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 Methodology ...................................................................................................................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 Multiple and Cumulative 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
ii

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 LowIncome 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-1

Attachment B. Statistical Calculations ....................................................................................... B-2

Attachment C. Acronyms and Abbreviations............................................................................. C-1

Attachment D. Glossary.............................................................................................................. D-1

Attachment E. State, Urban and Rural Analyses.........................................................................E-1
iii
 1

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.

 
2

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.

 Facilities 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.
3

 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/notify-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 
4

“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_java.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 
5

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/ej-meth.pdf.

3

 Id. P 17
6

 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 H010), solvents recovery (BR management 

method code H020), and other recovery (BR management method code H039).
7

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. Identified facilities 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 generatorbased 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. Excluded facilities that submitted notification to EPA indicating that they would be 

managing hazardous secondary materials under the 2008 DSW final 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. 
8

final rule, since these facilities are being analyzed under Section 2.4.1 of this 

document (“Notification Facilities”).

5. Excluded facilities 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. 
9

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 H010), 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-HQ-RCRA-2010-0742-0002. 
10

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. Excluded facilities that submitted notification to EPA indicating that they would be 

managing hazardous secondary materials under the 2008 DSW final 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. Excluded facilities 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. Excluded facilities 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 
11

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 
12

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).
13

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 Code8data 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

Disposal Units

H132 Landfill or surface impoundment 

that will be closed as landfill

D80 Landfill

D83 Surface impoundment disposal

H131 Land treatment or application D81 Land application

Thermal Treatment Units

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

X01 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 Code9in 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:

RCRAInfo Legal and Operating Status Codes Considered Active

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.
14

Commercial Status 

Category RCRAInfo Commercial Status Code

Commercial 1 Accepts waste from offsite generators

3 Accepts waste from limited offsite 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:

Biennial Report Management Method Code Description

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). 
15

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. 
16
17

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
 18

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 
 19

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.

 
 20

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 nonaffected population in the selected buffer regions.
 21

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 nondemographic 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 CochranMantel-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-1), 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 pr1/pr2 = 1 against the alternative hypothesis that pr1/pr2 

≠ 1. This alternative hypothesis means that either demographic group G populations are more adversely affected 

(pr1/pr2 > 1) or non-affected demographic group G populations are more adversely affected (pr1/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 pr1/pr2 > 1 and the probabilities of chance occurrence (p-values) 

would be halved (assuming that the estimated ratio pr1/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.
 22

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: Plaintiff’s 

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.
 23

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. 
 24

Figure 2.1 Demographics for Notification Facilities

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 11-20% 21-30% 31-40% 41-50% 50-100%

Percent of Facilities

Percent of Population in Demographic

Minority (all except

non-Hispanic whites)

Persons 200% below

poverty

American Indians and

Alaska Natives

Children under age 5
 25

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 nonHispanic 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%
 26

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 PValue

Minority (all except non-Hispanic 

whites) 0.832528802 0.885798957 N/A N/A 0.003154776 -

84.476352 ~0

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
 27

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 nonHispanic 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-MantelHaenszel 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
 28

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

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 11-20% 21-30% 31-40% 41-50% 50-100%

Percent of Facilities

Percent of Population in Demographic

Minority (all except

non-Hispanic whites)

Persons 200% below

poverty

American Indians and

Alaska Natives

Children under age 5
 29

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 nonHispanic 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%
 30

Table 2-7 National Demographic Comparison Analysis of Statistical Significance for Damage Case Facilities

Demographic Group

Affected 

Population Ratio

Demographic 

Ratio 

Fisher 

Exact 

Test Pvalue

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 7.61E-05
 31

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 nonHispanic 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-MantelHaenszel 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
 32

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

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 11-20% 21-30% 31-40% 41-50% 51-100%

Percent of Facilities

Percent of Population in Demographic

Minority (all except nonHispanic whites)

Persons 200% below

poverty

American Indians and

Alaska Natives

Children under age 5
 33

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 nonHispanic 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%
 34

Table 2-11 National Demographic Comparison Analysis of Statistical Significance for Hazardous Waste Facilities

