Attention Environmental Justice Mapping,
Assessment, and Protection (EJMAP) Users: The
following document discusses the data sources
and methodologies used to calculate each
stressor value in EJMAP prior to the January 31,
2024, data update, as well as general
descriptions of each stressor and the scientific
rationale for their inclusion in the baseline
analysis. While the calculation methodologies
are similar, if not identical, for each iteration of
EJMAP, users should refer to the EJMAP Data
Documentation page to identify the proper data
and methodology documentation for each
iteration.
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Contents
Introduction .......................................................................................................................... 4
Background ........................................................................................................................... 4
Methodology Development ................................................................................................... 6
EJ Screen ............................................................................................................................................. 6
CalEnviroScreen .................................................................................................................................. 8
New Jersey’s Method ....................................................................................................................... 10
Stressors: Descriptions & Analysis........................................................................................ 15
Concentrated areas of air pollution .................................................................................................. 16
Ground-Level Ozone.................................................................................................................................... 16
Fine Particulate Matter (PM
2.5
) ................................................................................................................... 17
Cancer Risk from Diesel Particulate Matter ................................................................................................. 19
Cancer Risk from Air Toxics Excluding Diesel Particulate Matter................................................................. 22
Non-Cancer Risk from Air Toxics ................................................................................................................. 23
Mobile sources of air pollution ......................................................................................................... 26
Traffic – Cars and Light- and Medium-Duty Trucks ..................................................................................... 26
Traffic – Heavy-Duty Trucks ......................................................................................................................... 27
Railways ....................................................................................................................................................... 29
Contaminated Sites ........................................................................................................................... 32
Known Contaminated Sites ......................................................................................................................... 32
Soil Contamination Deed Restrictions ......................................................................................................... 34
Groundwater Classification Exception Area/Currently Known Extent Restrictions ..................................... 35
Transfer stations or other solid waste, recycling, and scrap metal facilities............................................. 36
Solid Waste Facilities ................................................................................................................................... 36
Scrap Metal Facilities ................................................................................................................................... 37
Point-sources of water pollution ...................................................................................................... 40
Surface Water ............................................................................................................................................. 40
Combined Sewer Overflows ........................................................................................................................ 42
May cause potential public health impacts ...................................................................................... 44
Drinking Water ............................................................................................................................................ 44
Potential Lead Exposure .............................................................................................................................. 46
Lack of Recreational Open Space ................................................................................................................ 47
Lack of Tree Canopy .................................................................................................................................... 49
Impervious Surface ...................................................................................................................................... 50
Flooding (Urban Land Cover) ....................................................................................................................... 52
Unemployment ........................................................................................................................................... 58
Education .................................................................................................................................................... 59
Appendix A: Air Quality Monitoring Coordinates.................................................................. 61
Appendix B: Glossary of Terms ............................................................................................ 63
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Acronyms
AADT: Average Annual Daily Traffic
ABG: A
djacent Block Group
ACS: American Community Survey
ALE: Action Level Exceedances
AQI: Air Quality Index
BMP: Best Management Practices
CSO: Combined Sewer Overflow
CST: Combined Stressor Total
EJ: Environmental Justice
EJMAP: Environmental Justice Mapping
Assessment and Protection Tool
EPA: Environmental Protection Agency
FHWA: Federal Highway Administration
GPC: Geographic Point of Comparison
GIS: Geographic Information Systems
HAP: Hazardous Air Pollutants
HPMS: Highway Performance Monitoring
System
IDW: Inverse Distance Weighting
IEC: Immediate Environmental Concern
KCS: Known Contaminated Sites
KCSL: Known Contaminated Sites List
MCL: Maximum Contaminant Level
NAAQS: National Air Quality Standard
NEI: National Emission Inventory
NJDEP: New Jersey Department of
Environmental Protection
NJEMS: New Jersey Environmental
Management System
NJPDES: New Jersey Pollutant Discharge
Elimination System
NO
x
: Nitrogen Oxides
OBC: Overburdened Community
PAH: polyaromatic hydrocarbons
PCB: polychlorinated biphenyls
PM
2.5
: Particulate Matter 2.5
PI: Preferential ID (AKA Program ID)
PWTA: Private Well Testing Act
RAP: Remedial Action Permit
RfC: Reference Concentration
SDOH: Social Determinants of Health
TT: Treatment Techniques
VOC: Volatile organic Compounds
4 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Introduction
On September 18, 2020, Governor Phil Murphy signed New Jersey's Environmental Justice Law (N.J.S.A.
13:1D-157). This groundbreaking new law (hereafter referred to as the Act) requires the New Jersey
Department of Environmental Protection (Department) to adopt rules and regulations to implement the
provisions of the Act. On April 3, 2023, the Department formally adopted these promulgating regulations in
the New Jersey Register (Adopted Environmental Justice Rules). These rules establish a process for assessing
relevant environmental and public health stressors affecting overburdened communities (OBCs) and adjacent
block groups (ABGs), and to deny or condition permits where facilities cannot avoid the occurrence of
disproportionate environment or public health stressors in those areas.
Simultaneous with the formal rule proposal in June 2022, the Department released a beta version of the
Environmental Justice Mapping, Assessment, and Protection (EJMAP) tool and its companion technical
guidance document on the Department’s website. EJMAP establishes an objective, publicly available
representation of the existing environmental and public health stressors in the State’s OBCs and supports the
analysis required under the Environmental Justice Rules.
S
pecifically, EJMAP enables users to:
• Id
entify OBCs and ABGs throughout the State and determine the reason(s) (i.e., minority status,
poverty, English proficiency or some combination of those factors) for those designations;
• Search by address to determine whether a specific facility is located or proposed to be located in an
OBC or ABG;
• Examine the presence of existing environmental and public health stressors in an OBC or ABG
;
• Compare the existing environmental and public health stressors in an OBC or ABG to their
appropriate geographic point of comparison and determine which, if any, stressors are considered
adverse; and
• Determine whether an OBC or ABG is subject to adverse cumulative stressors.
A final version of EJMAP released simultaneous with the rule adoption encompasses changes to
methodologies received during the beta release, and incorporates any updated data released during the beta
phase. This final technical guidance describes the current methodologies and data sets in final EJMAP.
Background
According to the Act, OBCs are block groups with:
1. At least 35 percent low-income households; or
2. At least 40 percent of the residents identify as minority or as members of a State recognized tribal
community; or
3. At least 40 percent of the households have limited English proficiency.
Census block groups with zero population and located immediately adjacent to an OBC are labeled as
“adjacent.” Existing or proposed facilities located in ABGs may be required to conduct further analysis in
accordance with the Environmental Justice Rules.
A census block group needs to meet only one of the three demographic criteria to be designated as an OBC.
The Department previously released mapping and a list of OBCs and notified municipalities that had areas
designated as OBCs. The Department updated this mapping and list to show designations based on 2021
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Census data and will continue to update and maintain the maps and lists at least once every two years. The
OBC mapping is the first tab in EJMAP.
Regulated facilities, as defined in the Environmental Justice Rules, seeking new permits or permit renewals in
OBCs or ABGs must analyze their existing and potential contributions to environmental and public health
stressors.
“Environmental or public health stressors” are sources of environmental pollution, including, but not limited to:
1. concentrated areas of air pollution,
2. mobile sources of air pollution,
3. contaminated sites,
4. transfer stations or other solid waste facilities, recycling facilities, scrap metal facilities, and point
sources of water pollution including, but not limited to, water pollution from facilities or combined
sewer overflows; or
5. conditions that may cause potential public health impacts, including, but not limited to
asthma, cancer, elevated blood lead levels, cardiovascular disease, and developmental problems in
the overburdened community.
For more information on the definitions of “facility” and “permit,” see Adopted Environmental Justice Rules.
Implementation of the Environmental Justice Rules requires consideration of whether and how any “facility”
seeking a new NJDEP “permit” or “permit renewal” in an OBC or ABG will contribute to these environmental
or public health stressors in a manner that results in a disproportionate impact when compared to the area’s
geographic point of comparison.
This comparative analysis considers:
• The existing environmental and public health stressors values in an OBC or ABG
1
,
• Whether the value of an environmental or public health stressor in an OBC or ABG is higher than its
geographic point of comparison (i.e., adversely impacted),
• Whether the total number of adverse environmental and public health stressors in an OBC or ABG is
higher than its geographic point of comparison, i.e., subject to adverse cumulative stressors, and
• How and whether a facility will contribute to environmental and public health stressors in the OBC or
ABG.
To facilitate this comparative analysis, the Department 1) identified justifiable and quantifiable
environmental and public health stressors, 2) designated the appropriate geographic points of comparison,
and 3) developed a methodology for determining whether an OBC or ABG is currently subject to adverse
cumulative stressors.
1
As discussed later in this document, the Department utilizes the values from the greatest stressed OBC (e.g., the
one with the highest Combined Stressor Total) that borders a respective ABGABG to determine if the ABG is
adversely impacted.
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Methodology Development
In developing its comparison methodology for evaluating stressors, the Department first reviewed existing
methodologies to inform its approach. U.S. Environmental Protection Agency’s (EPA; Agency) EJScreen and
California’s CalEnviroScreen are the two best-known environmental justice evaluation tools available in the
US, and as such, formed the foundation of the Department’s research efforts for establishing its own method
of comparison.
EJ Screen
The EPA developed EJScreen to better meet the Agency’s responsibilities to protect public health and the
environment and provide a nationally consistent environmental justice screening and mapping tool.
Combining environmental and demographic indicators, EJScreen highlights which geographic areas are
candidates for further review, analysis, or outreach by the EPA. Specifically, EJScreen uses environmental
indicators as proxy estimates of risk, pollution levels, or potential exposure, and demographic indicators as
proxies for community health status and potential susceptibility to pollution. EPA characterizes EJScreen as a
pre-decisional screening tool not designed for decision-making or determinations regarding the existence or
absence of EJ concerns.
EJScreen contains 11 environmental and six demographic indicators. The tool’s basic level of geographic
resolution is the census block group. Environmental indicators were selected for inclusion in the tool based
on the following characteristics: available data for the entire U.S. at the block group level; relevance to
environmental justice; and public health significance.
Figure 1 presents the environmental indicators included in EJScreen. The demographic indicators in EJScreen
flow from Executive Order 12898
, which specifically indicates low-income and minority populations as two
core factors representing the “social vulnerability characteristics of a disadvantaged population.” Based on a
review of other relevant factors, EJScreen also includes less than a high school education, linguistic isolation,
individuals under the age of five, and individuals over the age of 64 as demographic indicators.
EJScreen calculates two indexes from the available indicators: a demographic index and an EJ index. The
demographic index is the average of the percent minority and percent low-income in the block group and is
designed to address the potential overlap or synergy between these two indicators. Since percent minority
and percent low-income are two social determinants of health that are strongly correlated, it is difficult to
assess the individual impacts from each or the amount of symbiosis between them.
The EJ index is a combination of environmental and demographic information designed to consider the
extent to which the local demographics are above the national average. Specifically, the EJ index looks at the
difference between the demographic composition of the block group, as measured by the demographic
index, and the national average (which is approximately 35 percent). It also considers the population of the
block group.
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Figure 1: EJScreen Environmental Indicators
Indicator
Place on
Exposure–
Risk
Continuum
Key
Medium
AirToxScreen Air Toxics Cancer Risk
Lifetime inhalation cancer risk
Risk/
Hazard
Air
AirToxScreen Respiratory Hazard Index
Ratio of exposure concentration to RfC
AirToxscreen Diesel PM (DPM)
(µg/m
3
)
Potential
Exposure
Particulate Matter (PM
2.5
)
Annual average (µg/m
3
)
Ozone
Summer seasonal average of daily maximum 8-hour concentration in air (ppb)
Lead Paint
Percentage of housing units built before 1960
Dust/Lead
Paint
Traffic Proximity and Volume
Count of vehicles (average annual daily traffic) at major roads within 500 meters (or
nearest neighbor outside 500 meters), divided by distance in kilometers (km)
Proximity/
Quantity
Air/Other
Proximity to RMP Sites
Count of facilities within 5 km (or nearest neighbor outside 5 km), divided by
distance
Waste/
Water/Air
Proximity to TSDFs
Count of major TSDFs within 5 km (or nearest neighbor outside 5 km), divided by
distance
Proximity to NPL Sites
Count of proposed and listed NPL sites within 5 km (or nearest neighbor outside 5
km), divided by distance. Count excludes deleted sites.
Wastewater Discharge
Toxicity weighted stream concentrations divided by distance in kilometers (km)
Water
Abbreviations:
AirToxScreen The Air Toxics Screening Assessment
NPL National Priorities List, Superfund Program Risk Management Plan (RMP)
TSDFs Hazardous Waste Treatment, Storage, and Disposal Facilities
RfC Reference concentration from EPA’s Integrated Risk Information System
PM
2.5
Particulate matter (PM) composed of particles smaller than 2.5 microns
µg/m
3
Micrograms of PM
2.5
per cubic meter of air
ppb Parts per billion of ozone in air
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
CalEnviroScreen
California’s Office of Environmental Health Hazard Assessment developed and maintains the CalEnviroScreen
tool on behalf of the California Environmental Protection Agency. The tool analyzes the cumulative effects of
pollution burden and additional socioeconomic and health factors to identify which communities might need
policy, investment, or programmatic interventions.
CalEnviroScreen applies a place-based geographic framework for assessing cumulative impacts categorized
into four “bins” – two representing pollution burden (exposures and environmental effects) and two
representing population characteristics (sensitive populations and socioeconomic factors). Twenty-one (21)
statewide indicators are sorted into these bins and “scored” for a given geographic area using percentiles.
