance can be granted, it will also go through a public notice and comment process,
allowing communities the opportunity to have a voice in the environmental decisions that may
affect them.
Because of the additional oversight, public participation and controls under the verified recycler
exclusion, the potential for increased adverse impact under Scenarios 4, 5, and 6 and the off-site
options under Scenarios 1, 7, and 8 is minimized (see Section 2.1 of Volume 1 Hazard
Characterization for an explanation of the scenarios).
59
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Codified "Contained" Standard
In addition, the codification of the "contained" standard addresses the lack of preventative
measures and the lack of RCRA air standards under the generator-controlled exclusions. Under
the 2014 DSW final rule, the HSM must be contained in a unit (including a land-based unit) that
meets the following criteria:
(1) The unit is in good condition, with no leaks or other continuing or intermittent unpermitted
releases of the hazardous secondary materials to the environment, and is designed, as appropriate
for the hazardous secondary material, to prevent releases of the hazardous secondary materials to
the environment. Unpermitted releases are releases that are not covered by a permit (such as a
permit to discharge to water or air) and may include, but are not limited to, releases through
surface transport by precipitation runoff, releases to soil and groundwater, wind-blown dust,
fugitive air emissions, and catastrophic unit failures;
(2) The unit is properly labeled or otherwise has a system (such as a log) to immediately identify
the hazardous secondary materials in the unit; and
(3) The unit holds hazardous secondary materials that are compatible with other hazardous
secondary materials placed in the unit and is compatible with the materials used to construct the
unit and addresses any potential risks of fires or explosions. Hazardous secondary materials in
units that meet the applicable requirements of 40 CFR parts 264 or 265 are presumptively
contained.
This contained definition provided both the regulated community and the implementing agencies
with an approach that helps address the potential for fires/explosions, environmental
contamination and human exposure under the generator-controlled exclusions in Scenarios 1, 2,
3, 7 and 8.
Emergency Preparedness
New emergency preparedness and response requirements under the generator-controlled
exclusion and the verified recycler exclusion address the risk of fires, explosions and other
accidents. Specifically, EPA is requiring that generators that accumulate less than or equal to
6,000 kg of hazardous secondary material on site comply with the emergency preparedness and
response requirements equivalent to those in part 265 subpart C, which discuss maintaining
appropriate emergency equipment on site, having access to alarm systems, maintaining needed
aisle space, and making arrangements with local emergency authorities. A generator must also
have a designated emergency coordinator who must respond to emergencies and must post
certain information next to the telephone in the event of an emergency. For generators that
accumulate more than 6,000 kg of hazardous secondary material on site, EPA is requiring that
generators comply with requirements equivalent to those in part 265 subparts C and D, which
includes all the requirements already discussed above for those accumulating less than or equal
to 6,000 kg, as well as requiring a contingency plan and sharing the plan with local emergency
responders.
These new requirements help address the potential for fires/explosions, environmental
contamination and human exposure in Scenarios 1, 2, 3, 4, 6, 7 and 8.
60
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Additional Recordkeeping Requirements For Speculative Accumulation and for Transfers
Under the Tolling and Same-Company Provisions Under the Generator-Controlled
Exclusion
Under the 2014 DSW final rule, all persons subject to the speculative accumulation requirements
of 40 CFR § 261.1(c)(8) (including, but not limited to, persons operating under the generator-
controlled exclusion) must place materials subject to those requirements in a storage unit with a
label indicating the first date that the material began to be accumulated. If placing a label on the
storage unit is not practicable, the accumulation period must be documented through an
inventory log or other appropriate method. This provision will allow inspectors and other
regulatory authorities to quickly ascertain how long a facility has been storing an excluded
hazardous secondary material, and, therefore, whether that facility is in compliance with the
accumulation time limits.
In addition, the 2014 DSW final rule includes revisions to the generator-controlled exclusion for
tolling and "same-company" recycling that require recordkeeping for shipments sent and
received under the exclusion. The records must contain the name of the transporter, the date of
the shipment, and the type and quantity of hazardous secondary material shipped or received.
These records may consist of normal business records. Such recordkeeping will facilitate
enforcement of the exclusion and will allow tracking of hazardous secondary materials to ensure
that these materials remain within the control of the generator and are not discarded.
Together, these provisions help address the concern that the HSM could become abandoned
under the generator-controlled exclusions in Scenarios 1, 2, 3, 7 and 8.
6.3.1 Implementation Measures
In addition to the regulatory changes to address potential adverse impacts of hazardous
secondary materials recycling, EPA can take non-regulatory steps to help mitigate the potential
adverse impacts. These steps include closely monitoring the facilities notifying under the 2014
DSW final rule, making information about the DSW facilities available to the public, and
working with states and EPA Regions to ensure they have the information they need to ensure
compliance with the provisions of the rule, and making available to the public information about
the facilities that have notified. EPA has begun this process for the states and territories
currently operating under the 2008 DSW final rule, and plans to continue these efforts in order to
help prevent potential adverse impacts under the 2014 DSW final rule.
In particular, the notification condition will allow EPA (and the public) to know exactly who is
operating under the DSW exclusions. EPA has the authority to inspect these facilities and
enforce Subtitle C regulations if the facilities are not meeting the conditions of the exclusions.
This enforcement authority, coupled with the new condition that EPA is imposing requiring
third-party recyclers be verified prior to operating under the exclusion, will help ensure that
recyclers operating the DSW exclusions are capable of safely and legitimately recycling
hazardous secondary materials prior to beginning operations, and that they continue to do so as
long as they operate under the exclusions.
61
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-------
Attachment A. Methodology for Identifying Potentially Recyclable
Hazardous Wastes
A-l
-------
The Regulatory Impact Analysis (RIA) developed for the Definition of Solid
Waste (DSW) Rule27 uses a two-step data screening (i.e., data selection) process or
methodology to identify potentially recyclable hazardous wastes. This methodology is
applied to wastes reported to the Biennial Report that are managed through methods other
than recycling (i.e., methods other than metals recovery, solvents recovery, or other
recovery).
A detailed description of the methodology for identifying potentially recyclable
hazardous wastes is provided below.
Step 1: Primary screening criteria to identify wastes disposed of containing
constituents of potential commodity value
The first data screening step is structured according to each of the three Biennial
Report recycling methods: metals recovery, solvent recovery, and other recovery. Each
materials recovery method is categorized as a "commodity group" according to the
respective types of materials involved in each of these three recovery methods. EPA
identified and assigned the screening codes based on determining whether each of the
codes pertained to metals, solvents, or to other types of materials contained in the wastes
which might be amenable for recovery in the three commodity groups.