Demographic Group

Affected 

Populatio

n Ratio

Demograp

hic Ratio 

Fish

er 

Exac

t 

Test 

Pvalu

e

Equival

ent No. 

of 

Standar

d 

Deviatio

ns (SD)

Probabili

ty 

(Affected

)

Kendall 

Test 

Statistic

Kend

all 

Test 

PValue

Minority (all except nonHispanic whites)1.680615

321

1.4172884

25 ~0 N/A 0.121226233

1709.4322

97 ~0

Persons below 200% poverty

1.261363

882

1.1921192

76 ~0 N/A 0.121226233

731.38959

33 ~0

American Indians and Alaska 

Natives

0.729979

194

0.7067524

36 N/A N/A 0.121226233

-

209.43092

48

~0

Children under age 5

1.051925

362

1.0553574

77 ~0 N/A 0.121226233

83.804669

57 ~0
 35

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 nonHispanic 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-MantelHaenszel 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
 36

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

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

0-10% 11-20% 21-30% 31-40% 41-50% 50-100%

Percent of Facilities

Percent of Population in Demographic

Persons 200% below

poverty

American Indians and

Alaska Natives

Children under age 5
 37

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 nonHispanic 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%
 38

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

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 nonHispanic whites)

11 14 0 -0.82% -1.99%

Below 200% 

Poverty Level 11 14 0 -0.73% -1.75%

American 

Indians or 

Alaska Natives

8 17 0 -0.14% -0.21%

Children under 

age 5 13 12 0 -0.05% 0.06%
 39

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
40

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.
41

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
42

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. 

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

% Minority % Below 200

Poverty

% AIAN % Children Under

5

Percent of Facilities

PopulationDemographic

Commercial

Disposal and

Treatment

Facilities

Generator and

Transfer-Based

Exclusion Facilities
43

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 nonHispanic 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
44

Figure 2.1 Sensitivity Analysis for Notification Facilities Comparing Demographics within 1 km and 1 to 3 km 

Compared to National Demographics

0%

5%

10%

15%

20%

25%

30%

35%

40%

Minority Below 200%

Poverty

AIAN Children Under 5

Percentage of Population in Demographic

Population Demographic

Within 1 km Radiu

Around Notification

Facilities

Between 1 and 3 kms

Around Notification

Facilities

National
45

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 
46

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 
47

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/.
48

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. 
49

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 
50

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. Twentyseven 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.
51

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 μm)

Particulates 

(size < 2.5 μm)

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% 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
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 μm)

Particulates 

(size < 2.5 μm)

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% 1 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% 1 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% 1 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
53

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 μm)

Particulates 

(size < 2.5 μm)

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 EJView tool
54

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.
55

Community-Level Analysis of Potential Disproportionate Impacts 

of the DSW Exclusions to Minority and Low-Income Communities

Highlighted Values Indicate Potential Disproportionate Impact

National 

Comparison

% communities 

with higher 

minority 

representation

(average 

difference)

National 

Comparison

% communities 

with higher lowincome 

representation

(average 

difference)

State 

Comparison

% communities 

with higher 

minority 

representation

(average 

difference)

State

Comparison

% communities 

with higher lowincome 

representation

(average 

difference)

Notification 

Facilities

(60 total)

26.7%

(-11.84%)

51.7%

(1.17%)

48.3%

(0.23%)

68.3%

(5.25%)

Damage Case 

Facilities 

(250 total)

52.4%

(6.97%)

68.0%

(8.65%)

52.4%

(7.20%)

71.2%

(8.98%)

Hazardous 

Waste Facilities

(2,115 total)

46.8%

(1.37%)

59.7%

(4.17%)

53.5%

(5.07%)

60.4%

(4.37%)

Non-Hazardous 

Industrial Waste 

Facilities

(25 total)

36.0%

(-4.0%)

48.0%

(-0.08%)

44.0%

(-0.82%)

44.0%

(-0.73%)

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 lowincome) 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.
56