These “scores” are averaged by bin, and then a combined score is calculated for a given area in a way that
uses the population characteristics as a modifier of the pollution burden. The tool’s basic level of geographic
resolution is the census tract. Figure 2, below, highlights the 21 indicators and how they are categorized in
CalEnviroScreen. Figure 3 provides an example of how the final combined score is calculated.
Figure 2: CalEnviroScreen Indicators
Pollution Burden
Population Characteristics
Exposures
• Ozone concentrations
• PM
2.5
concentrations
• Diesel PM emissions
• Drinking water contaminants
• Children’s lead risk from housing pesticide use
• Toxic releases from facilities
•
Traffic impacts
Sensitive populations
• Asthma emergency department visits
• Cardiovascular disease (Emergency department
visits for heart attacks)
• Low birth-weight infants
Environmental effects
• Cleanup sites
• Groundwater threats
• Hazardous waste
• Impaired water bodies
•
Solid waste sites and facilities
Socioeconomic factors
• Educational attainment
• Housing-burdened low-income households
• Linguistic isolation
• Poverty
•
Unemployment
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Figure 3: CalEnviroScreen Combined Score Calculations – An Example Census Tract Calculation
Pollution Burden
Population Characteristics
Exposure
Indicators
Environmental
Effects Indicators*
Sensitive
Population
Indicators
Socioeconomic
Factor Indicators
Component
Score
79.67
(0.5 × 45.95)
=22.98
96.51 79.78
Average of
Component
Score
102.65 ÷ (1 + 0.5) =
68.43
Pollution Burden is calculated as the
average of its two component scores,
with the Environmental Effects component
half-weighted.
176.29 ÷ 2 =
88.15
Population Characteristics is calculated
as the average of its two component
scores.
Scaled
Component
Scores (Range
0-10)
(68.43 ÷ 81.9
**
) × 10 =
8.36
The Pollution Burden percentile is scaled
by the statewide maximum Pollution
Burden scores.
(88.15 ÷ 96.4
***
) × 10 =
9.14
The Population Characteristics percentile
is scaled by the statewide maximum
Population Characteristics scores.
CalEnviroScreen
Score
8.36 x 9.14 = 76.4
A score of 76.4 puts this census tract in the 95-100 percentile or
top 5% of all CalEnviroScreen scores statewide.
* The Environmental Effects component was given half the weight of the Exposures component.
** The tract with the highest Pollution Burden score in the state had a value of 81.9.
*** The tract with the highest Population Characteristics score in the state had a value of 96.4.
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New Jersey Department of Environmental Protection
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New Jersey’s Method
The Department looked at three broad areas in developing its own baseline comparison method:
1. Identification of Core Environmental and Social Stressors:
The Department established the following guidelines for stressor inclusion in its baseline environmental and
public health comparative impact analysis:
• At least one core stressor in each of the legislatively mandated categories of concern (i.e.,
concentrated source of air pollution; mobile sources of air pollution, point sources of water
pollution; solid waste facilities and scrap metal facilities; contaminated sites; and other
environmental or social stressors that may cause public health issues).
• The quantifiability of the stressor.
• The availability of robust, quality, statewide, public data meaningful at the block group geographic
scale.
• The value of the stressor in terms of adequately representing the environmental or public health
concerns of distressed communities.
• Consistency with stressors chosen for use by either California or EPA for their tools (although the
data and methodologies used for determining these stressors varied).
The Department initially developed a brainstorming list of more than 60 potential stressors from various
sources, including past NJ Environmental Justice initiatives, the California and EPA Environmental Justice
tools, and input from program staff and stakeholders. Applying the guidelines above, this list was reduced to
approximately 30 indicators for a more in-depth review, with the stated goal of minimizing the number of
stressors necessary to accurately assess the environmental and public health conditions in an OBC. Upon
completion of this analysis, twenty-six (26) stressors were incorporated into New Jersey’s method. Table 1
below lists each of the 26 stressors. The next section of this document discusses each stressor in greater
detail.
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Table1: New Jersey’s Twenty-Six (26) Environmental and Public Health Stressors
Concentrated areas of air pollution (5 stressors)
Ground-Level Ozone
Fine Particulate Matter
Cancer Risk from Diesel Particulate Matter
Cancer Risk from Air Toxics Excluding Diesel Particulate Matter
Non-Cancer Risk from Air Toxics
Mobile Sources of Air Pollution (3 stressors)
Traffic– Cars, Light- and Medium-Duty Trucks
Traffic – Heavy-Duty Trucks
Railways
Contaminated Sites (3 Stressors)
Known Contaminated Sites
Soil Contamination Deed Restrictions
Ground Water Classification Exception Areas/Currently Known Extent Restrictions
Transfer Stations or other Solid Waste Facilities, Recycling Facilities, Scrap Metal Facilities (2 stressors)
Solid Waste Facilities
Scrap Metal Facilities
Point Sources of Water Pollution (2 stressors)
Surface Water
Combined Sewer Overflows
May Cause Potential Public Health Impacts (6 stressors)
Drinking Water
Potential Lead Exposure
Lack of Recreational Open Space
Lack of Tree Canopy
Impervious Surface
Flooding (Urban Land Cover)
Proximity Stressors (3 stressors)
Emergency Planning Sites
Permitted Air Sites
NJPDES Sites
Social Determinants of Health (2 stressors)
Unemployment
Education
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EJMAP: Technical Guidance April 12, 2023
2. Determination of the geographic point(s) of comparison
The Act required the Department to determine the appropriate geographic point of comparison (GPC) for the
OBC comparative analysis. While California uses a statewide geographic unit, the EPA provides several
different geographic units (nation, state, region) for users to consider. After contemplating different
geographic units and discussing their pros and cons with stakeholders, the Department ultimately agreed
with the EPA’s premise that a “one-size-fits-all” approach to geographic comparison would not provide
equitable protection in a state as diverse as New Jersey.
Instead, New Jersey compares the OBC, or an ABG’s greatest stressed OBC neighbor, to both the State and
relevant county non-OBC 50
th
percentile levels for each environmental and public health stressor, relying on
whichever is most protective (e.g., lower) in each instance to establish the basis of comparison. For these
calculations, the non-OBC median values for all counties and the State includes identified adjacent block
groups. The inclusion of these areas in the non-OBC median totals aligns with the Department’s rules which
state that ABGs are not de facto OBCs, but instead areas of concern given their proximity to other OBCs and
the inability to complete an accurate demographic assessment without population data, and as such may be
subjected to the EJ rule requirements. The Department determined that OBC comparison to aggregate non-
OBC totals was the most protective comparison, since it does not dilute the standard by including other areas
in the State or county values that are already impacted by social determinants of health such as income and
minority status.
3. Development of a comparison methodology to determine adverse cumulative stressors when
compared to the geographic point(s) of comparison.
New Jersey devised a two-step comparison approach to determine if an area’s environmental and public
health stressors are “higher than” it’s GPC.
First, individual stressor values were determined for every block group in the State. Next, the non-OBC block
groups (including ABGs) were separated out and sorted by county and by State to determine the 50
th
percentile (e.g., the median or middle value when a data set is ordered from least to greatest) non-OBC
values for each stressor. For example, for the stressor “ground-level ozone”, the NJDEP first determined the
50
th
percentile for the ozone values for the non-OBC portions of the State and each county. The GPC is the
lower (e.g., most protective) of the non-OBC State or relevant county values. The individual OBC stressor
value is then compared to the GPC to determine if that individual stressor is “adverse” for that OBC. If the
OBC stressor is higher than the lower non-OBC State or relevant county value, it is considered “adversely
stressed”. For each stressor for each OBC, that determination is either yes (=1) or no (=0). The number of
adverse stressors is then counted to determine the combined stressor total (CST) for that OBC.
Step 2 repeats this process for the CST. First, the CST is calculated for all block groups in the State. For ABGs,
individual stressor values were calculated. However, since an ABG has zero-population, the stressor values
that rely on population data (for example, the two social determinants of health stressors) will report a null
value. This means that those CSTs would potentially underreport the number of stressors that were
comparatively “higher than” their GPC. To address this, ABG CSTs use the values from their greatest stressed
OBC neighbor (i.e., the OBC with the highest CST value that shares a border with the ABG) for calculation
purposes. Next, the non-OBC and ABGs are selected and sorted to determine the non-OBC State and county
CST values. This results in the median, or middle value, of the total “yes” responses (counts with a maximum
of 26 if all stressors are “yes”) for the non-OBC portion of the State and each county. The GPC is the lower
(e.g., most protective) of the non-OBC State or relevant county values. If an OBC block group CST value is
higher than the GPC, that OBC is subject to adverse cumulative stressors. Table 2 below shows each county
non-OBC CST as compared with the State non-OBC CST and includes a final column that indicates which
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EJMAP: Technical Guidance April 12, 2023
would be the GPC in each case for block groups in that county. The EJMAP tool includes layers that show
OBCs only to identify which are subject to adverse cumulative stressors, as well as a second layer that shows
the CST for all block groups in the State.
As noted previously, New Jersey’s EJ Law defines OBCs at the block group level, a statistical division of a
census tract. A block group consists of clusters of census blocks with the same first digit in their four-digit
census block number. The smallest division of U.S. Census data that provides basic demographic data, the
block group provides a more nuanced localized view than a municipality, county, or tribal area could. The
2021 block groups and tribal areas available from the U.S. Census Bureau were used for EJMAP calculations
except for those along the eastern coast of the state and within Ocean County that had no (zero) land area
(census field “ALAND”). These block groups are wholly comprised of water (Atlantic Ocean or Ocean County
lakes/bays) and were only included by the Census Bureau to fill space in a geospatial context. However,
without land, these block groups added no value to the individual stressor or CST calculations and were
removed from totals.
Where non-OBCs intersect with tribal areas, the Department denoted that the tribal areas were considered a
block group for NJ’s limited tribal areas. Block groups and tribal areas are not always wholly encompassed by
the geographic boundaries of a municipality, and in some cases, are split between more than one
municipality. Tribal areas may also be split between more than one county. For calculation purposes,
municipally split block groups are treated as a single entity. While EJMAP displays these splits, the underlying
values are identical between each section of the municipally split block group. For the Ramapough
designated tribal land along New Jersey’s northeastern border with New York, individual stressor values for
adverse comparisons are calculated based on the stressors within the actual county split between Passaic
and Bergen counties. The split tribal land was treated as separate block groups for consistency as each block
group is subject to a county GPC to determine if it is subject to adverse cumulative stressors. Treating the
tribal land as one block group and comparing it with two different county GPCs for each stressor would be
inconsistent with the analysis completed for other block groups. Additionally, communicating which county
value was utilized for each stressor’s GPC would add unnecessary complexity to the calculations.
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Table 2: CST Geographic Points of Comparison by County
County
County Non-OBC
50
th
Percentile
State Non-OBC 50
th
Percentile
Geographic Point
Comparison
Atlantic
11
13
11
Bergen
15
13
13
Burlington
13
13
13
Camden
14
13
13
Cape may
12
13
12
Cumberland
12
13
12
Essex
14
13
13
Gloucester
11
13
11
Hudson
17
13
13
Hunterdon
11
13
11
Mercer
13
13
13
Middlesex
14
13
13
Monmouth
12
13
12
Morris
13
13
13
Ocean
11
13
11
Passaic
14
13
13
Salem
12
13
12
Somerset
11
13
11
Sussex
10.5
13
10.5
Union
14
13
13
Warren
12
13
12
Using the table above, if an OBC in Ocean County has a combined stressor total of 11 or higher, it would be
considered subject to adverse cumulative stressors, since its CST exceeds the most protective GPC of 10. Had
that OBC’s combined stressor total been 9, it would not be considered subject to adverse cumulative
stressors.
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EJMAP: Technical Guidance April 12, 2023
Stressors: Descriptions & Analysis
The following section discusses in detail each stressor included in the comparative analysis. The stressors are
grouped into the broader related categories outlined by the Act (e.g., concentrated areas of air pollution,
mobile sources of air pollution, etc.) and each individual stressor discussion includes:
• a general description of the stressor,
• the specific indicator and measurement unit(s),
• the scientific rationale for including the stressor in the baseline analysis, and
• discussion of the publicly available data source(s) relied on to quantify the indicator and the method
the used to calculate the stressor values.
Stressor values are standardized to three decimal places for calculation and display purposes.
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Concentrated areas of air pollution
The Act specifically discusses the detrimental environmental and health impacts from the “numerous
industrial, commercial and governmental facilities” located in low-income communities and communities of
color. These facilities, despite being subject to permit and approval conditions intended to control and
minimize emissions, still produce air pollutants that can cause or contribute to environmental and health
impacts in surrounding communities. These pollutants include precursors to the formation of ground-level
ozone (i.e., volatile organic compounds (VOCs) and nitrogen oxides (NO
x
)), fine particulate matter (PM
2.5
),
and other pollutants that have carcinogenic and other serious health impacts.
Ground-Level Ozone
Description
In the upper atmosphere, stratospheric ozone provides protection against the sun’s ultraviolet rays. In
contrast to ozone in the upper atmosphere, tropospheric ozone at ground level is harmful to public health.
Ground-level ozone is the only National Ambient Air Quality Standard (NAAQS) that the two multi-state
nonattainment areas inclusive of New Jersey are yet to attain. Ground-level ozone forms when VOCs and NO
x
react in the presence of sunlight. Ground-level ozone is an irritant that causes swelling in the lungs’
passageways making it harder to breathe. This irritation can also damage lung tissue making them more
vulnerable to lung-related illness such as bronchitis and asthma.
Of the six NAAQS, ozone and particulate matter pose the most widespread and significant health threats.
New Jersey maintains a network of monitoring stations
that provide data to better understand exposures to
ground-level ozone and other air pollutants across the state. Ground-level ozone is measured at 16
monitoring stations throughout New Jersey, 10 of which operate year-round and six that operate only during
the ozone season (May through October). There is also a monitor in Washington Crossing State Park in
Mercer County that is maintained and operated by the EPA.