Possible Metals Recovery
¦ If the waste is represented by one of the following waste form codes, it is
assigned to this commodity group:
I 'd I'm Code
I'd I'm Code Description
W107
Aqueous waste containing cyanides
W117
Waste liquid mercury
W303
Ash
W304
Slags, drosses, and other solid thermal residues
W307
Metal scale, filings and scrap (including metal drums)
W312
Cyanide or metal cyanide bearing solids, salts or chemicals
W316
Metal salts or chemicals not containing cyanides
W501
Lime and/or metal hydroxide sludges and solids with no cyanides
W505
Metal bearing sludges (including plating sludge) not containing cyanides
W506
Cyanide-bearing sludges
27 EPA, Regulatory Impact Analysis - USEPA's 2008 Final Rule Amendments to the Industrial Recycling
Exclusions of the RCRA Definition of Solid Waste, September 25, 2008. Available online at:
http://www.regulations.gov/search/Regs/home.html#documentDetail?R=0900006480728all. last accessed
on May 25, 2010.
A-2
-------
¦ If the waste is not associated with any of the above waste form codes, but is
represented by one of the following source codes, it is assigned to this
commodity group:
Source ( ode
Source ( ode Description
GO 3
Plating and phosphating (electro- or non-electroplating or phosphating)
G04
Etching (using caustics or other methods to remove layers or partial
layers)
¦ If the waste is not associated with any of the above waste form or source
codes, but is represented by one of the following EPA hazardous waste codes,
it is assigned to this commodity group:
Wsisle ( ode
\\;is(e ( ode Description
D005
Barium
D006
Cadmium
D007
Chromium
D008
Lead
D009
Mercury
D010
Selenium
DO 11
Silver
F006, F007, F008, F009
Metal electroplating
F010, F011, F012
Metal heat treating
F019
Sludge from conversion coating of aluminum
F035
Inorganic wood preservative waste (arsenic or chromium)
K002, K003, K004,
K005, K006, K007, K008
Inorganic pigment mfg sludge & residues (listed for chromium)
K064, K065, K066,
K069, K086, K100
Lead- or chromium-bearing
K061
Iron & steel mfg emission dust
K071, K073, K106,
K176, K177, K178
Inorganic chemical manufacturing
K171, K172
Petroleum refining spent catalysts
¦ Note that, if the waste stream is represented by waste form code W312
(cyanide or metal cyanide bearing solids, salts or chemicals) and EPA
hazardous waste code K088 (aluminum production spent potliners), it is
moved from Commodity Group #1 (Possible Metals Recovery) to Commodity
Group #3 (Possible Other Recovery). Wastes that fit this description are
generally not recycled by metals recovery, but by other recovery processes.
Possible Solvents Recovery
A-3
-------
¦ If the waste is represented by one of the following waste form codes, it is
assigned to this commodity group:
Idi in ( ode
Form Code Description
W202
Concentrated halogenated (e.g., chlorinated) solvent
W203
Concentrated non-halogenated (e.g., non-chlorinated) solvent
W204
Concentrated halogenated/ non-halogenated solvent mixture
W209
Paint, ink, lacquer, or varnish
W211
Paint thinner or petroleum distillates
¦ If the waste is not associated with any of the above waste form codes, but is
represented by one of the following source codes, it is assigned to this
commodity group:
Source ( ode
Source ( ode Description
G01
Dip, flush or spray rinsing (using solvents to clean or prepare parts or
assemblies for further processing - i.e. painting or assembly)
G06
Painting and coating (manufacturing, building, or maintenance)
¦ If the waste is not associated with any of the above waste form or source
codes, but is represented by one of the following EPA hazardous waste codes,
it is assigned to this commodity group:
Wsisle ( ode
\\;is(e ( ode Description
F001, F002,
F003, F004, F005
Spent solvents
F024, F025
Chlorinated aliphatic manufacturing
K086
Solvent washes of ink equipment
Possible Other Recovery (Carbon Regeneration and Sodium Fluoride)
¦ If the waste is represented by the following waste form code, it is assigned to
this commodity group:
l-'orm ( ode
I'nnil Code Description
W310
Filters, solid adsorbents, ion exchange resins and spent carbon (spent
carbon only)
¦ If the waste is not associated with the above waste form code, but is
represented by the following EPA hazardous waste code, it is assigned to this
commodity group:
Wsiste ( ode
\\;iste ( ode Description
K088
Aluminum production spent potliners (sodium fluoride)
A-4
-------
¦ Note that, if the waste is represented by waste form code W312 (cyanide or
metal cyanide bearing solids, salts or chemicals) and EPA hazardous waste
code K088 (aluminum production spent potliners), it is moved from
Commodity Group #1 (Possible Metals Recovery) to Commodity Group #3
(Possible Other Recovery). Wastes that fit this description are generally not
recycled by metals recovery, but by other recovery processes.
Step 2: Secondary screening criteria (physical quality)
The purpose of these secondary screening criteria is to introduce a consideration
of the anticipated physical quality of the waste. The secondary screening criteria consist
of six elements as follows:
(1) Remove wastes that were residuals from hazardous waste management
processes. Residuals generated by either (a) current materials recovery
operations (H010, H020, H039), (b) energy/fuel recovery operations (H050,
H061), or (c) thermal destructive treatment processes (H040), are assumed
not to have a high content of recoverable material and are assumed will
continue to be disposed. This corresponds to removing wastes with source
code G25. Wastes that are disposed of with RCRA waste codes F006 and
F007 were retained because these potentially recoverable wastes were often
reported using this source code because they are derived from wastewater
treatment processes.
(2) Remove wastes generated from industrial processes that are not continuous
(e.g., those generated from remediation or one-time industrial activities).
The material values from these wastes are less likely to be recoverable given
they are not generated in a controlled process environment (i.e., remediation
wastes involve spills and releases to the environment). Given their one-time
nature of generation, generators are unlikely to go through the notification
process to the Agency for an exclusion from the definition of solid waste for
a one-time waste generation event. This corresponds to removing baseline
disposal data records corresponding to three sets of non-continuous source
codes: (a) spills and accidental releases G31, G32, G33, G39, (b)
remediation of past contamination G41, G42, G43, G44, G45, G49, and (c)
non-periodic activities G12, G15, G19.