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

Demographic Ratio

National 

Comparison

Low-Income 

Population

Affected Population 

Ratio

Demographic Ratio

State 

Comparison

Minority 

Population

Affected Population 

Ratio

Demographic Ratio

State 

Comparison

Low-Income 

Population

Affected 

Population Ratio

Demographic 

Ratio

Notification 

Facilities

(60 total)

0.83

0.89

1.00

1.00

1.39

1.26

1.31

1.21

Damage 

Case 

Facilities 

(250 total)

2.45

1.64

1.60

1.36

2.28

1.49

1.76

1.46

Hazardous 

Waste 

Facilities

(2,115

total)

1.68

1.42

1.26

1.19

1.41

1.22

1.09

1.06

NonHazardous 

Industrial 

Waste 

Facilities

(25 total)

1.23

1.14

1.13

1.09

1.41

1.22

1.09

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 populationlevel 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 
57

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 lowincome 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 (AIAN) 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 nonhazardous 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 DecisionMaking 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. EPA 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
58

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.
59

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 Recycler 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). 
60

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.
61

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 generatorcontrolled 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.

A-1

Attachment A. Methodology for Identifying Potentially Recyclable 

Hazardous Wastes
A-2

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:

Form Code Form 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=0900006480728a11, last accessed 

on May 25, 2010.
A-3

 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 Code Source Code Description

G03 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:

Waste Code Waste Code Description

D005 Barium

D006 Cadmium

D007 Chromium

D008 Lead

D009 Mercury

D010 Selenium

D011 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-4

 If the waste is represented by one of the following waste form codes, it is 

assigned to this commodity group:

Form Code 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 Code Source Code 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:

Waste Code Waste Code 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:

Form Code Form 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:

Waste Code Waste Code Description

K088 Aluminum production spent potliners (sodium fluoride)
A-5

 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-6

(4) 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.

(5) 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 types—filters, solid adsorbents, and ion exchange, 

only spent carbon from these four waste types is evaluated.

(6) 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.
B-2

Attachment B. Statistical Calculations

Affected Population Ratio

The Affected Population Ratio is calculated as follows. 

There is a disparity if pr1/pr2 ≠ 1,

where 

pr1 = prob(within 3-km of facility | in demographic group)

pr2 = prob(within 3-km of facility | not in demographic group)

pr1/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 pvalue which is reported as “N/A” and in such cases the Kendall Test results can be used 

as a good approximation.
B-3

Kendall Test

The Kendall test is calculated as follows (Kendall and Stuart 1973, sec 33.22):

Std Error (pr1-pr2) = [q(1-q){n/(n-1)}{(1/H + 1/N)} ]1/2

SD = (pr1-pr2)/[ Std Error (pr1-pr2)]

= (pr1-pr2)/[ q(1-q){n/(n-1)}{(1/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 (pr1-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 = {∑ a(c + d) / n} / {∑ 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 = {∑ a(b + d) / n} / {∑ 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-4

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:

χ

2 = ∑ {a – (a+b)(a+c)/n}2

/ ∑ {(a+b)(a+c)(b+d)(c+d)/(n3 – n

2

)}

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 χ

2

.

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 χ2tests. 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.
C-1