Indicator and Measurement Unit(s)
The Department utilized the 3-year (2019 to 2021) average of the Air Quality Index (AQI) days greater than
100 for ozone. The AQI is a system for communicating daily air quality to the public and warning them when
air pollutant levels in their area are unhealthy. It is easiest to visualize the AQI as a yardstick that runs from 0
to 500; the higher the AQI daily value, the greater the concern. AQI values correspond to a NAAQS for a
particular pollutant, with AQI values below 100 considered safe.
Rationale
Ground-level ozone can irritate the entire respiratory tract. Repeated exposure to ozone pollution may cause
permanent damage to the lungs. Even when ozone is present at low levels, inhaling it can trigger a variety of
health problems including chest pains, coughing, nausea, throat irritation, and congestion. Ozone also can
aggravate other medical conditions such as bronchitis, heart disease, emphysema, and asthma, and can
reduce lung capacity.
2
Anyone who spends time outdoors in the summer can be affected by ozone, as studies show that even
healthy adults can have trouble breathing when exposed. However, people with pre-existing respiratory
ailments are especially prone to the effects of ozone. For example, asthmatics affected by ozone may have
more frequent or severe attacks during periods when ozone levels are high. Children are particularly at risk
for ozone-related problems since they breathe more air per pound of body weight than adults, and ozone can
affect the development of their immature respiratory systems. Also, children tend to be active outdoors
during the summer when ozone levels are at their highest. These additional impacts are particularly
2
New Jersey Department of Environmental Protection (2021), 2020 New Jersey Air Quality Report, see
https://www.state.nj.us/dep/airmon/pdf/2020-nj-aq-report.pdf
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concerning in Environmental Justice areas that already experience a higher-than-average share of at-risk
communities. During 2016, asthma affected 15.7 percent of African American children and 12.9 percent of
children of Puerto Rican descent, while it affected only 7.1 percent of white children.
3
African
American children were burdened by 138,000 asthma attacks and 101,000 lost school days each year.
S
tressor Value Calculation Method
• Obtained daily ozone monitoring results for all New Jersey air monitoring sites as well as nearby
monitors in Connecticut, Delaware, Pennsylvania, and New York from the EPA'
s Daily Summary Data
Site for the years 2019 to 2021. See Appendix A of this document for the coordinates of all the air
quality monitors used in this analysis.
• C
reated separate GIS files from the monitoring sites’ latitude and longitude data for each applicable
year.
• Applied ArcGIS’ Inverse Distance Weighting (IDW) interpolation tool t
o each year’s monitoring results
to estimate daily grid level concentrations of ozone in parts per million (ppm). The IDW interpolation
tool determines cell values using a linearly weighted combination of a set of sample points. The
weight is a function of inverse distance. The surface being interpolated is the locationally dependent
variable (e.g., the monitor locations). The following specific parameters were used:
o G
rid cell size of 0.05 degrees
o Power: of 5
o Search Radius: Variable 10
• Summarized the daily results for each grid to determine the number of days the estimated
concentration was above the Air Quality Index (AQI) level of 100 (which equals 0.070 ppm for ozone
(averaged over 8-hours)), and then averaged those summarized results to create one 3-year value for
each grid.
• D
ownloaded the 2021 NJ block groups and applicable tribal areas file and in ArcMap a
nd added a
new field (field type = double) ] named “BGAcres”.
• U
sed ArcGIS’ Calculate Geometry tool to calculate the total acres found in each census block.
• Ran a Spatial Intersect between the NJ 2021 census block group file and the grid file. Then, using the
methods listed above to calculate the total acres (field type = double, name = “SIAcres”) within the
output created from the Spatial Intersect.
• D
ivided the acres “SIAcres” from the spatial intersect output by the Acres calculated from the Census
block group file “BGAcres” to develop the Area Ratio.
• With the ArcGIS field calculator, multiplie
d the Area Ratio from the previous step by the daily
concentrations of ozone in micrograms per cubic meter (μg/m3).
• R
an the ArcGIS Frequency tool using the Spatial Intersect shapefile as the input table, the
Department's IDNum field in the frequency field, and the multiplied values from in the previous step
in the Summary field to get the weighted sum of ozone in parts per million (ppm) for each block
group.
• Dev
eloped block group ozone data using a join feature to associate fields in the the output weighted
sum of ozone from the previous step with the original 2021 NJ block groups and applicable tr
ibal
ar
eas.
Fine Particulate Matter (PM
2.5
)
Description
Particulate matter is the descriptive term for particles found in the air, including dust, dirt, soot, smoke, and
liquid droplets. These particles can be manmade or naturally occurring, and directly emitted or formed in the
3
Fleischman, L. & Franklin, M. (2017) “Fumes Across the Fence-Line: The Health Impacts of Air Pollution from Oil &
Gas Facilities on African American Communities”, NAACP & Clean Air Task Force report, see
https://cdn.catf.us/wp-content/uploads/2017/11/21092330/catf-rpt-naacp-4.21.pdf
18 Page of 65
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EJMAP: Technical Guidance April 12, 2023
atmosphere from the chemical reactions of other pollutants. Particles less than 2.5 micrometers in diameter,
referred to as fine particulate matter or PM
2.5
, pose the greatest public health risk. PM
2.5
can penetrate
deeper into the lungs and may even get into the bloodstream. New Jersey was redesignated to attainment
for the latest PM
2.5
24-hour primary NAAQS (35 micrograms per cubic meter (μg/m
3
)) in 2013 and the latest
PM
2.5
annual primary NAAQS (12 μg/m
3
) in 2015 and continues to maintain both those standards.
4
A strong body of scientific evidence shows that long- and short-term exposure to PM
2.5
below the current standards
can lead to heart attacks, asthma attacks, and premature death.
5
Of the six NAAQS, ozone and particulate matter
pose the most widespread and significant health threats. New Jersey maintains a network of monitoring stations
that provide data to better understand exposures to PM
2.5
and other air pollutants across the state. Fine particulate
matter is measured at 20 monitoring stations throughout New Jersey, 13 of which use the Federal Reference
Method of filter-based samplers that pull a predetermined amount of air through the selective inlets for a 24-hour
period. To provide real-time hourly data to the public, the State also has particle monitors that operate continuously.
Indicator and Measurement Unit(s)
The Department utilized a 3-year (2019 to 2021) average AQI days greater than 100 for fine particulate matter. The
AQI is a system for communicating daily air quality to the public, warning them when air pollutant levels in their area
are unhealthy. It’s easiest to visualize the AQI as a yardstick that runs from 0 to 500; the higher the AQI daily value,
the greater the concern. AQI values correspond to a NAAQS for a particular pollutant, with AQI values below 100
considered safe.
Rationale
PM
2.5
has known adverse effects on the heart and lungs and can exacerbate existing respiratory diseases and
cardiovascular effects. Health studies show a significant association between exposure to fine particulate pollution
and health risks, including premature death. The smaller the size of the particles, the greater the potential for
causing health issues. In 2013, the World Health Organization’s International Agency for Research on Cancer
concluded that outdoor air pollution is carcinogenic to humans, with the particulate matter component most closely
associated with increased cancer incidence, particularly lung cancer.
6
Other health effects from PM
2.5
exposure
include lung disease, decreased lung function, asthma attacks, heart attacks and irregular heartbeat.
As with ground-level ozone, people with pre-existing respiratory ailments are especially prone to the effects of
PM
2.5
. Roughly one out of every three people in the United States is at a higher risk of experiencing PM
2.5
related
health effects, from active children that spend a lot of time playing outdoors as their bodies develop to the elderly
population. These additional impacts are particularly concerning in overburdened communities that already
experience a higher-than-average share of at-risk communities. For PM
2.5
, those in poverty had 1.35 times higher
burden than did the overall population, and non-whites had 1.28 times higher burden. Black people, specifically, had
1.54 times higher burden than did the overall population. These patterns were relatively unaffected by sensitivity
analyses, and disparities held not only nationally but within most states and counties as well.
7
Particulate matter comes from many sources, both stationary and mobile, emitted as direct solid particles made of
various components, including black and organic carbon, metals, and indirect formation from gas emissions (nitrates
and sulfates. The main sources of black carbon are combustion engines, particularly diesel engines, residential wood
4
https://www.nj.gov/dep/baqp/aas.html#annualpm
5
https://www.epa.gov/newsreleases/epa-reexamine-health-standards-harmful-soot-previous-administration-left-
unchanged
6
PR 221 - IARC: Outdoor air pollution a leading environmental cause of cancer deaths (who.int)
7
Mikati, I.; Benson, A.F.; Luben, T.J.; Sacks, J.D.; & Richmond-Bryant, J. “Disparities in distribution of particulate
matter emission sources by race and poverty status.” American Journal of Public Health, vol. 108, no. 4, 2018, pp.
480-485) https://doi.org/10.2105/AJPH.2017.304297
19 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
and coal burning, fossil fuel power stations and forest and other vegetative burning. Consequently, black carbon is a
universal indicator of particulate matter from a large variety of combustion sources and, when measured in the
atmosphere, is always associated with other substances from combustion sources, such as organic compounds.
Because of these links, the health outcomes associated with exposure to particulate matter are also associated with
exposure to black carbon.
8
Stressor Value Calculation Method
• Obtained PM
2.5
FRM/FEM Mass daily monitoring results for all NJ air monitoring sites as well as
nearby monitors in Connecticut, Delaware, Pennsylvania, and New York from the
EPA's Daily
Summary Data Site for the years 2019 to 2021. See Appendix A of this document for the coordinates
of all the air quality monitors used in this analysis.
• Created separate GIS files from the monitoring sites’ latitude and longitude data for each applicable
year.
• Applied ArcMap’s Inverse Distance Weighting (IDW) interpolation tool
to these monitoring results to
estimate daily grid level concentrations of PM
2.5
in micrograms per cubic meter (μg/m
3
). The IDW
interpolation tool determined cell values using a linearly weighted combination of a set of sample
points. The weight is a function of inverse distance. The surface being interpolated is the locationally
dependent variable (e.g., the monitor locations). The following specific parameters were used:
o Grid cell size of 0.05 degrees
o Power: of 5
o Search Radius: Variable 10
• Summarized the daily results for each grid to determine the number of days the estimated
concentration was above the Air Quality Index (AQI) level of 100 (which equals 35 μg/m
3
for PM
2.5
(averaged over 24-hours)) and then averaged those summarized results to create one 3-year value
for each grid.
• Downloaded the 2021 NJ block groups and applicable tribal areas file
and in ArcMap, added a new
field (field type = double) named “BGAcres”.
• Used ArcGIS’ Calculate Geometry tool to calculate the total Acres found in each census block group.
• Ran a Spatial Intersect between the 2021 NJ block groups and applicable tribal areas file and the grid
file. Then, using the methods listed above to calculate the total acres (field type = double, name =
“SIAcres”) within the output created from the Spatial Intersect.
• Divided the acres “SIAcres from the spatial intersect output by the acres calculated from the Census
block group file (“BGAcres”) to develop the Area Ratio.
• With the ArcGIS field calculator
, multiplied the Area Ratio from the previous step by the daily
concentrations of PM
2.5
in micrograms per cubic meter (μg/m3).
• Ran the Frequency tool using the Spatial Intersect shapefile as the input table, the Department's
IDNum field in the frequency field, and the multiplied values from the previous step in the Summary
field to get the weighted sum of PM
2.5
in micrograms per cubic meter (μg/m3) for each block group.
• Developed block group PM
2.5
data using a join feature to associate fields in the output weighted sum
of PM
2.5
from the previous step with the original 2021 NJ block groups and applicable tribal areas.
Cancer Risk from Diesel Particulate Matter
Description
Diesel is a type of fuel derived from crude oil that is used most in the large engines in trucks, buses, trains,
construction and farm equipment, generators, and ships. Diesel exhaust is comprised of gases, including
carbon dioxide, carbon monoxide, nitric oxide, nitrogen dioxide, sulfur oxides, and hydrocarbons, and
particulates, including black carbon, organic materials, and metallic compounds. Both parts of diesel exhaust
8
World Health Organization, Regional Office for Europe (2012), Health Effects of Black Carbon, see
https://www.euro.who.int/__data/assets/pdf_file/0004/162535/e96541.pdf
20 Page of 65
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contain polycyclic aromatic hydrocarbons or PAHs. Several national and international agencies, including the
WHO’s International Agency for Research on Cancer (IARC), the National Toxicology Program (NTP), EPA, and
the National Institute for Occupational Safety and Health (NIOSH) have classified diesel exhaust as a probable
human carcinogen, based largely on its link to lung cancer.
9
Indicator and Measurement Unit(s)
AirToxScreen, formally known as the National Air Toxics Assessment or NATA, is a key part of the EPA’s Air
Toxics Data Update, an ongoing thorough evaluation of air toxics in the United States. AirToxScreen is a
screening tool to help state, local and tribal agencies identify which pollutants, emission sources, and places
they may wish to study further to better understand any possible risks to public health. AirToxScreen gives a
snapshot of outdoor air quality based on inhalation of air toxics, estimating cancer risk for all covered air
toxics and noncancer health effects for certain covered pollutants at the census tract level. The 2018
AirToxScreen, the most recent publicly available assessment, includes emissions, ambient concentrations,
and exposure estimates for 181 of the 189 air toxics plus diesel particulate matter.
10
The Department utilized
2018 AirToxScreen ambient air concentration data and California’s Diesel Unit Risk Factor to estimate the
potential cancer risk from Diesel Particulate Matter in Risk per Million.
Rationale
AirToxScreen includes diesel particulate matter as an indicator of diesel exhaust as one of its core stressors.