(3) Remove wastes with waste descriptions containing the word "debris" from
the data set. The material values from these wastes are less likely to be
recoverable given they are not generated in a controlled process
environment. Given their one-time nature of generation, generators are
unlikely to go through the notification process to the Agency for an
exclusion from the definition of solid waste for a one-time waste generation
event.
A-5
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Remove wastes with waste descriptions indicating they are "rinsewaters" or
"groundwaters" to ensure the physical makeup of the waste (i.e., the
minimal recoverable material concentration) is technically sufficient for
recovery. These dilute aqueous-based wastes typically do not contain
recoverable fractions of valuable materials. This screening criterion was
only applied to wastes with no reported form code. Normally wastes like
these would have a reported form code of W101 very dilute aqueous waste
containing more than 99% water and W105-- acidic aqueous wastes with
less than 5% acid.
Remove some miscellaneous wastes:
¦ On-site Commodity Group #2 quantities were primarily managed by
non-beneficial incineration (H040), or by beneficial energy recovery
(H050), or beneficial fuel blending (H061). For the purposes of the
RIA, it was assumed that facilities that generate and managed wastes on
site via beneficial energy or fuel recovery (i.e., H050 or H061) will not
change to a materials recovery process under the 2008 DSW final rule
exclusions. All these processes require relatively large on-site capital
investments and air pollution control permitting costs, which make it
less likely that on-site H040, H050 or H061 wastes will switch over to
materials recovery under the 2008 DSW final rule. . This corresponds to
removing wastes corresponding to on-site management involving H040,
H050 and H061. Note, however, that the RIA does not remove wastes
corresponding to off-site management involving H040, H050, and H061.
¦ All records with form code W310 not containing the word "carbon" or
"charcoal" in the waste description were deleted. This is necessary
because the definition of the W310 physical/chemical form code allows
reporting together in this single code for four different types of
materials: (1) filters, (2) solid adsorbents, (3) ion exchange resins, and
(4) spent carbons. Because of the lack of characterizing data on the
other three waste typesfilters, solid adsorbents, and ion exchange,
only spent carbon from these four waste types is evaluated.
Because of the fact there are tens of thousands of individual wastes in the
Biennial Report for any given data year, it was beyond the time and resource
constraints of the RIA to individually examine each narrative comment for
wastes containing the "other" code sub-categories. This corresponds to
removing wastes for H129 "other treatment." The "other" form codes
already were removed by their exclusion from the "primary" screening
selection criteria.
A-6
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Attachment B. Statistical Calculations
Affected Population Ratio
The Affected Population Ratio is calculated as follows.
There is a disparity if prl/pr2 ^ 1,
where
prl = prob(within 3-km of facility | in demographic group)
pr2 = prob(within 3-km of facility | not in demographic group)
prl/pr2 = the Affected Population Ratio.
Demographic Ratio
The Demographic Ratio is calculated as follows:
There is a disparity if pr3/pr4 ^ 1,
where
pr3 = prob(in demographic group | within 3-km of facility)
pr4 = prob(in demographic group | not within 3-km of facility).
pr3/pr4 = the Demographic Ratio.
Fisher Exact Test
The Fisher Exact test is calculated as follows (Kendall and Stuart, 1973, sections 33.19
and 33.20):
The Fisher Exact Test calculates the probability that the demographic distributions of the
affected and non-affected populations are as or more extreme than the observed counts.
Let H be the total number in the demographic group and N be the total number not in the
demographic group. Let A be the total number living within 3 km of a facility and let U
be the total number not living within 3 km of a facility. Let x be the number of persons in
the demographic group that also live within 3 km of a facility. Given the values of H, N,
A, and U, the Fisher Exact Test probability (p-value) is twice the sum of the probabilities
of all possible x values equal to or above the observed x (but cannot be more than 1).
When some of H. N, A, and U are too large, the software is unable to compute the p-
value which is reported as "N/A" and in such cases the Kendall Test results can be used
as a good approximation.
B-2
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Kendall Test
The Kendall test is calculated as follows (Kendall and Stuart 1973, sec 33.22):
Std Error (prl-pr2) = [q(l-q){n/(n-l)}{(l/H + 1/N)} ]1/2
SD = (prl-pr2)/[ Std Error (prl-pr2)]
(prl-pr2)/[ q(l-q){n/(n-l)}{(l/H + 1/N)}]1/2,
where n = total population,
q = total within 3-km of facilities/n,
H = total in demographic group, and
N = total not in demographic group, and
SD = the number of standard deviations that the difference (prl-pr2) is
away from 0, the value indicating no disparity under the null hypothesis.
Mantel-Haenszel Common Relative Risk
The procedure developed by Mantel and Haenszel (see Agresti, 2002) was used to
estimate the overall Affected Population Ratio and Demographic Ratio for all states that
have one or more facilities. Assume that all the states have the same underlying Affected
Population Ratio. Using the notation in the above table, the Affected Population Ratio for
a given state is estimated by {a / (a + b)} / {c / (c +d)}. The common Affected Population
Ratio is estimated using the formula
Common Affected Population Ratio = (X a(c + d) / n} / (X c(a + b) / n},
where each sum is over all the tables for the individual states. It can be shown that this
value is a weighted average of the state-specific Affected Population Ratios.
In a similar manner, the Demographic Ratio for a given state is estimated by {a / (a + c)}
/ {b / (b +d)}. The common Demographic Ratio is estimated using the formula
Common Demographic Ratio = (X a(b + d) / n} / (X b(a + c) / n},
where each sum is over all the tables for the individual states. It can be shown that this
value is a weighted average of the state-specific Demographic Ratios.
Cochran-Mantel-Haenszel Test
The procedure developed by Cochran, Mantel and Haenszel (see Cochran, 1954 and
Mantel and Haenszel, 1959) was used to test whether there was a disparity in one or more
of the states that have one or more facilities. The null hypothesis is that the underlying
Threshold Risk Ratio is equal to one for all the states, which is mathematically the same
B-3
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as saying that the underlying Demographic Ratio is equal to one for all the states, which
in turn is the same as the null hypothesis that the location (within or not within 3 km of a
facility) and demographic group are statistically independent for each and every state.
The statistical test is mathematically identical to the Kendall test if there is only one state
that has a facility.