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-2

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 

HMR 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-3

L

LDR Land Disposal Restrictions 

LQG Large quantity generator

N

NAAQS National Ambient Air Quality Standards

NAICS North American Industry Classification System

NATA National-Scale Air Toxics Assessment

NBR National Biennial Report

NESHAP

NPDES

National Emissions Standards for Hazardous Air Pollutants

National Pollutant Discharge Elimination System

NPL National Priorities List

NPM National Program Manager

NRC National Response Center

NRHM Non-Radioactive Hazardous Materials

NSPS New Source Performance Standards

O

OECA Office of Enforcement and Compliance

ORCR Office of Resource Conservation and Recovery

OSHA Occupational Safety and Health Administration

OSH Act Occupational Safety and Health Act

OSWER Office of Solid Waste and Emergency Response

P

PBE Petition-Based Exclusion

PC Priority Chemical

PERC Tetrachloroethylene
C-4

POTW Publicly Owned Treatment Works

ppm Parts per million 

ppmw Parts per million by weight

PR Population ratio

PSM Process Safety Management

R

RCRA Resource Conservation and Recovery Act

RCRAInfo Resource Conservation and Recovery Act Information

RIA Regulatory Impact Analysis

RMP Risk Management Plan

RQ Reportable Quantities 

S

SD Standard Deviation

SF Summary File

Site ID Site Identification

SOCMI Synthetic Organic Chemical Manufacturing Industry

SPCC Spill Prevention, Control, and Countermeasure

SQG Small quantity generators

T

TBE Transfer-Based Exclusion

TPY Tons per Year

APR Affected Population Ratio

TSDF Treatment, Storage, or Disposal Facility

U

U.S. United States
C-5

U.S. EPA United States Environmental Protection Agency

V

VOC Volatile Organic Compound

W

WR Waste Received from Offsite
D-1

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
D-2

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 Comprehensive federal law that regulates air emissions from stationary and mobile sources. 

Clean Water Act Establishes the basic structure for regulating discharges of pollutants into the waters of the United 

States and regulating quality standards for surface waters

Comprehensive 

Environmental Response, 

Compensation and 

Liability Act

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.

Comprehensive 

Environmental Response, 

Compensation and 

Liability Information 

System

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).

Conditionally Exempt 

Small Quantity Generator

Generate 100 kilograms or less per month of hazardous waste, or 1 kilogram or less per month of 

acutely hazardous waste

D

D001 Ignitable waste

D007 Chromium waste

D008 Lead waste 
D-3

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 Facilities that highlighted in EPA’s An Assessment of Environmental Problems Associated with 

Recycling of Hazardous Secondary Materials

Definition of Solid Waste 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.

Definition of Solid Waste 

Rule

The DSW rule creates specific conditions for recycling hazardous secondary materials under the 

Resource Conservation and Recovery Act (RCRA).

Definition of Solid Waste 

Final Rule (2008)

Revision of the Definition of Solid Waste under RCRA for certain types of hazardous secondary 

materials being recycled

Disproportionate Impact 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 Toolkit for Assessing Potential Allegations of Environmental Justices

Emergency Planning and 

Community Right-to-Know 

Act

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-4

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. 

F

F003 Spent non-halogenated solvents

F005 Spent non-halogenated solvents

F006 Wastewater treatment sludges

F037 Petroleum refinery primary sludges 

F1_5 Mixture of F001-F005

Facility Registry System FRS is a centrally managed database that identifies facilities, sites or places subject to 

environmental regulations or of environmental interest.

G

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-5

Hazard Communication 

Standard

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

Hazardous Air Pollutant 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.

Hazardous Materials 

Regulations

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.

Hazardous Materials 

Transportation Act

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.

Hazardous Secondary 

Materials

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.

Hazardous Waste Facilities 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

Hazardous Waste 

Operations and Emergency 

Response

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-6

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 

Quality Standards

Standards established by EPA under authority of the Clean Air Act (42 U.S.C. 7401 et seq.) that 

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-7

National Emissions 

Standards for Hazardous 

Air Pollutants

NESHAPS are stationary source standards for hazardous air pollutants.

National Priorities List 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.

National Response Center 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.

National-Scale Air Toxics 

Assessment

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.

New Source Performance 

Standards

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.

Non-hazardous Industrial 

Waste Facilities

Facilities not currently generating or managing hazardous wastes that may choose to begin 

reclaiming hazardous secondary materials under the 2008 DSW Final Rule

North American Industry 

Classification System

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.

Notification Facility Facility that has notified EPA that it will be managing hazardous secondary materials under the 

2008 DSW Final Rule
D-8

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.

P

Petition-Based Exclusion Materials that EPA or an authorized state determines to be non-wastes through a case-by-case 

petition process.

Process Safety 

Management

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

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.

Resource Conservation and 

Recovery Act Information

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.

Risk Management Plan 

(RMP)

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-9

Rural All territory, population, and housing units located outside of urbanized areas and urban clusters.

S

Spill Prevention, Control, 

and Countermeasure Plan 

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.

Small Quantity Generator SQG generate more than 100 kilograms, but less than 1,000 kilograms, of hazardous waste per 

month.