The key measures of cancer risk developed for the 2018 AirToxScreen include upper-bound estimated
lifetime individual cancer risk and the estimated numbers of people within specific risk ranges (e.g., number
of individuals with estimated long-term cancer risk of 1-in-1 million or greater). Starting in 2014, the National
Emission Inventory (NEI) included diesel particulate matter along with NEI criteria and hazardous air
pollutants. In the NEI, diesel particulate matter is computed as the PM
10
emissions (particulate matter with
diameters less than or equal to 10 μg/m
3
, inclusive of PM
2.5
) from on-road and nonroad engines burning
diesel or residual oil fuels. Although stationary engines also can burn diesel fuel, only mobile sources were
used for estimating diesel PM emissions in the NEI.
11
Diesel engines emit a variety of pollutants, with diesel particulate matter having potentially the greatest
health impacts. In fact, diesel exhaust may contribute as much as 70 percent of the cancer risk from air toxic
pollution, making it more harmful than all the other toxic air contaminants combined. Diesel particulate
matter can also cause or aggravate other health problems and has been linked with illnesses and deaths from
heart and lung disease. These effects have been associated with both short-term exposures (over a 24-hour
period) and long-term exposures (over many years). Diesel exhaust includes over 40 substances, including
benzene, toluene, arsenic, and formaldehyde, that are listed by the EPA as hazardous air pollutants and by
the California Air Resources Board as toxic air contaminants. Fifteen of these substances are listed by the
International Agency for Research on Cancer (IARC) as carcinogenic to humans, or as probable human
carcinogens. Long-term exposure to diesel exhaust particles poses the highest cancer risk of any toxic air
contaminant.
12, 13
California has long identified diesel exhaust as a chemical known to cause cancer and
developed a unit risk factor for quantifying its cancer risk in the range of 1.3 x 10
-4
to 1.5 x 10
-3
per μg/m
3
9
https://www.cancer.org/cancer/cancer-causes/chemicals/diesel-exhaust-and-cancer.html
10
https://www.epa.gov/AirToxScreen/2018-airtoxscreen. The USEPA is still preparing the 2018 version of its
Technical Support Document, and refers users to the very similar 2017 version (USEPA (2022), Technical Support
Document EPA’s Air Toxics Screening Assessment, 2017 AirToxScreen TSD, March 2022, see
https://www.epa.gov/system/files/documents/2022-03/airtoxscreen_2017tsd.pdf) in the interim.
11
Ibid.
12
https://www.stopthesoot.org/Raritan%20health%20effects%20final%20Feb%2008_1.pdf
13
https://oehha.ca.gov/air/health-effects-diesel-exhaust
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with a “reasonable estimate” of 3 x 10
-4
, which equates to the air concentration that gives a one in a million
cancer risk (.0033 μg/m
3
).
14
There is an extensive body of empirical evidence detailing the health impacts of from the PM
2.5
component of
diesel and other goods movement-related transportation emissions in environmental justice communities.
Those communities located adjacent to ports and related goods movement infrastructure (e.g., warehouses,
logistics centers, railyards, etc.) experience higher levels of truck traffic, both from surrounding thruways and
on local streets.
15
A recent study by the Union of Concerned Scientists found that communities of color
throughout the Northeast and Mid-Atlantic U.S. are more likely to be expose to the highest levels of PM
2.5
.
Specifically, the Union of Concerned Scientist’s noted that average annual PM
2.5
concentrations of exposures
from cars, trucks and buses for Latino residents are 75 percent higher, and for Asian American residents they
are 73 percent higher, than they are for white residents. Exposures for African American residents are 61
percent higher than for white residents.
16
Stressor Value Calculation Method
• Obtained New Jersey’s 2018 state summary file from AirToxScreen’s
State Summary Files dropdown
menu, and isolated the Diesel PM concentrations from the Ambient Concentration.
• Applied the Diesel exhaust particulate Unit Risk Factor (URF) from NJ's Toxicity Values for Inhalation
Exposure (0.0003 (ug/m3)-1) to the Diesel PM concentrations to determine the estimate potential
cancer risk in risk per million.
• Summed the potential cancer risk from each pollutant for each census tract to estimate total
potential cancer risk in risk per million.
• Download the 2021 NJ block groups and applicable tribal areas file
and in ArcMap, add a new field
(field type = double) named “BGAcres”.
• Used ArcGIS’ Calculate Geometry tool to calculate the total Acres found in each census block group.
• Ran a Spatial Intersect between the 2021 NJ block groups and applicable tribal areas file and the
census tract file. Then, using the methods listed above to calculate the total acres (field type =
double, name = “SIAcres”) within the output created from the Spatial Intersect.
• Divided the acres “SIAcres” from the spatial intersect output by the acres calculated from the Census
block group file (“BGAcres”) to develop the Area Ratio.
• With the ArcGIS field calculator
, multiplied the Area Ratio from the previous step by the estimated
potential cancer risk.
• Ran the ArcGIS Frequency tool using the Spatial Intersect shapefile as the input table, the
Department’s IDNum field in the frequency field, and the multiplied values from in the previous step
in the Summary field to get the weighted sum of estimated potential cancer risk for each block
group.
• Developed block group cancer risk from diesel PM data using a join feature to associate fields in the
output weighted sum of estimated potential cancer risk from the previous step with the original
2021 NJ block groups and applicable tribal areas.
14
https://www.nj.gov/dep/airtoxics/diesemis.htm
15
NJB&A (2020), Newark Community Impacts of Mobile Source Emissions: A Community-Based Participatory
Research Analysis, November 2020, see
https://www.njeja.org/wp-
content/uploads/2021/04/NewarkCommunityImpacts_MJBA.pdf
16
Union of Concerned Scientists (2019), Inequitable Exposure to Air Pollution from Vehicles in the Northeast and
Mid-Atlantic, see
https://www.ucsusa.org/sites/default/files/attach/2019/06/Inequitable-Exposure-to-Vehicle-
Pollution-Northeast-Mid-Atlantic-Region.pdf
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Cancer Risk from Air Toxics Excluding Diesel Particulate Matter
Description
While cancer risk from diesel exhaust is significant, it does not negate the carcinogenic effects of other air
toxics in the atmosphere. However, it does make them less noticeable when presented together with the
carcinogenic impacts from diesel particulate matter. As such, the Department removed diesel PM from the
equation and concentrated on the remaining air toxics with carcinogenic effects assessed in the 2018
AirToxScreen. Air toxics (also referred to as toxic air pollutants or hazardous air pollutants (HAPs)) include
benzene, found in gasoline; perchloroethylene, emitted from dry cleaning facilities; vinyl chloride, used to
make polyvinyl chloride (PVC) plastic and vinyl products; and ethylene oxide, emitted from commercial and
hospital sterilizers.
Indicator and Measurement Unit(s)
The Department utilized the 2018 AirToxScreen’s ambient concentration data for all air toxics except for
diesel particulate matter and aligned those values with the pollutant’s corresponding unit risk factor (URF) to
estimate the potential cancer risk from 138 of the non-diesel particulate matter air toxics in Risk per Million.
Rationale
AirToxScreen includes air toxics that the EPA has classified as “carcinogenic to humans,” “likely to be
carcinogenic to humans,” or “suggestive evidence of carcinogenic potential.” The key measures of cancer risk
developed for the 2018 AirToxScreen include upper-bound estimated lifetime individual cancer risk and the
estimated numbers of people within specific risk ranges (e.g., number of individuals with estimated long-
term cancer risk of 1-in-1 million or greater).
17
Zhou et al. (2015) identified formaldehyde, carbon
tetrachloride, acetaldehyde, and benzene as the most frequently found air toxics with cancer risk greater
than 1-in-1 million in the U.S. Zhou et al. (2015) further determined that the most frequently occurring binary
pairs or ternary mixtures were various combinations of those four air toxics, with formaldehyde and benzene
together contributing nearly 60 percent of the total cancer-related health impacts.
18
The 2018 AirToxScreen
confirms these findings by identifying formaldehyde as a National Cancer Driver and carbon tetrachloride,
acetaldehyde, and benzene as National Cancer Contributors.
19
From 1990 to 2017 emissions of air toxics declined by 74 percent, largely driven by federal and state
implementation of stationary and mobile source regulations.
20
Weitekamp, Lein et al (2021) leveraged HAPs
monitoring data across the Nation to complement USEPA’s modeled cancer risk in AirToxScreen and allow for
spatial and temporal trend evaluation.
21
Their findings show that the estimated cancer risk (5-year annual
average) for most monitoring sites exceeded 50 in 1 million, and all sites had an estimated risk of 20 in 1
million. These estimated risks were primarily driven by carbonyl concentrations (formaldehyde and
acetaldehyde), which represented 37 to 82 percent of the cancer risk across these sites. VOCs represented
12%–41%, PAHs represented 1%–11%, and PM-speciated metals and metalloids represented 2%–15% of the
estimated cancer risk across these sites.
17
https://www.epa.gov/system/files/documents/2022-08/AirToxScreen%20Risk%20Drivers.pdf
18
Zhou, Y., Li, C., Huijbregts, M. A., & Mumtaz, M. M. (2015). Carcinogenic Air Toxics Exposure and Their Cancer-
Related Health Impacts in the United States. PloS one, 10(10),
e0140013https://doi.org/10.1371/journal.pone.0140013
19
https://www.epa.gov/system/files/documents/2022-08/AirToxScreen%20Risk%20Drivers.pdf
20
https://www.epa.gov/air-trends/air-quality-national-summary
21
Weitekamp, C. A., Lein, M., Strum, M., Morris, M., Palma, T., Smith, D., Kerr, L., & Stewart, M. J. (2021). An
Examination of National Cancer Risk Based on Monitored Hazardous Air Pollutants. Environmental health
perspectives, 129(3), 37008. https://doi.org/10.1289/EHP8044
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EJMAP: Technical Guidance April 12, 2023
Much of the published literature supports the hypothesis that proximity to environmental hazards translates
to higher risks, including increased adverse health risks. Concern about proximity to industrial facilities and
other pollutant sources stems from the fact that industrial areas generally carry a higher environmental
burden than do purely residential neighborhoods in terms of pollution and risks.
22
Given that carcinogenic air
toxics are associated with industrial sources, its unsurprising that these elevated exposures would align with
environmental justice communities where there is greater air toxics exposure overall. Weitekamp, Lein et al
(2021) examined population levels within a 0.25-, 0.5-, and 1-mile radius corresponding to the location of
National HAP monitors and found a cancer risk of 51–75 in 1 million was associated with the highest
population living within a 10-mile radius.
23
Also, using linear regression, Weitekamp, Lein et al (2021) found a
positive correlation between estimated cancer risk and percent of the population within 1 mile that was low
income but no relationship with percent of the population within 1 mile that was minority status.
Stressor Value Calculation Method
• Obtained New Jersey’s 2018 state summary file from AirToxScreen’s State Summary Files dropdown.
• Applied the corresponding Unit Risk Factor (URF) from NJ's Toxicity Values for Inhalation Exposure
to
each applicable pollutant’s estimated ambient concentration, excluding Diesel PM to estimate each
individual pollutant’s potential cancer risk in risk per million. If there was not a corresponding URF,
that pollutant only has non-carcinogenic impacts, and was excluded from this analysis.
• Summed the potential cancer risk from each pollutant for each census tract to estimate total
potential cancer risk in risk per million.
• Download the 2021 NJ block groups and applicable tribal areas file
and in ArcMap, add a new field
(field type = double) named “BGAcres”.
• Used the ArcGIS Calculate Geometry tool to calculate the total acres found in each census block
group.
• Ran a Spatial Intersect between the NJ census block group file and the census tract file. Then, using
the methods listed above to calculate the total acres (field type = double, name = “SIAcres”) within
the output created from the Spatial Intersect.
• Divided the acres “SIAcres” from the spatial intersect output by the acres calculated from the Census
block group file (“BGAcres”) to develop the Area Ratio.
• With the ArcGIS field calculator
, multiplied the Area Ratio from the previous step by the estimated
potential cancer risk.
• Ran the ArcGIS Frequency tool using the Spatial Intersect shapefile as the input table, the
Department’s IDNum field in the frequency field, and the multiplied values from in the previous step
in the Summary field to get the weighted sum of estimated potential cancer risk for each block
group.
• Developed block group cancer risk excluding diesel PM data using a join feature to associate fields in
the output weighted sum of estimated potential cancer risk from the previous step with the original
2021 NJ block groups and applicable tribal areas.
Non-Cancer Risk from Air Toxics
Description
The EPA’s 2018 AirToxScreen also accounts for the noncancer health impacts from exposure to air toxics.
These health effects include impacts on the lungs and other parts of the respiratory system; on the immune,
22
Maantay, Chakraborty, and Brender (2010), Proximity to Environmental Hazards: Environmental Justice and
Adverse Health Outcomes, May 12, 2010, see https://archive.epa.gov/ncer/ej/web/pdf/brender.pdf
23
Weitekamp, C. A., Lein, M., Strum, M., Morris, M., Palma, T., Smith, D., Kerr, L., & Stewart, M. J. (2021). An
Examination of National Cancer Risk Based on Monitored Hazardous Air Pollutants. Environmental health
perspectives, 129(3), 37008. https://doi.org/10.1289/EHP8044
24 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
nervous, and reproductive systems; and to organs such as the heart, liver, and kidneys. These effects can
range from headaches and nausea to respiratory arrest and death, with the severity depending on the
amount and length of exposure and the nature of the chemical itself.
24
Indicator and Measurement Unit(s)
The Department utilized the EPA 2018 AirToxScreen data to estimate the potential non-cancer risk from 138
of the air toxics in Risk per Million.