Using the same notation as above, the test statistic is:
X2 = Z (a ~ (a+b)(a+c)/n}2 / £ {(a+b)(a+c)(b+d)(c+d)/(n3 - n2)}
The sum is over all the state tables. The p-value is the probability that a chi-square
distribution with 1 degree of freedom exceeds x2
References
Agresti, A. 2002. Categorical Data Analysis, Second Edition, New York, John Wiley and
Sons.
Cochran, W. G. 1954. Some methods for strengthening the common x2 tests. Biometrics
10: 417-451.
Kendall, M.G. and A. Stuart. 1973. The advanced theory of statistics, Third Edition.
Griffin. London.
Mantel, N. and W. Haenszel. 1959. Statistical aspects of the analysis of data from
retrospective studies of diseases. J. Natl. Cancer Inst. 22: 714-748.
B-4
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Attachment C. Acronyms and Abbreviations
A
AFS Air Facility System
AIAN American Indian/Alaska Native
B
BR Biennial Report
C
CAA Clean Air Act
CERCLA Comprehensive Environmental Response, Compensation and
Liability Act
CERCLIS Comprehensive Environmental Response, Compensation and
Liability Information System
CESQG Conditionally Exempt Small Quantity
CWA Clean Water Act
D
DNA Deoxyribonucleic acid
DOT Department of Transportation
DR Demographic Ratio
DSW Definition of Solid Waste
E
EAF Electric arc furnace
EHS Extremely Hazardous Substance
EJ Environmental Justice
EJ SEAT Environmental Justice Smart Enforcement Assessment Tool
C-l
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EJ Toolkit Toolkit for Assessing Potential Allegations of Environmental
Justices
EPA Please see U.S. EPA
EPCRA Emergency Planning and Community Right-to-Know Act
F
FR Federal Register
FRS Facility Registry System
G
GCE Generator-Controlled Exclusion
GIS Geographic Information Systems
GM Waste Generation and Management
H
HAP Hazardous Air Pollutant
HAZWOPER Hazardous Waste Operations and Emergency Response
HazCom Hazard Communication Standard
IIMR Hazardous Materials Regulations
HMTA Hazardous Materials Transportation Act
HSM Hazardous Secondary Material
HTMR High Temperature Metals Recovery
HWR Hazardous Waste Regulation
I
IARC International Agency for Research on Cancer
IRIS Integrated Risk Information System
K
K061 Electric arc furnace dust
C-2
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LDR
LQG
NAAQS
NAICS
NATA
NBR
NESHAP
NPDES
NPL
NPM
NRC
NRHM
NSPS
OECA
ORCR
OSHA
OSH Act
OSWER
PBE
PC
PERC
L
Land Disposal Restrictions
Large quantity generator
N
National Ambient Air Quality Standards
North American Industry Classification System
National-Scale Air Toxics Assessment
National Biennial Report
National Emissions Standards for Hazardous Air Pollutants
National Pollutant Discharge Elimination System
National Priorities List
National Program Manager
National Response Center
Non-Radioactive Hazardous Materials
New Source Performance Standards
O
Office of Enforcement and Compliance
Office of Resource Conservation and Recovery
Occupational Safety and Health Administration
Occupational Safety and Health Act
Office of Solid Waste and Emergency Response
P
Petition-Based Exclusion
Priority Chemical
T etrachl oroethyl ene
C-3
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POTW
PPm
ppmw
PR
PSM
RCRA
RCRAInfo
RIA
RMP
RQ
SD
SF
Site ID
SOCMI
SPCC
SQG
TBE
TPY
APR
TSDF
U.S.
Publicly Owned Treatment Works
Parts per million
Parts per million by weight
Population ratio
Process Safety Management
R
Resource Conservation and Recovery Act
Resource Conservation and Recovery Act Information
Regulatory Impact Analysis
Risk Management Plan
Reportable Quantities
S
Standard Deviation
Summary File
Site Identification
Synthetic Organic Chemical Manufacturing Industry
Spill Prevention, Control, and Countermeasure
Small quantity generators
T
Transfer-Based Exclusion
Tons per Year
Affected Population Ratio
Treatment, Storage, or Disposal Facility
U
United States
C-4
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U.S. EPA United States Environmental Protection Agency
V
VOC Volatile Organic Compound
W
WR Waste Received from Off site
C-5
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Attachment D. Glossary
A
Air Facility System
Contains compliance and permit data for stationary sources regulated by EPA, state and local air
pollution agencies
American Indian Alaska
Native
A Census Bureau term that refers to these entity types: American Indian reservation, American
Indian off-reservation trust land, Oklahoma tribal statistical area, joint use area, American Indian
tribal subdivision, tribal designated statistical area, state designated American Indian statistical area,
Alaska Native Regional Corporation, Alaska Native village, Alaska Native village statistical area.
B
Biennial Report All generators and treatment, storage, and disposal (TSD) facilities who handle hazardous waste are
required to report to the EPA Administrator at least once every two years. The data collected is used
to create the National Biennial Resource Conservation and Recovery Act (RCRA) Hazardous Waste
Report. This data is processed within the RCRA Information (RCRAInfo) database.
Block group A statistical subdivision of a census tract. A block group (BG) consists of all tabulation blocks
whose numbers begin with the same digit in a census tract; for example, for Census 2010, BG 3
within a census tract includes all blocks numbered between 3000 and 3999. The block group is the
lowest-level geographic entity for which the Census Bureau tabulates sample data from the
decennial census.
C
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Census Block
An area bounded by visible and/or invisible features shown on Census Bureau maps. A block is the
smallest geographic entity for which the Census Bureau collects and tabulates 100-percent
decennial census data.
Clean Air Act
Clean Water Act
Comprehensive
Environmental Response,
Compensation and
Liability Act
Comprehensive
Environmental Response,
Compensation and
Liability Information
System
Conditionally Exempt
Small Quantity Generator
D001
D007
D008
Comprehensive federal law that regulates air emissions from stationary and mobile sources.
Establishes the basic structure for regulating discharges of pollutants into the waters of the United
States and regulating quality standards for surface waters
Known as CERCLA or Superfund, provides a Federal "Superfund" to clean up uncontrolled or
abandoned hazardous waste sites as well as accidents, spills, and other emergency releases of
pollutants and contaminants into the environment.