T

Transfer-Based Exclusion Materials that are generated and legitimately reclaimed under the control of the generator

U

Urban For Census 2010, all territory, population, and housing units in urbanized areas and urban clusters.

Urban Cluster A densely settled area that has a census population of 2,500 to 49,999.

Urbanized Area A densely settled area that has a census population of at least 50,000.

V

Volatile Organic 

Compound

VOCs are organic chemical compounds whose composition makes it possible for them to evaporate 

under normal indoor atmospheric conditions of temperature and pressure.
D-1

Attachment E. National and State Urban and Rural Analyses
D-1

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 PValue

Minority (all except non-Hispanic 

whites) 0.70821708 0.807716274 N/A N/A 0.003719767 -150.944 ~0

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 PValue

Minority (all except non-Hispanic 

whites) 0.91244904 0.927625227 1.84974E37 12.79062768 0.001609112 -

12.674748

8.16203E37

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
D-2

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 nonHispanic 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-3

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 nonHispanic 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 Pvalue

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-4

Table 6-6 State Rural Demographic Comparison Analysis of Statistical Significance for Notification Facilities

Demographic Group

Affected 

Population Ratio Demographic Ratio 

Cochran-Mantel-Haenszel Pvalue

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 1.175146591 1.2868E-52

1.883920185 1.760132319 ~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)

Ke

Minority (all except non-Hispanic whites) 1.440430372 1.33172518 ~0 N/A 0.003484304 8

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 1
D-5

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 nonHispanic 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-6

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 nonHispanic 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 Pvalue

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-7

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 Pvalue

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 Pvalue

Equivalent No. 

of Standard 

Deviations (SD)

Probability 

(Affected)

Kenda

Stat

Minority (all except non-Hispanic whites) 1.340072517 1.210475806 ~0 N/A 0.159826638 96

Persons below poverty 1.25425977 1.196325972 ~0 N/A 0.159826638 71

American Indians and Alaska Natives 0.915856581 0.90243699 N/A N/A 0.159826638 -58

Children under age 5 1.023988452 1.026680122 ~0 N/A 0.159826638 39
D-8

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 nonHispanic 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-9

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 nonHispanic 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 Pvalue

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-10

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 Pvalue

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 PValue

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-11

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 nonHispanic 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-12

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 nonHispanic 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 Pvalue

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-13

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 Pvalue

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-14

Commercial Hazardous Waste Facilities That Do Not Recycle

Figure 6.1 Demographics for Commercial Hazardous Waste Facilities That Do Not Recycle

Table 6-25 National Demographic Comparison for Commercial Hazardous Waste Facilities That Do Not Recycle 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 11-20% 21-30% 31-40% 41-50% 50-100%

Percent of Facilities

Percent of Population in Demographic

Minority (all except

non-Hispanic

whites)

Persons 200%

below poverty

American Indians

and Alaska Natives
D-15

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 nonHispanic 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-16

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 nonHispanic 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-17

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 nonHispanic 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-18

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 nonHispanic 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 PValue

Minority (all except non-Hispanic 

whites) 2.646397133 1.683429372 ~0 N/A 0.020955069 1272.548665 ~0

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-19

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 PValue

Minority (all except non-Hispanic 

whites) 2.127700864 1.457330272 ~0 N/A 0.027738431 955.6563884 ~0

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 

Pvalue

Equivalent 

No. of 

Standard 

Deviations 

(SD)

Probability 

(Affected)

Kendall 

Test 

Statistic

Kendall 

Test PValue

Minority (all except non-Hispanic 

whites) 1.371313481 1.282623826 ~0 N/A 0.002397605 60.34486091 ~0

Persons below poverty 1.082731832 1.056017756 5.25E61 16.47837569 0.002397605 16.56119631 1.33E-61

American Indians and Alaska 

Natives 0.572912851 0.577830077 9.54E207 30.6832035 0.002397605 -

28.30777462 2.77E-176

Children under age 5 1.092753255 1.08680898 2.60E22 9.715069113 0.002397605 9.836315749 7.85E-23
D-20

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 Pvalue

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 Pvalue

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 3.31E-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 Pvalue

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