Rationale
AirToxScreen includes air toxics that are associated with many noncancer adverse health effects. Unlike other
pollutants that EPA regulates, air toxics have no universal, predefined risk levels that clearly represent
acceptable or unacceptable thresholds. Instead, EPA sets regulatory-specific targets (e.g., benzene NESHAP
rule) to protect the most people possible to an individual lifetime risk level no higher than about 1-in-1
million. These determinations require the consideration of other health and risk factors, including risk
assessment uncertainty, in making an overall judgment on risk acceptability.
To estimate noncancer air toxic health impacts, EPA calculates a Hazard Index (HI) that sums the Hazard
Quotients (HQs) to account for potential noncancer health effects to certain human organs and organ
systems due to long-term exposure to air toxics. Each air toxic HQ is a ratio of the potential exposure to that
substance and the level at which no adverse effects are expected. An HQ or HI of 1 or lower means a specific
air toxic, or air toxics combined, are unlikely to cause adverse noncancer health effects over a lifetime of
exposure. However, an HQ or HI greater than 1 does not necessarily mean adverse effects are likely. Instead,
the EPA evaluates this on a case-by-case basis, considering the confidence level of the underlying health data,
the uncertainties, the slope of the dose-response curve (if known), the magnitude of the exceedances, and
the numbers or types of people exposed at various levels above the Reference Concentration (RfC).
As discussed previously, much of the published literature supports the hypothesis that proximity to
environmental hazards translates to higher risks, including increased adverse health risks. Concern about
proximity to industrial facilities and other pollution sources stems from the fact that industrial areas generally
carry a higher environmental burden than do purely residential neighborhoods in terms of pollution and
risks.
25
Health disparities (adverse health outcomes disproportionately affecting minority and lower-income
populations) are a well-documented phenomena in the United States.
Despite overall health improvements over time, significant disparities remain in several health indicators,
most notably in life expectancy and infant mortality.
26
In addition, racial disparities have widened over time;
in 2015, black infants had 2.3 times higher mortality than white infants (11.4 vs. 4.9 per 1,000 live births).
Infant and child mortality was markedly higher in rural areas and poor communities, and Black infants and
children in poor, rural communities had nearly three times higher mortality rate compared to those in
affluent, rural areas. Racial/ethnic, socioeconomic, and geographic disparities were particularly marked in
mortality and/or morbidity from cardiovascular disease, cancer, diabetes, COPD, HIV/AIDS, homicide,
psychological distress, hypertension, smoking, obesity, and access to quality health care.
24
USEPA (2022), Technical Support Document EPA’s Air Toxics Screening Assessment, 2017 AirToxScreen TSD,
March 2022, see https://www.epa.gov/system/files/documents/2022-03/airtoxscreen_2017tsd.pdf
.
25
Maantay, Chakraborty, and Brender (2010), Proximity to Environmental Hazards: Environmental Justice and
Adverse Health Outcomes, May 12, 2010, see https://archive.epa.gov/ncer/ej/web/pdf/brender.pdf
26
Singh, G. K., Daus, G. P., Allender, M., Ramey, C. T., Martin, E. K., Perry, C., Reyes, A., & Vedamuthu, I. P. (2017).
Social Determinants of Health in the United States: Addressing Major Health Inequality Trends for the Nation,
1935-2016. International journal of MCH and AIDS, 6(2), 139–164. https://doi.org/10.21106/ijma.236
.
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Stressor Value Calculation Method
• Obtained New Jersey’s 2018 state summary file from AirToxScreen’s State Summary Files dropdown.
• Applied the corresponding Reference Concentration (RfC) from
NJ's Toxicity Values for Inhalation
Exposure to each applicable pollutant’s estimated ambient concentration to estimate each individual
pollutant’s potential noncancer HQ. If there was not a corresponding RfC, that pollutant only has
carcinogenic impacts, and was excluded from this analysis.
• Summed all pollutant HQs for each census tract to estimate the total HI.
• Download the 2021 NJ block groups and applicable tribal areas file
and in ArcMap, add a new field
(field type = double) named “BGAcres”.
• Used ArcGIS’ Calculate Geometry tool to calculate the total acres found in each census block group.
• Ran a Spatial Intersect between the NJ census block group file and the census tract file. Then, using
the methods listed above to calculate the total acres (field type = double, name = “SIAcres”) within
the output created from the Spatial Intersect.
• Divided the acres “SIAcres” from the spatial intersect output by the acres calculated from the Census
block group file (“BGAcres”) to develop the Area Ratio.
• With ArcGIS field calculator
, multiplied the Area Ratio from the previous step by the estimated
potential HI.
• Ran ArcGIS Frequency tool using the Spatial Intersect shapefile as the input table, the Department's
IDNum field in the frequency field, and the multiplied values from in the previous step in the
Summary field to get the weighted sum of estimated HI for each block group.
• Developed block group non-cancer risk data using a join feature to associate fields in the output
weighted sum of estimated HI risk from the previous step with the original
2021 NJ block groups and
applicable tribal areas.
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New Jersey Department of Environmental Protection
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Mobile sources of air pollution
The State’s transportation network, including cars, buses, light-, medium- and heavy-duty trucks, and rail, is
its large source of criteria and hazardous air pollutants, as well as greenhouse gas emissions. Cars and light-
duty trucks alone account for approximately 30% of the total VOCs and NO
x
emissions that contribute to
ground-level ozone formation. Additionally, the transportation sector accounts for 42% of the State’s net
greenhouse gas emissions, making it New Jersey’s largest contributor to climate change.
Traffic – Cars and Light- and Medium-Duty Trucks
Description
There are over 6.5 million cars and light- and medium-duty trucks (up to 14,000 pounds) registered in New
Jersey. These vehicles, primarily fueled by gasoline, join larger trucks as well as commuter and thru traffic
from surrounding states to make New Jersey roads some of the most densely travelled in the U.S. Traffic
congestion, defined as periods when traffic volume exceeds roadway capacity
27
, creates stop and go traffic,
and idling in place. Idling for more than 10 seconds uses more fuel, thereby producing more emissions, than
stopping and restarting the engine, which is simply not practical in gridlock traffic.
28
In many instances,
congestion is recurring, as high traffic volumes regularly overload roadways during weekday peak “rush hour”
periods. This recurring congestion increases risk for both on- and near-road populations.
Indicator and Measurement Unit(s)
The Federal Highway Administration’s (FHWA) Highway Performance Monitoring System (HPMS)
Average
Annual Daily Traffic (AADT)-mile per square mile within a block group as an indicator of cars and light- and
medium-duty truck traffic proximity to residences and other institutions (e.g., schools).
Rationale
Residential proximity to traffic is associated with various health impacts, particularly the onset of, or
exacerbation of asthma, as well as mortality rates.
29
Proximity to traffic has also been associated with
subclinical atherosclerosis (a key pathology underlying cardiovascular disease (CVD)), prevalence of CVD and
coronary heart disease (CHD), incidence of myocardial infarction, and CVD mortality. These health impacts
likely stem from increased exposure to vehicle-related emissions such as ultrafine and other components of
PM
2.5
, lead and other metals, and mobile source air toxics such as benzene, nitrogen oxides (NO
x
), volatile
organic compounds (VOCs) and carbon monoxide (CO). Vehicles also emit ozone and PM
2.5
precursors in
addition to being New Jersey’s largest source of CO
2
emissions. Ambient exposure to nitrogen oxides, sulfur
dioxide, and fine particulate matters significantly increases the risk of lung cancer.
30
Traffic proximity is also associated with noise, which is a risk factor for various health problems. Workplace
and transportation-related noise is associated with the release of stress hormones; sleep disturbance;
hypertension; altered heart rate; ischemic heart disease; myocardial infarction; and, among the elderly, risk
of stroke.
31
In one study, Sørensen et al. (2011) found that among those older than 64.5 years of age, the
27
Zhang, K., & Batterman, S. (2013). Air pollution and health risks due to vehicle traffic. The Science of the total
environment, 450-451, 307–316. https://doi.org/10.1016/j.scitotenv.2013.01.074
28
US Department of Energy (2015), Idling Reduction for Personal Vehicles, see
https://afdc.energy.gov/files/u/publication/idling_personal_vehicles.pdf
29
U.S. Environmental Protection Agency (EPA), 2019. EJSCREEN Technical Documentation, see
https://www.epa.gov/sites/default/files/2021-04/documents/ejscreen_technical_document.pdf
30
Chen, G., Wan, X., Yang, G., & Zou, X. (2015). Traffic-related air pollution and lung cancer: A meta-analysis.
Thoracic cancer, 6(3), 307–318. https://doi.org/10.1111/1759-7714.12185
.
31
U.S. Environmental Protection Agency (EPA), 2019. EJSCREEN Technical Documentation, see
https://www.epa.gov/sites/default/files/2021-04/documents/ejscreen_technical_document.pdf
27 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
stroke incidence rate ratio was 1.27 per 10 decibels from road traffic.
32
(Whether noise or other factors
account for it, local traffic volume is a predictor of stress which itself is associated with significant health
risks. In 2010, Yang & Matthews concluded that, “[a]t the neighborhood level, the presence of hazardous
waste sites and traffic volume were determinants of self-rated stress even after controlling for other
individual characteristics”.
33
A 2022 study from the Rutgers Robert Wood Johnson Medical School found that
5% of hospitalizations for heart attacks were attributable to elevated high noise levels (an average of 65
decibels or higher over the course of the day) in New Jersey.
34
The study further found that the heart attack
rate was 72% higher in places with high transportation noise exposure, with these areas seeing 3,336 heart
attacks per 100,000 people compared with 1,938 heart attacks per 100,000 people in quieter areas. Based on
the relative rates of heart attack in different locations, the researchers calculated that high noise exposure
accounted for about 1 in 20 heart attacks in the state.
Stressor Value Calculation Method
• Obtained NJ’s 2020 HPMS GIS file data
.
• Summed the single unit (attribute field labeled aadt_single_unit) and combined truck (attribute field
labeled aadt_combination) AADT values for each road segment in New Jersey to determine the total
AADT Truck values representing all heavy-duty trucks classes 4 through 13 (i.e., buses, singe-unit
trucks, single- and multi-trailer trucks) for each road segment.
• Subtracted the calculated AADT Truck values from the total AADT (attribute field labeled aadt) values
for each road segment for New Jersey, to calculate the AADT for cars, and light- and medium-duty
trucks only for each road segment.
• Applied ArcGIS’ line density
function to the calculated AADT for cars and light-duty trucks using the
following parameters:
o Grid cell size 100 ft.
o Search radius of 1000 ft.
o AADT for cars and light-duty trucks used as population field.
This created a raster surface file.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst
using the created raster surface
file as the input to determine the spatially weighted average AADT for each 2021 NJ census block
group and applicable tribal areas as the indicator for light-duty traffic on major roads.
Traffic – Heavy-Duty Trucks
Description
There are approximately 189,000 vehicles over 14,000 lbs. (e.g., delivery vans, tractors pulling trailers)
registered in New Jersey. These trucks, predominately fueled by diesel, join commuter and thru traffic from
surrounding states to make New Jersey roads some of the most densely travelled in the U.S. According to the
American Transportation Research Institute, New Jersey is home to some of the most congested stretches of
highway in America; in particular, 1-96 and Route 4 in Fort Lee.
35
These trucks are vital to goods movement in
and around the state, transporting freight from the source of production to points of consumption. However,
32
Sørensen, M., Hvidberg, M., Andersen, Z. J., Nordsborg, R. B., Lillelund, K. G., Jakobsen, J., . . . Raaschou-Nielsen,
O. (2011). Road traffic noise and stroke: A prospective cohort study. Eur Heart J, 32(6), 737-744,
https://doi.org/10.1093/eurheartj/ehq466
.
33
Yang, T.-C., & Matthews, S. A. (2010). The Role of Social and Built Environments in Predicting Self-rated Stress: A
Multilevel Analysis in Philadelphia. Health & Place, 16(5), 803-810,
https://doi.org/10.1016/j.healthplace.2010.04.005
.
34
Moreyra A, Subramanian K, Mi Z, et al. THE IMPACT OF EXPOSURE TO TRANSPORTATION NOISE ON THE RATES
OF MYOCARDIAL INFARCTION IN NEW JERSEY. J Am Coll Cardiol. 2022 Mar, 79 (9_Supplement) 1148,
https://doi.org/10.1016/S0735-1097(22)02139-8
.
35
https://truckingresearch.org/2021/02/23/atri-releases-annual-list-of-top-100-truck-bottlenecks-4/
28 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
the ports of entry and intermediary storage for goods (e.g., seaports, airports, railyards and warehouse and
distribution facilities) are often collocated with low-income communities and communities of color.
36
The
amplified truck traffic in and around these facilities, coupled with the increased emissions from stop and go
traffic and unavoidable idling on roads in these communities, increases exposure to diesel particulate matter
and other toxic air pollutants.
Indicator and Measurement Unit(s)
FHWA HPMS AADT mile per square mile within a block group as an indicator of heavy-duty truck traffic
proximity to residences and other institutions (e.g., schools).
Rationale
Residential proximity to traffic is associated with various health impacts, particularly the onset of, or
exacerbation of asthma, as well as mortality rates.
37
Proximity to traffic has also been associated with
subclinical atherosclerosis (a key pathology underlying cardiovascular disease (CVD)), prevalence of CVD and
coronary heart disease (CHD), incidence of myocardial infarction, and CVD mortality. These health impacts
likely stem from increased exposure to vehicle-related emissions such as ultrafine and other components of
PM
2.5
, lead and other metals, and mobile source air toxics such as benzene, nitrogen oxides (NO
x
), volatile
organic compounds (VOCs) and carbon monoxide (CO). Ambient exposure to nitrogen oxides, sulfur dioxide,
and fine particulate matter significantly increase the risk of lung cancer.