CERCLIS is EPA's inventory of abandoned, inactive, or uncontrolled hazardous waste sites
regulated under the Comprehensive Environmental Response, Compensation, and Liability Act
(CERCLA). It records information about all aspects of hazardous waste sites from initial discovery
to listing on the National Priorities List (NPL).
Generate 100 kilograms or less per month of hazardous waste, or 1 kilogram or less per month of
acutely hazardous waste
D
Ignitable waste
Chromium waste
Lead waste
D-2
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Damages
The likelihood of harm or injury to property or a person resulting in loss of value or the impairment
of usefulness
Damage Case Facility
Definition of Solid Waste
Definition of Solid Waste
Rule
Definition of Solid Waste
Final Rule (2008)
Disproportionate Impact
Facilities that highlighted in EPA's An Assessment of Environmental Problems Associated with
Recycling of Hazardous Secondary Materials
A solid waste is any discarded material that is not excluded under §261.4(a) or that is not excluded
by a variance granted under §§260.30 and 260.31 or that is not excluded by a non-waste
determination under §§260.30 and 260.34.
The DSW rule creates specific conditions for recycling hazardous secondary materials under the
Resource Conservation and Recovery Act (RCRA).
Revision of the Definition of Solid Waste under RCRA for certain types of hazardous secondary
materials being recycled
Impact that: (1) is predominately borne by a minority population and/or a low-income population;
or (2) is appreciably more severe or greater in magnitude than the adverse effect or impact that will
be suffered by a non-minority population and/or non-low-income population.
E
EJ Toolkit
Emergency Planning and
Community Right-to-know
Act
Toolkit for Assessing Potential Allegations of Environmental Justices
Establishes requirements for Federal, state and local governments, Indian Tribes, and industry
regarding emergency planning and "Community Right-to-Know" reporting on hazardous and toxic
chemicals.
Environmental Justice
The fair treatment and meaningful involvement of all people regardless of race, color, national
origin, or income with respect to the development, implementation, and enforcement of
environmental laws, regulations, and policies.
D-3
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Environmental Justice
Smart Enforcement
Assessment Tool
Created by EPA's Office of Enforcement and Compliance Assurance to serve as a consistent
methodology that would enable OECA to identify communities or areas experiencing
disproportionate environmental and public health burdens for the purposes of enhancing and
focusing OECA's enforcement and compliance in those areas.
F003
F005
F006
F037
F1 5
Facility Registry System
Spent non-halogenated solvents
Spent non-halogenated solvents
Wastewater treatment sludges
Petroleum refinery primary sludges
Mixture of F001-F005
FRS is a centrally managed database that identifies facilities, sites or places subject to
environmental regulations or of environmental interest.
Generator-Controlled
Exclusion
Materials that are generated and transferred to another company for legitimate reclamation under
specific conditions
Geographic Information
System
A computer system for the input, storage, processing, applications development, retrieval, and
maintenance of information about the points, lines, and areas that represent the streets and roads,
rivers, railroads, geographic entities, and other features on the surface of the Earth-information that
previously was available only on paper maps.
H
D-4
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Hazard Communication
Standard
Hazardous Air Pollutant
Hazardous Materials
Regulations
Hazardous Materials
Transportation Act
Hazardous Secondary
Materials
Hazardous Waste Facilities
Hazardous Waste
Operations and Emergency
Response
The HCS became effective in 1986. A fundamental premise of the HCS is that employees who may
be exposed to hazardous chemicals in the workplace have a right to know about the hazards and
how to protect themselves
HAPs are pollutants that are known or suspected to cause cancer or other serious health effects,
such as reproductive effects or birth defects, or adverse environmental effects.
HMRs are issued by the Pipeline and Hazardous Materials Safety Administration and govern the
transportation of hazardous materials by highway, rail, vessel, and air. The HMR address hazardous
materials classification, packaging, hazard communication, emergency response information and
training.
Its primary objective is to provide adequate protection against the risks to life and property inherent
in the transportation of hazardous material in commerce by improving the regulatory and
enforcement authority of the Secretary of Transportation.
The DSW rule defines hazardous secondary materials (HSM) as those materials that would be
classified as hazardous waste, if discarded. HSMs can be stored for longer periods of time than
hazardous materials, but must meet various criteria such as 75% of the material must be recycled
each year.
Likely to recycle under the DWS Final Rule, including hazardous waste generators producing more
than a truckload (25 tons) of recyclable hazardous secondary materials annually, and hazardous
waste recyclers
Refers to five types of hazardous waste operations conducted in the United States under OSHA
Standard 1910.120 "Hazardous Waste Operations and Emergency Response." The standard contains
the safety requirements employers must meet in order to conduct these operations.
I
D-5
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Integrated Risk
Information System
a human health assessment program that evaluates quantitative and qualitative risk information on
effects that may result from exposure to environmental contaminants
K
K061 Electric arc furnace dust
K088 Spent potliners
K171 Spent hydrotreating catalyst
KXXX Mixture of K waste code wastes
L
Land Disposal Restrictions LDR program ensures that toxic constituents present in hazardous waste are properly treated before
hazardous waste is land disposed
Large quantity generator LQG generate 1,000 kilograms per month or more of hazardous waste, or more than 1 kilogram per
month of acutely hazardous waste.
N
National Ambient Air Standards established by EPA under authority of the Clean Air Act (42 U.S.C. 7401 et seq.) that
Quality Standards apply for outdoor air throughout the country. Primary standards set limits to protect public health,
including the health of "sensitive" populations such as asthmatics, children, and the elderly.
Secondary standards set limits to protect public welfare, including protection against decreased
visibility, damage to animals, crops, vegetation, and buildings.
D-6
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National Emissions
Standards for Hazardous
Air Pollutants
National Priorities List
National Response Center
National-Scale Air Toxics
Assessment
New Source Performance
Standards
Non-hazardous Industrial
Waste Facilities
North American Industry
Classification System
Notification Facility
NESHAPS are stationary source standards for hazardous air pollutants.
The list of national priorities among the known releases or threatened releases of hazardous
substances, pollutants, or contaminants throughout the United States and its territories. The NPL is
intended primarily to guide the EPA in determining which sites warrant further investigation.
The NRC is the sole federal point of contact for reporting all hazardous substances and oil spills.
The NRC receives all reports of releases involving hazardous substances and oil that trigger the
federal notification requirements under several laws.
U.S. EPA developed the NATA as a state-of-the-science screening tool for State/Local/Tribal
Agencies to prioritize pollutants, emission sources and locations of interest for further study in order
to gain a better understanding of risks.