38
Heavy-duty trucks contribute to
PM
2.5
and its precursors because of their primary reliance on diesel fuel.
Traffic proximity is also associated with noise, which is a risk factor for various health problems. Workplace
and transportation-related noise are associated with the release of stress hormones; sleep disturbance;
hypertension; altered heart rate; ischemic heart disease; myocardial infarction; and, among the elderly, risk
of stroke.
39
In one study, Sørensen et al., (2011) found among those older than 64.5 years of age, the stroke
incidence rate ratio was 1.27 per 10 dB more road traffic noise.
40
Whether noise or other factors account for
it, local traffic volume is a predictor of stress (which itself is associated with significant health risks). In 2010,
Yang & Matthews concluded that, “[a]t the neighborhood level, the presence of hazardous waste sites and
traffic volume were determinants of self-rated stress even after controlling for other individual
characteristics”.
41
A 2022 study from the Rutgers Robert Wood Johnson Medical School found that 5% of hospitalizations for
heart attacks were attributable to elevated high noise levels (an average of 65 decibels or higher over the
36
https://www.epa.gov/community-port-collaboration/ports-primer-51-goods-movement-and-transportation-
planning
37
U.S. Environmental Protection Agency (EPA), 2019. EJSCREEN Technical Documentation, see
https://www.epa.gov/sites/default/files/2021-04/documents/ejscreen_technical_document.pdf
.
38
Chen, G., Wan, X., Yang, G., & Zou, X. (2015). Traffic-related air pollution and lung cancer: A meta-analysis.
Thoracic cancer, 6(3), 307–318. https://doi.org/10.1111/1759-7714.12185
.
39
U.S. Environmental Protection Agency (EPA), 2019. EJSCREEN Technical Documentation, see
https://www.epa.gov/sites/default/files/2021-04/documents/ejscreen_technical_document.pdf
.
40
Sørensen, M., Hvidberg, M., Andersen, Z. J., Nordsborg, R. B., Lillelund, K. G., Jakobsen, J., . . . Raaschou-Nielsen,
O. (2011). Road traffic noise and stroke: A prospective cohort study. Eur Heart J, 32(6), 737-744,
https://doi.org/10.1093/eurheartj/ehq466
.
41
Yang, T.-C., & Matthews, S. A. (2010). The Role of Social and Built Environments in Predicting Self-rated Stress: A
Multilevel Analysis in Philadelphia. Health & Place, 16(5), 803-810,
https://doi.org/10.1016/j.healthplace.2010.04.005
.
29 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
course of the day) in New Jersey.
42
The study further found that the heart attack rate was 72% higher in
places with high transportation noise exposure, with these areas seeing 3,336 heart attacks per 100,000
people compared with 1,938 heart attacks per 100,000 people in quieter areas. Based on the relative rates of
heart attack in different locations, the researchers calculated that high noise exposure accounted for about 1
in 20 heart attacks in the state.
Stressor Value Calculation Method
• Obtained NJ’s 2020 HPMS GIS file data
.
• Combined the single unit (attribute field labeled aadt_single_unit) and combined truck (attribute
field labeled aadt_combination) AADT values for each road segment in New Jersey to calculate total
AADT Truck values representing all heavy-duty trucks classes 4 through 13 (i.e., buses, singe-unit
trucks, single- and multi-trailer trucks) for each road segment.
• Applied ArcGIS’ line density
function to the calculated total AADT for Truck values using the
following parameters:
o Grid cell size 100 ft.
o Search radius of 1000 ft.
o Total AADT for Truck used as population field
This creates a raster surface file.
• Apply Zonal Statistics as a Table function in ArcMap Spatial Analyst
using the created raster surface
file as the input to determine the spatially weighted average AADT for 2021 NJ census block group
and applicable tribal areas as the indicator for heavy-duty traffic on major roads.
Railways
Description
There are two type of rail systems operating in New Jersey: passenger (both light rail and commuter rail) and
freight. New Jersey Transit Corporation (NJ Transit) is the State-owned public transportation system that
services the State, along with portions of New York State and Pennsylvania. NJ Transit operates three light-
rail systems – Hudson-Bergen (20.6 miles from Bayonne to North Bergen), Newark (4.3 miles from Newark
Penn station to North Newark and Bloomfield) and the River Line (34 miles from Trenton to Camden).
43
In addition, NJTransit operates 11 commuter rail lines throughout the State. While the Hudson-Bergen and
Newark light rails are electric, the River Line light rail is diesel-powered. NJ Transit commuter lines currently
operate 100 diesel and 61 electric locomotives. Other private passenger rail entities, such as Amtrak, share
use of the rail lines throughout the State. New Jersey has eighteen (18) freight railroads operating on
approximately 1,000 miles of rail freight lines.
44
The two Class 1 freight railroads operating in the State are
CSX Transportation and Norfolk Southern. Freight railroads operate their own tracks and associated rail
yards, and often share track access through use agreements.
Indicator and Measurement Unit(s)
The New Jersey Department of Transportation’s rail miles per square mile within a block group as an
indicator of rail traffic proximity to residences and other institutions (e.g., schools).
42
Moreyra A, Subramanian K, Mi Z, et al. THE IMPACT OF EXPOSURE TO TRANSPORTATION NOISE ON THE RATES
OF MYOCARDIAL INFARCTION IN NEW JERSEY. J Am Coll Cardiol. 2022 Mar, 79 (9_Supplement) 1148.
https://doi.org/10.1016/S0735-1097(22)02139-8
.
43
https://en.wikipedia.org/wiki/NJ_Transit
44
New Jersey Department of Transportation (NJDOT) (2014), New Jersey Statewide Freight Rail Strategic Plan, June
2014, see
https://www.state.nj.us/transportation/freight/rail/pdf/NewJerseyStatewideFreightRailStrategicPlanJune2014.pdf
30 Page of 65
New Jersey Department of Environmental Protection
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Rationale
According to data from the U.S. Bureau of
Transportation Statistics (BTS), at the end
of 2020 just over 23,500,000 freight and
484 passenger rail locomotives were in
operation in the U.S.
45
Except for a few
electrified passenger light and commuter
rail lines, the majority of passenger rail and
all of freight rail in the U.S. is diesel-
powered. As seen in the map below, these
predominately diesel locomotives regularly
operate on rail lines and in rail yards
concentrated in and around the most
densely populated areas of New Jersey.
Of particular concern are freight
locomotives transporting goods to and
from the State’s container ports. The Port
Authority of New York and New Jersey is
the third largest container port in the
U.S.
46
, transporting approximately 9
million Twenty-foot Equivalent Units
(TEUs) in 2021, with approximately 70,000
total rail lifts through four on-dock rail
terminals.
47
Freight operations often operate round-
the-clock, and in addition to air and
climate emissions from the locomotives
and associated truck traffic and rail yard
equipment, also contribution to noise,
traffic congestion and industrial blight.
48
A
2014 study of freight rail impacts on
environmental justice communities in
California found that 167,000 residents in
proximity of their three highest priority rail
yards had an estimated diesel cancer of
greater than 100 in a million, which is
characterized as a significant risk.
49
Overall, there was a statistically higher
percentage of non-white residents, particularly Latinos, in the high-risk cancer isopleths near rail yards than
45
https://www.bts.gov/content/rail-profile
46
https://www.bts.gov/archive/publications/port_performance_freight_statistics_annual_report/2016/ch3
47
https://www.panynj.gov/port/en/our-port/facts-and-figures.html
48
Trade, Health and Environmental Impact Project (2012), Tracking Harm: Health and Environmental Impacts of
Rail Yards, January 2012, see https://envhealthcenters.usc.edu/wp-content/uploads/2016/11/Tracting-Harm.pdf
49
Hricko, A., Rowland, G., Eckel, S., Logan, A., Taher, M., & Wilson, J. (2014). Global trade, local impacts: lessons
from California on health impacts and environmental justice concerns for residents living near freight rail yards,
International journal of environmental research and public health, 11(2), 1914–1941,
https://doi.org/10.3390/ijerph110201914.
31 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
the comparative county population. The same study found that with respect to income, the estimated
percentage of low-income households in the 100 in a million-risk isopleth was higher than the comparative
county population for most of their rail yards.
Stressor Value Calculation Method
• Obtained NJDOT ArcGIS REST Railroad Network layer
.
https://njogis-newjersey.opendata.arcgis.com/datasets/NJDOT::railroads-network/about
• Applied the ArcGIS line density function using the following parameters:
o Grid cell size 100 ft.
o Search radius of 1000 ft.
This created a raster surface file.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst
using the created raster surface
file as the input to determine the spatially weighted average rail length for each 2021 NJ census
block group and applicable tribal areas as the indicator for proximity to railroads.
32 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Contaminated Sites
The legacy of New Jersey’s industrialized past is thousands of known contaminated sites (KCS) with polluted
soil and/or groundwater throughout the State. The Site Remediation Reform Act
(SRRA) established the
Department’s Licensed Site Remediation Professional (LSRP) program, which fundamentally changed the
process for how sites are remediated in New Jersey. With the primary goal of reducing the threat of
contamination to public health and the environment, the LSRP program has demonstrated success in
accelerating the process of returning contaminated properties to productive use.
Known Contaminated Sites
Description
New Jersey’s Known Contaminated Sites (KCS) List identifies all properties within the state with confirmed
soil and/or groundwater contamination levels greater than applicable standards. This dataset broadly
includes contaminated sites various stages of remediation (not yet started, currently underway or completed
with implementation of an institutional/engineering control). For this stressor, however, only KCS where
remediation is pending or in progress are included. Fully remediated sites with institutional/engineering
controls in place under a Remedial Action Permit (RAP) are included under other stressors in this category.
The Contaminated Sites stressor is also weighted to accentuate the most critically contaminated locations
from a public health and environmental prospective.
Indicator and Measurement Unit(s)
Weighted KCS per square mile as an indicator of proximity to residents and other institutions (e.g., schools)
within the block group. This is one of six density-based stressors that rely on location and attribute
information from DEP programs to determine how the density calculation impacts a block group. For
contaminated sites, each facility has a Program Interest (PI) Number (also referred to as Pref ID Num). The PI
Number represents a scenario that requires a new record to be entered. The PI Number created by a DEP
program is unique to that specific DEP program and is not linked to another program’s data. As the PI
Number establishes new records based on regulated activities, it presents a more complete picture of a
facility’s impact within its density stressor. Therefore, the PI Number was utilized in this stressor to capture
the environmental burden from contaminated sites present in a block group.
Rationale
Starting in the early 1800s, New Jersey grew and prospered as a manufacturing center in the U.S. Major New
Jersey cities like Paterson, Trenton, Camden, Elizabeth, Jersey City, Newark, Vineland, and Passaic, developed
distinctive industries, including textiles, trains, clay products, iron, and steel.
50
Those industries contributed
to significant contamination with waste products and chemical pollutants. Many of these sites were
abandoned following cessation of industrial activity without a responsible party to remediate for future use.
Presently, those same cities and their citizens, many of whom are low-income and/or communities of color,
bear the brunt of that legacy pollution as well as newer contaminated sites such as former dry cleaners and
gas stations.
Soil contamination can impact human health through various exposure routes. Common routes of human
exposure involve direct contact with soil pollutants via dermal-incidental soil ingestion and inhalation of soil
and dust particles, as well as inhalation of substances volatilized to the atmosphere. Soil contaminants can
also be transported to potable water aquifers, which can result in the ingestion of contaminated
groundwater. Children in urban environments are particularly susceptible to soil contamination.
51
They may
50
https://nj.gov/nj/about/history/short_history.html
51
Gochfeld, M., & Burger, J. (2011). Disproportionate exposures in environmental justice and other populations:
the importance of outliers. American journal of public health, 101 Suppl 1(Suppl 1), S53–S63.
https://doi.org/10.2105/AJPH.2011.300121
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
absorb more contaminants (e.g., lead) and metabolize them differently and their developing nervous systems
are more susceptible to chemicals. From conception through adolescence, children have critical
developmental windows when the nervous system is more susceptible to damage. Children from low-income
and minority families are more likely to be at risk of exposure because they (1) spend more time playing on
contaminated soil than children from higher-income families, (2) spend more time in houses that have lead
paint or high dust levels, (3) may be exposed to higher levels of contaminants in utero and in breast milk
because their mothers are also disproportionately exposed, and (4) have inadequate diets that may increase
the absorption of toxic chemicals from their digestive system.
In New Jersey, about 41 percent of potable water comes from groundwater, either through public- or
domestic-supply wells.
52
Groundwater is supplied by rain that infiltrates the ground. A geological unit that
can yield water to a well is called an aquifer. Aquifers are the primary source of water in Southern New
Jersey, particularly in the Pine Barrens. While water seeping into the ground is cleansed of many pollutants
by natural soil, if a pollutant is one which is resistant to break-down, or if the pollutant
doesn’t get exposed to the soil long enough (such as by entering a bedrock fracture or by
entering the ground water through sub-surface disposal), it can spread underground and potentially
cause health issues and other problems.
53
A 2021 Report by the National Environmental Justice Advisory Council (NEJAC) looked more closely at how
federal Superfund cleanups were addressed in environmental justice communities.
54
That report noted that
EPA’s data shows that Superfund sites disproportionately impact minorities, people living under the poverty
level, and communities who are linguistically isolated, and urged EPA to perform an analysis of the of the
demographics in the communities surrounding National Priorities List Superfund sites to gain a better
prospective on the impacted communities.
Stressor Value Calculation Method
• Obtained NJ's Known Contaminated Sites List (KCSL)
GIS file data. This publicly available dataset now
includes an attribute field (labeled CATEGORY) with a weighted ranking for each site based on
environmental concerns. Sites in the
Immediate Environmental Concern (IEC) GIS layer with a
receptor status of in-progress, and those sites on the NPL were given the highest stressor score (3).
Licensed Site Remediation Professional (LSRP) program cases with 10 or fewer contaminated Areas
of Concern, and Pending sites, were given the lowest weighted stressor score (1). All other sites were
given a weighted stressor score of 2. Unregulated Heating Oil USTs (UHOT) sites and sites with a
restricted or limited restricted Remedial Action Outcome (RAO) were not included in the stressor
evaluation and are assigned a weighted stressor score of 0. RAO sites are identified as Remedial
Action Permit (RAP) sites in the Lead field in the KCSL layer. Unregulated heating oil underground
storage tank sites were assigned a weighted stressor score of zero because they are considered low
risk since they discharge smaller quantities which do not typically impact ground water or travel off
site from the discharge location. Also, any discharges from an unregulated heating oil underground
storage tank that cannot be remediated by a simple excavation are elevated to a higher rank, and
not listed as an unregulated heating oil underground storage tank site. Sites with a restricted or
limited restricted RAO are included in the “Soil Contamination Deed Restriction” and/or the “Ground
52
New Jersey Department of Environmental Protection (NJDEP) (2014), Water Withdrawals in New Jersey from
2000-2009, see https://www.nj.gov/dep/njgs/enviroed/infocirc/withdrawals2009.pdf
53
https://www.co.hunterdon.nj.us/mun/Holland/GroundWater.pdf
54
National Environmental Justice Advisory Council, “Superfund Remediation and Redevelopment for
Environmental Justice Communities”, May 2021, see
https://www.epa.gov/sites/default/files/2021-
05/documents/superfund_remediation_and_redevelopment_for_environmental_justice_communities_may_2021
.pdf
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Water Classification Exception/Currently Known Extent Restrictions” stressor evaluations and are
therefore also assigned a weighted stressor score of zero for this evaluation. Finally, all sites where
remediation has been completed were assigned a weighted stressor score of zero.
• Applied ArcGIS’ Kernel Density
function using the weighted list as input with the following
parameters:
o Search radius of 1 mile, which is consistent with the distance requirements in Department’s
Hazardous Waste rules
o Used field CATEGORY as population to weight sites
o Grid size of 100 ft.
This calculated the raster density file.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst
using the created raster surface
file as the input to determine the spatially weighted average number of sites for each 2021 NJ block
groups and applicable tribal areas as the indicator for proximity to each site.
Soil Contamination Deed Restrictions
Description
Sites with complex contamination issues can have several sources of contamination and can impact both the
soil and groundwater as well as additional media. For KSCL sites where remediation is complete such that it
no longer poses a threat to public health, but the soil and/or ground water still does not meet the requisite
standards, restrictions are placed on use of the site. In cases where soil contamination remains above the
Soil
Remediation Standards (N.J.A.C. 7:26D), the Department requires the addition of a deed notice to the
property’s title. Specifically, the deed notice requires a property owner’s consent, specifies the location of
the contamination as well as its concentrations, and outlines how the remaining contamination must be
controlled, maintained, and/or monitored for protection of human health and the environment.
The deed notice is intended to inform prospective holders with an interest in the property of the remaining
contamination and related use restrictions. A soil Remedial Action Permit (RAP) is issued by the Department
to ensure that the remedial action remains protective. Remedial actions involving a Deed Notice require
institutional and, if necessary, engineering controls (e.g., soil and asphalt caps) designed to eliminate contact
with contaminated soil, prevent contaminant infiltration into the groundwater, eliminate airborne particulate
contamination, and eliminate erosion or off-site migration of contaminated soil from storm runoff.
Indicator and Measurement Unit(s)
The percent of acreage within the block group with Deed Notice restrictions.
Rationale
While soil contamination deed restrictions are protective, sites subject to such restrictions cannot be used for
any purpose and, when found in abundance, reflect siting inequities that the Act seeks to address. Further,
soil contamination deed restrictions are an indicator of historical and ongoing contamination. See the
rationale under “Known Contaminated Sites” above for more detail on the impacts of soil contamination.
Stressor Value Calculation Method
• Obtained Deed Notice Area
GIS file and isolated the Deed Notice Percent Areas for all block groups
data file in each.
• Applied ArcGIS’ Intersect geoprocessing tool to calculate the geometric intersection between the
2021 NJ block groups and applicable tribal areas file and the Deed Notice Percent Area data file such
that only the common features are represented in the output coverage.
• Applied ArcGIS’ Dissolve geoprocessing tool to the output coverage to aggregate features based on
the IDNum field
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• Calculated the total soil restricted area and divided this value by the total acres of the block group to
determine the percentage of each block group that is soil restricted.
Groundwater Classification Exception Area/Currently Known Extent Restrictions
Description
For Known Contaminated Sites where remediation is complete such that it no longer poses a threat to public
health, but the soil and/or groundwater still does not meet the requisite standards, restrictions are placed on
use of the site. A Classification exception area (CEA) is established as a notification that the
Ground Water
Quality Standards (N.J.A.C. 7:9C) have been exceeded and ensures the use of the ground water in an area is
restricted until the standards are achieved. Specifically, the Department initially establishes a classification
exception area (CEA) at the completion of a remedial investigation. The CEA is based on existing ground
water quality data and modeling to determine the extent and duration the contamination will remain above
standards.
The Department also establishes a Currently Known Extents (CKEs) based on potable well sampling results
conducted during the initial stages of an Immediate Environmental Concern (IEC)
investigation. CEAs
boundaries may change over time, while CKEs boundaries generally don't change. CKEs can be replaced by a
CEA when the source(s) of the ground water IEC is identified, and sufficient data exists to establish a CEA for
the site. The CEA can only be lifted when the established ground water quality standards are met. A ground
water RAP is issued by the NJDEP to ensure a remedial action remains protective. Remedial actions involving
a CEA require institutional and if necessary, engineering controls when contamination remains above
applicable ground water standards. An example of an engineering control is a system to treat ground water
contamination.
Indicator and Measurement Unit(s)
The percent of acreage within the block group with CEA/CKEs restrictions.
Rationale
Like Soil Contamination Deed Restrictions, while the establishment of a CEA and/or CKE is protective, the
measures also restrict the overall utility of a given site. In accordance with the findings of the Act, the
Department has determined that the presence of multiple such restricted sites in an overburdened
community is an impediment to the growth, stability, and long-term well-being of that community. This
stressor is also an indicator of historical and ongoing contamination. See the rationale under “Known
Contaminated Sites” above for more detail on the impacts of ground water contamination.
Stressor Value Calculation Method
• Obtained CEA and CKE
GIS file and isolated CEA/CKE Percent Areas for all block groups data file in
each.
• Applied ArcGIS’ Intersect geoprocessing tool to determine the geometric intersection between the
2021 NJ block groups and applicable tribal areas file and the Groundwater Contamination (CEA/CKA)
Percent Area data file such that only the common features are represented in the output coverage.
• Applied ArcGIS’ Dissolve geoprocessing tool to the output coverage to aggregate features based on
the IDNum field
• Calculated the total groundwater restricted area and divided this value by the total acres of the block
group to determine the percentage of each block group that is groundwater restricted.
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Transfer stations or other solid waste, recycling, and scrap metal facilities
In 2018, New Jersey municipalities and counties generated 23 million total tons of solid waste (including
municipal waste, construction debris and other types of non-municipal waste), with 13.3 million of that waste
recycled and 9.7 million tons disposed of in landfills or waste incinerators. While waste management is
essential to New Jersey’s public and environmental health, solid waste facilities emit air and water pollution,
generate truck and rail traffic-related emissions, and create noise, odor, dust, and sometimes light pollution.
Solid waste landfills can release methane and carbon dioxide into the air for decades, even after they are
permanently closed. Traditional solid waste facilities include landfills, waste incinerators, recycling centers,
and transfer stations. Scrap metal facilities include automotive recycling and scrap metal processing facilities.
Improperly managed scrap metal facilities can contaminate soils, groundwater, and surface waters with
hazardous materials and release refrigerants containing fluorocarbons into the air.
Solid Waste Facilities
“Solid waste facilities” are part of the definition of “environmental or public health stressors” under the New
Jersey Environmental Justice Law. Specifically, the Law’s definition of “facility” includes resource recovery
facilities and incinerators, transfer stations or other solid waste facilities, recycling facilities intended to
receive at least 100 tons of recyclable materials per day, landfills (including, but not limited to those
accepting ash, construction or demolition debris, or solid waste), resource recovery facilities and other waste
incinerators, and medical waste incinerators (except those associated with a hospital or university to process
self-generated regulated medical waste). In State operated sanitary landfills, recycling facilities, and transfer
stations (where solid waste is transferred from collection vehicles to larger trucks or rail cars for long distant
transport to another location for disposal) are all considered in this stressor.
Indicator and Measurement Unit(s)
The density of solid waste facilities per square mile as an indicator of proximity to residents and other
institutions (e.g., schools) within the block group. This is one of six density-based stressors that rely on
location and attribute information from DEP programs to determine how the density calculation impacts a
block group. For solid waste facilities, each facility has a Program Interest (PI) Number (also referred to as
Pref ID Num) or Facility ID. For solid waste, either ID represents a scenario that requires a new record to be
entered. The IDs created by a DEP program are unique to that specific DEP program and are not linked to
another program’s data. As both establish new records based on regulated activities, they present a more
complete picture of a facility’s impact within its density stressor. Therefore, both IDs are utilized for in this
stressor to capture the environmental burden present in a block group.
Rationale
Currently, 12 of New Jerseys 21 counties have operating sanitary landfills. Available landfill capacity in the
State is less than anticipated due to higher levels of waste acceptance, the fact that new landfills are difficult
to site, and the expansion of existing facilities is limited. Eight (8) counties awarded waste disposal contracts
requiring county-generated waste go only to those facilities under contract, while the remaining 13 counties
can send waste to a facility of its choosing. Transfer station capacity is approximately 10 million tons and
There are dozens of transfer stations spread throughout the State.
New Jersey’s recycling industry is highly regulated with dozens of facilities licensed throughout the State to
deal with one or more of the 4 classes of recyclable materials. Class A recyclable materials are those most
people are familiar with; post-consumer materials such as glass, carboard, paper, plastic, and ferrous metals.
Class B recyclable materials include construction and demolition items such as concrete, asphalt, non-
painted/treated wood, tires, non-hazardous (<30,000 ppm) petroleum contaminated soils, and processed
tree and bush materials. Class C recyclable materials are composted matter such as grass, leaves and food
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waste. Class D recyclable materials are various types of universal waste such as used oils, antifreeze, latex
paints, light bulbs, batteries, mercury-containing equipment, and consumer electronics (e-waste).
Available data provides consistent proof that all types of waste facilities are disproportionally sited in low-
income and Black, Indigenous, and people of color (BIPOC) communities.
55
56
In fact, in the United States,
race is the biggest predictor of an individual’s likelihood of living near a hazardous waste site. The waste
industries know that these communities often lack resources to fight their facility siting to protect their
health. Policies like exclusionary zoning and redlining have further concentrated polluting facilities, including
waste facilities, in EJ and BIPOC communities. Studies considering the health effects from living in proximity
to these facilities observe inequalities in exposure and health and represent a case of environmental injustice
as they are the result of social processes and may be prevented, at least partly.
Food waste and other organic matter comprise the largest portion of trash in landfills.
57
As it decomposes,
organic waste creates off-putting odors, attracts disease-carrying rodents, and releases the greenhouse gas
methane. Landfill gases have been associated with increased incidence of respiratory illnesses and various
types of cancer. Additionally, all landfills will eventually leak toxins into the soil and groundwater. These
toxins can contaminate sources of drinking water, and they persist for years, threatening the health of nearby
communities even after landfills are closed.
Stressor Value Calculation Method
• Obtained NJ's Solid & Hazardous Waste facilities
GIS file data.
• Applied ArcGIS’ Kernel Density function using the GIS file data as input with the following
parameters:
o Search radius of 1 mile, which is consistent with the distance requirements in Department’s
Environmental and Health Impact Statement requirements
in the Solid Waste rules.
o Grid size of 100 ft.
This calculated a raster density file.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst
using the created raster surface
file as the input to determine the spatially weighted average number of sites for each 2021 NJ block
groups and applicable tribal areas as the indicator for proximity to each site.
Scrap Metal Facilities
Description
“Scrap yards” are part of the Law’s “environmental or public health stressors” definition, similar to “solid
waste facilities.” The Law also includes scrap metal facilities in its definition of “facility.” Unlike traditional
solid waste facilities that are regulated primarily through one program area of the Department for how they
manage waste, scrap metal facilities are regulated by various Department permitting programs (e.g., some,
but not all, require air and/or stormwater permits) depending on their size and location. As such, this stressor
required identification of these facilities through various data sets and processes. In general, scrap metal
facilities were considered synonymous with establishments primarily engaged in distribution of wholesale or
55
Marco Martuzzi, Francesco Mitis, Francesco Forastiere, Inequalities, inequities, environmental justice in waste
management and health, European Journal of Public Health, Volume 20, Issue 1, February 2010, Pages 21–26,
https://doi.org/10.1093/eurpub/ckp216
.
56
Yang, C. (2021), Q&A: Addressing the Environmental Justice Implications of Waste, Environmental and Energy
Study Institute, May 14, 2021, see
https://www.eesi.org/articles/view/qa-addressing-the-environmental-justice-
implications-of-waste.
57
Williams, I. (2020), One Man’s Trash is Another’s Burden: Social Justice & Waste Management, Population
Education, February 19, 2020, see
https://populationeducation.org/one-mans-trash-is-anothers-burden-social-
justice-waste-management/.