Section 111 of the Clean Air Act authorized the EPA to develop technology based standards which
apply to specific categories of stationary sources. These standards are found in 40 CFR Part 60. The
NSPS apply to new, modified and reconstructed affected facilities in specific source categories such
as manufacturers of glass, cement, rubber tires and wool fiberglass.
Facilities not currently generating or managing hazardous wastes that may choose to begin
reclaiming hazardous secondary materials under the 2008 DSW Final Rule
The standard used by Federal statistical agencies in classifying business establishments for the
purpose of collecting, analyzing, and publishing statistical data related to the U.S. business
economy.
Facility that has notified EPA that it will be managing hazardous secondary materials under the
2008 DSW Final Rule
D-7
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o
Occupational Safety and
Health Act
The primary federal law which governs occupational health and safety in the private sector and
federal government in the United States.
Petition-Based Exclusion
Process Safety
Management
Materials that EPA or an authorized state determines to be non-wastes through a case-by-case
petition process.
The major objective of process safety management (PSM) of highly hazardous chemicals is to
prevent unwanted releases of hazardous chemicals especially into locations that could expose
employees and others to serious hazards. An effective process safety management program requires
a systematic approach to evaluating the whole chemical process.
R
Resource Conservation and
Recovery Act
Resource Conservation and
Recovery Act Information
Risk Management Plan
(RMP)
The (RCRA) gives EPA the authority to control hazardous waste from the "cradle-to-grave." This
includes the generation, transportation, treatment, storage, and disposal of hazardous waste. RCRA
also set forth a framework for the management of non-hazardous solid wastes.
RCRAInfo is EPA's comprehensive information system that supports the Resource Conservation
and Recovery Act (RCRA) of 1976 and the Hazardous and Solid Waste Amendments (HSWA) of
1984 through the tracking of events and activities related to facilities that generate, transport, and
treat, store, or dispose of hazardous waste. RCRAInfo allows RCRA program staff to track the
notification, permit, compliance, and corrective action activities required under RCRA.
The RMP database stores the risk management plans reported by companies that handle,
manufacture, use, or store certain flammable or toxic substances, as required under section 112(r) of
the Clean Air Act (CAA).
D-£
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Rural
All territory, population, and housing units located outside of urbanized areas and urban clusters.
S
Spill Prevention, Control,
and Countermeasure Plan
Small Quantity Generator
Transfer-Based Exclusion
Urban
Urban Cluster
Urbanized Area
Volatile Organic
Compound
The Spill Prevention, Control, and Countermeasure (SPCC) rule includes requirements for oil spill
prevention, preparedness, and response to prevent oil discharges to navigable waters and adjoining
shorelines. The rule requires specific facilities to prepare, amend, and implement SPCC Plans. The
SPCC rule is part of the Oil Pollution Prevention regulation, which also includes the Facility
Response Plan (FRP) rule.
SQG generate more than 100 kilograms, but less than 1,000 kilograms, of hazardous waste per
month.
T
Materials that are generated and legitimately reclaimed under the control of the generator
U
For Census 2010, all territory, population, and housing units in urbanized areas and urban clusters.
A densely settled area that has a census population of 2,500 to 49,999.
A densely settled area that has a census population of at least 50,000.
V
VOCs are organic chemical compounds whose composition makes it possible for them to evaporate
under normal indoor atmospheric conditions of temperature and pressure.
D-9
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Attachment E. National and State Urban and Rural Analyses
D-l
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Notification Facilities
Table 6-1 National Urban Demographic Comparison Analysis of Statistical Significance for Notification Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact Test
P-value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall
Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic
whites)
0.70821708
0.807716274
N/A
N/A
0.003719767
-150.944
~o
Persons below 200% poverty
1.022017821
1.014927126
9.69E-21
9.339374085
0.003719767
9.3522191
8.58E-21
American Indians and Alaska
Natives
0.68872454
0.690369402
3.47E-226
32.10742312
0.003719767
-30.34102
3.30E-202
Children under age 5
0.96289238
0.965203379
5.91E-18
8.634198023
0.003719767
8.5890718
8.77E-18
Table 6-2 National Rural Demographic Comparison Analysis of Statistical Significance for Notification Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact Test
P-value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall
Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic
whites)
0.91244904
0.927625227
1.84974E-
37
12.79062768
0.001609112
12.674748
8.16203E-
37
Persons below 200% poverty
0.798393263
0.850944199
1.93E-294
36.67358528
0.001609112
36.128774
8.02E-286
American Indians and Alaska
Natives
0.311101089
0.315601471
N/A
N/A
0.001609112
37.613355
~0
Children under age 5
1.083814844
1.078417702
6.14E-13
7.197247726
0.001609112
7.2827155
3.27E-13
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Table 6-3 State Urban Demographic Comparison for Notification Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
22
12
0
7.38%
5.78%
Below 200%
Poverty Level
28
6
0
14.34%
15.88%
American Indians
or Alaska
Natives
24
10
0
0.38%
0.18%
Children under
age 5
30
4
0
2.09%
0.18%
D-2
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Table 6-4 State Rural Demographic Comparison for Notification Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
22
4
0
13.57%
9.25%
Below 200%
Poverty Level
26
0
0
21.64%
22.02%
American Indians
or Alaska
Natives
18
8
0
0.82%
0.10%
Children under
age 5
26
0
0
4.33%
4.64%
Table 6-5 State Urban Demographic Comparison Analysis of Statistical Significance for Notification Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.222894989
1.145210456
~0
Persons below 200% poverty
1.26910836
1.187335614
~0
American Indians and Alaska Natives
1.272727197
1.288744365
7.22E-89
Children under age 5
1.029689055
1.029028231
1 21276E-11
D-3
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Table 6-6 State Rural Demographic Comparison Analysis of Statistical Significance for Notification Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.883920185
1.760132319
~0
Persons below 200% poverty
1.328260145
1.240486806
~0
American Indians and Alaska Natives
1.203969152
1.208893649
8.23E-09
Children under age 5
1.180449912
1.883920185
1.175146591
1.760132319
1.2868E-52
~0
Damage Case Facilities
Table 6-7 National Urban Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Fisher Exact
Test P-value
Equivalent No. of
Standard
Deviations (SD)
Probability
(Affected)
Minority (all except non-Hispanic whites)
1.97697811
1.418345381
~0
N/A
0.035501109
Persons below 200% poverty
1.595986784
1.3574736
~0
N/A
0.035501109
American Indians and Alaska Natives
1.080614335
1.082800466
4.81E-130
24.26307841
0.035501109
Children under age 5
0.964164506
0.96533024
5.56E-151
26.17185442
0.035501109
Table 6-8 National Rural Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Fisher Exact
Test P-value
Equivalent No. of
Standard
Deviations (SD)
Probability
(Affected)
K
Minority (all except non-Hispanic whites)
1.440430372
1.33172518
~0
N/A
0.003484304
Persons below 200% poverty
1.177947532
1.117304194
~0
N/A
0.003484304
American Indians and Alaska Natives
0.535043335
0.539775786
N/A
N/A
0.003484304
-
Children under age 5
1.142361129
1.133015268
6.67E-71
17.80323963
0.003484304
D-4
-------
Table 6-9 State Urban Demographic Comparison for Damage Case Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
128
41
0
18.79%
19.43%
Below 200%
Poverty Level
142
27
0
17.33%
18.60%
American Indians
or Alaska
Natives
113
56
0
0.31%
0.22%
Children under
age 5
133
36
0
1.59%
1.55%
D-5
-------
Table 6-10. State Rural Demographic Comparison for Damage Case Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
77
5
0
19.47%
10.07%
Below 200%
Poverty Level
82
0
0
28.00%
25.55%
American Indians
or Alaska
Natives
58
24
0
0.96%
0.44%
Children under
age 5
81
1
0
5.00%
5.08%
Table 6-11 State Urban Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.993597083
1.382311819
~0
Persons below 200% poverty
1.720405497
1.447891817
~0
American Indians and Alaska Natives
1.101169035
1.108153786
3.50E-213
Children under age 5
0.976523831
0.97656438
1.35602E-66
D-6
-------
Table 6-12 State Rural Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.653242335
1.418026215
~0
Persons below 200% poverty
1.371261402
1.236323057
~0
American Indians and Alaska Natives
0.871452636
0.876359246
2.47E-15
Children under age 5
1.18862933
1.176968713
2.2475E-123
Hazardous Waste Facilities
Table6-13 National Urban Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Fisher
Exact
Test P-
value
Equivalent No.
of Standard
Deviations (SD)
Probability
(Affected)
Kend
Sta
Minority (all except non-Hispanic whites)
1.340072517
1.210475806
~0
N/A
0.159826638
9
Persons below poverty
1.25425977
1.196325972
~0
N/A
0.159826638
7
American Indians and Alaska Natives
0.915856581
0.90243699
N/A
N/A
0.159826638
-5
Children under age 5
1.023988452
1.026680122
~0
N/A
0.159826638
3
D-7
-------
Table6-14 National Rural Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Fisher Exact
Test P-value
Equivalent No. of
Standard
Deviations (SD)
Probability
(Affected)
Minority (all except non-Hispanic whites)
1.173953984
1.1392171
~0
N/A
0.015625854
Persons below 200% poverty
0.991910751
0.994295062
1.87E-05
4.279797927
0.015625854
American Indians and Alaska Natives
0.535710054
0.537395417
N/A
N/A
0.015625854
Children under age 5
1.07708188
1.073249732
4.16E-96
20.80193737
0.015625854
Table 6-15 State Urban Demographic Comparison for Hazardous Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
989
350
0
14.96%
13.33%
Below 200%
Poverty Level
1044
295
0
13.34%
13.29%
American Indians
or Alaska
Natives
831
508
0
0.34%
0.15%
Children under
age 5
1151
188
0
1.99%
1.92%
D-8
-------
Table 6-16 State Rural Demographic Comparison for Hazardous Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
699
77
0
17.82%
10.30%
Below 200%
Poverty Level
765
11
0
22.77%
22.27%
American Indians
or Alaska
Natives
499
277
0
0.79%
0.24%
Children under
age 5
761
15
0
4.44%
4.32%
Table 6-17 State Urban Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.169679077
1.091098002
~0
Persons below 200% poverty
1.091134577
1.05966551
1.7355E-204
American Indians and Alaska Natives
0.928180233
0.9280704
4.53E-06
Children under age 5
1.021002621
1.019725909
1.24E-04
D-9
-------
Table 6-18 State Rural Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.133832219
1.098239859
9.13952E-19
Persons below 200% poverty
0.622146433
0.707348497
1.1341E-272
American Indians and Alaska Natives
0.203457086
0.205058948
3.96E-48
Children under age 5
1.097167441
1.090681814
2.3246E-05
Non-hazardous Industrial Waste Facilities
Table 6-19 National Urban Demographic Comparison Analysis of Statistical Significance for Non-Hazardous Industrial Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Fisher Exact Test
P-value
Equivalent No. of
Standard
Deviations (SD)
Probability
(Affected)
Minority (all except non-Hispanic whites)
0.997496453
0.998553861
0.367175315
0.901777047
0.002351492
Persons below 200% poverty
1.153154734
1.099561588
~0
N/A
0.002351492
American Indians and Alaska Natives
0.624042044
0.626164339
8.89E-215
31.27943651
0.002351492
Children under age 5
1.008581189
1.008011967
1.16E-01
1.573669381
0.002351492
Table 6-20 National Rural Demographic Comparison Analysis of Statistical Significance for Non-Hazardous Industrial Waste Facilities
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact Test
P-value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic whites)
1.063760577
1.051170205
9.2918E-06
4.433029954
0.000397788
4.457651402
8.28625E-06
Persons below 200% poverty
0.618979855
0.701023515
N/A
N/A
0.000397788
-36.04832482
1.47E-284
American Indians and Alaska Natives
0.091311943
0.093164761
6.87E-222
31.79814334
0.000397788
-24.77626184
1.62E-135
Children under age 5
1.120590952
1.112427914
3.08E-07
5.118651895
0.000397788
5.194993364
2.05E-07
D-10
-------
Table 6-21 State Urban Demographic Comparison for Non-Hazardous Industrial Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
11
6
0
9.30%
8.53%
Below 200%
Poverty Level
12
5
0
9.30%
7.20%
American Indians
or Alaska
Natives
11
6
0
0.20%
0.13%
Children under
age 5
15
2
0
1.75%
1.45%
D-ll
-------
Table 6-22 State Rural Demographic Comparison for Non-Hazardous Industrial Waste Facilities
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
7
1
0
14.99%
11.37%
Below 200%
Poverty Level
6
2
0
18.66%
14.92%
American Indians
or Alaska
Natives
3
5
0
0.23%
-0.07%
Children under
age 5
761
15
0
4.44%
4.32%
Table 6-23 State Urban Demographic Comparison Analysis of Statistical Significance for Non-Hazardous Industrial Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.169679077
1.091098002
~0
Persons below 200% poverty
1.091134577
1.05966551
1.7355E-204
American Indians and Alaska Natives
0.928180233
0.9280704
4.53E-06
Children under age 5
1.021002621
1.019725909
0.000123739
D-12
-------
Table 6-24 State Rural Demographic Comparison Analysis of Statistical Significance for Non-Hazardous Industrial Waste Facilities
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.133832219
1.098239859
9.13952E-19
Persons below 200% poverty
0.622146433
0.707348497
1.1341E-272
American Indians and Alaska Natives
0.203457086
0.205058948
3.96E-48
Children under age 5
1.097167441
1.090681814
2.3246E-05
D-13
-------
Commercial Hazardous Waste Facilities That Do Not Recycle
Figure 6.1 Demographics for Commercial Hazardous Waste Facilities That Do Not Recycle
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
a
1 __
iZJ
rd
r
ii
II r
1
tl
1 i
t
Minority (all except
non-Hispanic
whites)
i Persons 200%
below poverty
American Indians
and Alaska Natives
0-10% 11-20% 21-30% 31-40% 41-50% 50-100%
Percent of Population in Demographic
Table 6-25 National Demographic Comparison for Commercial Hazardous Waste Facilities That Do Not Recycle
D-14
-------
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
195
179
0
7.50%
1.11%
Below 200%
Poverty Level
255
119
0
8.20%
8.75%
American Indians
or Alaska
Natives
100
274
0
0.03%
-0.70%
Children under
age 5
208
166
0
0.33%
0.23%
D-15
-------
Table 6-26 State Demographic Comparison for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
219
155
0
10.57%
5.94%
Below 200%
Poverty Level
252
122
0
7.17%
7.11%
American Indians
or Alaska
Natives
138
236
0
-0.01%
-0.24%
Children under
age 5
211
163
0
0.22%
0.29%
D-16
-------
Table 6-27 State Urban Demographic Comparison for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
158
37
0
25.65%
22.94%
Below 200%
Poverty Level
165
30
0
18.90%
21.75%
American Indians
or Alaska
Natives
131
64
0
0.46%
0.13%
Children under
age 5
183
12
0
2.43%
2.28%
D-17
-------
Table 6-28 State Rural Demographic Comparison for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic
Group
Number of
Facilities with
%
Demographics
Greater Than
Area
Comparison
Number of
Facilities with
%
Demographics
Less Than Area
Comparison
Number of
Facilities with
%
Demographics
Equal to Area
Comparison
Mean
Difference
Median
Difference
Minority (all
except non-
Hispanic whites)
166
13
0
24.68%
17.29%
Below 200%
Poverty Level
175
4
0
25.51%
25.05%
American Indians
or Alaska
Natives
102
77
0
0.92%
0.12%
Children under
age 5
176
3
0
4.27%
3.91%
Table 6-29 National Demographic Comparison Analysis of Statistical Significance for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact Test
P-value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall
Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic
whites)
2.646397133
1.683429372
~o
N/A
0.020955069
1272.548665
~o
Persons below poverty
1.589051251
1.349132516
~0
N/A
0.020955069
592.5296046
~0
American Indians and Alaska
Natives
0.824841894
0.823856736
N/A
N/A
0.020955069
53.44012507
~0
Children under age 5
1.127435729
1.120836528
~0
N/A
0.020955069
80.61309423
~0
D
-------
Table 6-30 National Urban Demographic Comparison Analysis of Statistical Significance for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact Test
P-value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall
Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic
whites)
2.127700864
1.457330272
~o
N/A
0.027738431
955.6563884
~o
Persons below poverty
1.585120102
1.348126784
~0
N/A
0.027738431
582.7875599
~0
American Indians and Alaska
Natives
1.03756889
1.038226537
1.18E-23
10.02534523
0.027738431
10.08264294
6.59E-24
Children under age 5
1.098993391
1.094506278
~0
N/A
0.027738431
62.75675604
~0
Table 6-31 National Rural Demographic Comparison Analysis of Statistical Significance for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic Group
Affected
Population
Ratio
Demographic
Ratio
Fisher
Exact
Test
P-
value
Equivalent
No. of
Standard
Deviations
(SD)
Probability
(Affected)
Kendall
Test
Statistic
Kendall
Test P-
Value
Minority (all except non-Hispanic
whites)
1.371313481
1.282623826
~o
N/A
0.002397605
60.34486091
~o
Persons below poverty
1.082731832
1.056017756
5.25E-
61
16.47837569
0.002397605
16.56119631
1.33E-61
American Indians and Alaska
Natives
0.572912851
0.577830077
9.54E-
207
30.6832035
0.002397605
28.30777462
2.77E-176
Children under age 5
1.092753255
1.08680898
2.60E-
22
9.715069113
0.002397605
9.836315749
7.85E-23
D
-------
Table 6-32 State Demographic Comparison Analysis of Statistical Significance for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
2.875510052
1.632878006
~0
Persons below poverty
1.661060211
1.389051189
~0
American Indians and Alaska Natives
0.929909127
0.929985531
3.26E-177
Children under age 5
1.122352268
1.116151058
~0
Table 6-33 State Urban Demographic Comparison Analysis of Statistical Significance for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
2.355590994
1.475416311
~0
Persons below poverty
1.627443251
1.380226678
~0
American Indians and Alaska Natives
1.09067331
1.093435702
3.31 E-249
Children under age 5
1.093565081
1.091025263
~0
Table 6-34 State Rural Demographic Comparison Analysis of Statistical Significance for Commercial Hazardous Waste Facilities That Do Not Recycle
Demographic Group
Affected
Population Ratio
Demographic Ratio
Cochran-Mantel-Haenszel P-
value
Minority (all except non-Hispanic whites)
1.675633862
1.459629196
~0
Persons below poverty
1.052971495
1.035053934
8.57226E-51
American Indians and Alaska Natives
0.752862492
0.762978304
1.38E-88
Children under age 5
1.10486831
1.098427469
2.87513E-55
D-20
------- |