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retail of used motor vehicle parts (SIC 5015) and those primarily engaged in assembling, breaking up, sorting,
or wholesale distribution of scrap and waste metal (SIC 5093). These facilities were compared to the list of
active NJPDES discharge sites for scrap metal processing, as stormwater management is one of the most
important operational and regulatory issue for these facilities.
Indicator and Measurement Unit(s)
Density of scrap metal facilities per square mile in the block group as an indicator of proximity to residents
and other institutions (e.g., schools). This is one of six density-based stressors that rely on location and
attribute information from DEP programs to determine how the density calculation impacts a block group.
The scrap metal dataset was pulled from NJEMS from multiple DEP programs as discussed in greater detail
below. When data crossed multiple program areas, the Site ID was used to identify duplicate facilities.
Rationale
Metal emissions are generated during outdoor operations in most scrap metal facilities from gas torch
cutting and mechanical cutting methods used to downsize scrap metal for eventual consumption by end
users.
58
Metal torch cutting typically is of most concern because it has the potential to generate inhalable
particles containing toxic heavy metals. However, little information is available about the impact on outdoor
air quality from metal emissions due to torch cutting and associated health outcomes of residents in the
downwind community. More is known about exposures from metal welding and torch cutting from data
obtained in the occupational arena.
In Houston, the Health Department conducted metal recycling facility fence line air monitoring from 2010 –
2012 in response to numerous citizen complaints, and found that at some locations, particularly those with
torch cutting, known carcinogenic metals (e.g., nickel compounds) were detected in the ambient air. Other
metals (e.g., manganese and cobalt) with non-carcinogenic adverse health effects were also detected.
59
A
follow up study using a community-based participatory research method characterized metal emissions in
four environmental justice communities.
60
Those results indicated that metal concentrations were the
highest at the fence line and decreased by 57-70% within 100 meters and reached similar levels to
background at 600 meters. After adjusting the measured data for meteorological parameters and operating
hours, estimated inhalation cancer risks ranged from 0.12 cases to 24 cases in 1 million people and hazard
index values ranged from 0.04 to 11.
Based on the nature of industrial activity and operations at scrap metal processing and recycling sites, there
is potential for surface and/or ground water contamination from stormwater runoff.
61
Pollutants are
discharged to surface water if stormwater is exposed to industrial activity on the site and is then discharged
to surface water. Likewise, pollutants are discharged to ground water if industrial activity is exposed to
stormwater and pollutants are mobilized downward as stormwater infiltrates into ground. The volume and
quality of stormwater discharges will depend on a variety of factors, including the outdoor activities at the
facility (e.g., material storage, loading/unloading, vehicle maintenance), extent of impervious surfaces, type
of ground cover, and duration and intensity of precipitation. Stormwater quality can also vary depending on
the effectiveness and implementation of Best Management Practices (BMPs) as well as the performance of
any pollution prevention and/or treatment methods.
58
Symanski, E., An Han, H., Hopkins, L. et al. Metal air pollution partnership solutions: building an academic-
government-community-industry collaboration to improve air quality and health in environmental justice
communities in Houston. Environ Health 19, 39 (2020). https://doi.org/10.1186/s12940-020-00590-1
.
59
Ibid.
60
Inkyu Han, Donald Richner, Heyreoun An Han, Loren Hopkins, Daisy James& Elaine Symanski (2020) Evaluation of
metal aerosols in four communities adjacent to metal recyclers in Houston, Texas, USA, Journal of the Air & Waste
Management Association, 70:5,568-579, https://doi.org/10.1080/10962247.2020.1755385
.
61
https://www.nj.gov/dep/dwq/pdf/sm-sm2-fact-sheet-5-16-13.pdf
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Stressor Value Calculation Method
Obtained Scrap Metal Facilities in New Jersey
GIS file.
• Applied ArcGIS’ Kernel Density function using the scrap metal facility GIS file data as the input with
the following parameters:
o Search radius of 1 mile to be consistent with the Solid Waste Facilities stressor.
o Grid size of 100 ft.
This calculated the raster density file.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst
using the created raster surface
file as the input to determine the spatially weighted average number of sites for each 2021 NJ block
groups and applicable tribal areas as the indicator for proximity to each site.
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Point-sources of water pollution
including, but not limited to, water pollution from facilities or combined sewer overflows
New Jersey’s surface waters, including rivers, streams, and lakes, provide numerous functions for the citizens
of the state, including potable water, crop irrigation, aquatic life habitat and recreation. However, urban and
agricultural pollution continues to threaten water quality. Since the passage of the Clean Water Act in 1972,
Federal, State, and local governments have invested billions of dollars to reduce pollution entering surface
water sources. Still, surface water ecosystems are fragile, and can undergo rapid environmental changes from
exposure to external effects from the atmosphere, or their watershed or groundwater. Human activities
often accelerate these changes.
62
New Jersey’s Surface Water Quality Standards (SWQS) are designed to protect the quality of New Jersey’s
surface waters and ensure they are suitable for all existing and designated uses, including drinking water
supply, fish consumption, shellfish resources, propagation of fish and wildlife, recreation, agriculture, and
industrial water supply.
63
The SWQS objectives are met through various Department programs include the
New Jersey Pollutant Discharge Elimination System (NJPDES) discharge to surface water permits, derived
effluent limits for discharge of remediated groundwater to surface water, Total Maximum Daily Load (TMDL)
program, Water Quality Assessment program and water compliance and enforcement.
Surface Water
Description
Every two years, New Jersey conducts a Statewide assessment of the State’s surface water quality and
publishes the results in New Jersey's Integrated Water Quality Assessment Report
. As its name suggests, the
report employs an integrated approach to assessing water quality by evaluating water monitoring data and
other information collected from numerous sources throughout the state to determine the health of New
Jersey’s surface water regions. In addition, each report includes a comprehensive assessment of one of the
State’s five water regions (i.e., Atlantic Coastal, Raritan, Lower and Upper Delaware and Northeast) on a
rotating basis. This integrated water quality assessment process helps determine if water quality conditions
have changed over time; determine if water quality standards are met and if designated uses, such as
recreation and water supply, are fully supported; identify causes and sources of water quality impairment;
and develop restoration strategies for impaired waters and protection strategies for healthy waters. While
the integrated water quality assessment process evaluates if all freshwaters fully support the drinking water
supply use, it does not assess drinking water quality.
Indicator and Measurement Unit(s)
To analyze this stressor, the Department utilizes water quality results from the 2018/2020 Integrated Report
at the Assessment Unit (AU) level. The AU is determined by the United States Geological Service (USGS)
Hydrologic Unit Code 14, or HUC14 (where 14 indicates the number of digits in the code), for delineating and
identifying drainage systems and watershed boundaries. For each AU, all station parameter results (i.e.,
chemicals or pollutants tested) were aggregated to determine if the General Aquatic Life Use designated use
was supported (that is, in attainment).
If an AU included more than one station, the results for each parameter were aggregated with the ‘worst
case’ station assessment representing the AU (i.e., if any of the stations are impaired for a parameter, then
the parameter is impaired (e.g., in nonattainment) at the AU level). If some stations were fully supported for
a parameter but others had insufficient data, then the parameter was considered fully supported (e.g., in
62
https://www.usgs.gov/special-topics/water-science-school/science/lakes-and-reservoirs?qt-
science_center_objects=0#qt-science_center_objects
63
https://www.state.nj.us/dep/wms/bears/swqs.htm
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attainment). The 2018/2020 Integrated Report covered 958 AUs, over 19,000 miles of rivers and streams,
48,000 acres of lakes, ponds, and reservoir, 950,000 acres of wetlands, 610 square miles of estuaries, 127
miles of coastline, and 450 square miles of ocean. The indicator is the percent of designated uses in
nonattainment.
Rationale
Surface water quality is the key to a healthy ecosystem and safe public recreation. Water quality parameters
such as concentrations of pathogenic bacteria (e.g., Enterococcus and E. coli) and dissolved oxygen are used
to understand how swimmable and fishable surface waters are when assessed against federal recreational
water quality recommendations and guidance. Excess nitrogen, phosphorus and sediment pollution has
resulted in algae blooms, beach closures, fish consumption advisories and dead zones.
64
New Jersey is
divided into five water regions
, with the Northeast and Raritan regions having the most urban and
industrialized settings.
New Jersey’s long history of industrial activity has left a legacy of toxic surface water contaminants such as
polychlorinated biphenyls (PCBs), heavy metals (e.g., mercury), pesticides, and polyaromatic hydrocarbons
(PAHs)
65
. Some of these toxins are particularly troubling because they persist in the environment for great
lengths of time and can bioaccumulate in the tissues of fish, aquatic plants, and wildlife, existing in greater
quantities higher up the food chain.
66
While statewide metals and toxins discharge into waterbodies is drastically reduced, legacy issues still impact
some areas of the state where metals remain in the sediment.
67
During storms and high flow, these
sediments can become resuspended in the water column, elevating metal levels. However, in the Raritan
region, metal levels remain low even during high flow events indicating clean sediment and/or metals that
are buried too far below the sediment for resuspension.
Communities of color, low-income communities, tribes, and other indigenous peoples depend on healthy
aquatic ecosystems and the fish and aquatic plants and wildlife that these ecosystems support to a greater
extent and in different ways than does the general population.
68
These resources are consumed and used to
meet nutritional and economic needs, and for many there are no real alternatives to eating and using fish
and aquatic plants and wildlife; it is entirely impractical to “switch” to “substitutes” when the fish and other
resources on which they rely have become contaminated.
For some groups, these resources are also consumed or used for cultural, traditional, or religious purposes.
For members of these groups, the conventional understandings of the “health benefits” or “economic
benefits” of catching, harvesting, preparing, and eating fish and aquatic plants and wildlife do not adequately
capture the significant value these practices have in their lives and the life of their culture. The harms caused
by aquatic habitat degradation and fishery depletion also have a generational toll, impeding the transfer of
64
Steinzor, r., Verchick, R., Vidargas, & Huang Y. (2012), Environmental Justic and Nutrient Trading, Center for
Progressive Reform Briefing Paper No. 1208, August 2012, see
https://cpr-
assets.s3.amazonaws.com/documents/WQT_and_EJ_1208.pdf
65
Lodge, J., Landeck Miller, R.E., Suszkowski, D., Litten, S., Douglas, S. 2015. Contaminant Assessment and
Reduction Project Summary Report. Hudson River Foundation. New York, NY, see
https://www.hudsonriver.org/article/contaminants
66
US Environmental Protection Agency (EPA) ( 2002), Fish Consumption and Environmental Justice, November
2002, see https://www.epa.gov/sites/default/files/2015-02/documents/fish-consump-report_1102.pdf
67
https://njdep.maps.arcgis.com/apps/MapSeries/index.html?appid=5d2d107d80b54eb48450a7d7c7248c73
68
US Environmental Protection Agency (EPA) ( 2002), Fish Consumption and Environmental Justice, November
2002, see https://www.epa.gov/sites/default/files/2015-02/documents/fish-consump-report_1102.pdf
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ecological knowledge, customs and traditions surrounding harvest, preparation, and consumption of aquatic
resources.
Stressor Value Calculation Method
• Obtained NJ's Surface Water Nonattainment
GIS file.
• Calculated the percent of impaired designated uses for each HUC 14 by dividing the number of
impaired designated uses by the total number of assessed designated uses applicable. If a designated
use did not apply to a waterbody or there were insufficient data to complete an assessment, it was
eliminated from the calculations (e.g., shellfish harvesting is limited to saline waters, so if there was
insufficient data for shellfish harvesting in a freshwater water body, it was eliminated from the
calculation). The higher the percentage, the worse the overall water quality. The results are a short-
term ‘snapshot’ of water quality conditions. The latest 5 years of data was used to determine if
waterbodies supported their designated uses.
• Applied ArcMap’s Polygon to Raster tool
to convert the HUC percent impaired data into 100 ft. raster
data using percent uses not in attainment as pixel value.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst using the created raster surface
file as the input to determine the spatially weighted average of nonattainment surface waters for
each
2021 NJ block groups and applicable tribal areas as the indicator for percent impaired.
Combined Sewer Overflows
Description
Twenty-one (21) of New Jersey’s oldest communities have combined sewer systems that collect rainwater
runoff, domestic sewage, and industrial wastewater into one pipe, rather than having separate systems for
wastewater and stormwater.
69
These combined systems are remnants of the country’s early infrastructure
and are often in urban areas that overlap with low-income areas or communities of color.
70
Under normal
conditions, these systems transport all the wastewater collected to a sewage plant for treatment, then
discharge the treated water into a water body.
However, the volume of wastewater can sometimes exceed the system’s capacity, particularly during heavy
rainfall or snowmelt events, creating an “overflow of untreated stormwater and wastewater” from their
outfalls directly into nearby streams, rivers, and other water bodies. Combined sewer overflows, or CSOs, can
contain untreated or partially treated human and industrial waste, toxic materials, and other debris, and
often contain high levels of total suspended solids, pathogens, nutrients, oxygen-demanding organic
compounds, oil, and grease. These contaminants and pollutants impair water quality and the recreational use
of urban waterways, resulting in beach closures, contamination of local drinking water sources and impacts
on aquatic ecosystems.
71
With climate impacts expected to increase regional average annual precipitation by
4 percent to 11 percent by 2050, as well as create more intense and frequent precipitation events, existing
CSOs could negatively impact more people more frequently as flooding covers larger areas.
72,73
69
https://www.nj.gov/dep/dwq/cso-basics.htm
70
https://www.epa.gov/npdes/combined-sewer-overflows-csos
71
https://www.nj.gov/dep/dwq/cso-basics.htm
72
New Jersey Department of Environmental Protection (NJDEP) (2020), 2020 New Jersey Scientific Report of
Climate Change, June 30, 2020, Chapter 4.2 Precipitation, see
https://www.nj.gov/dep/climatechange/docs/nj-
scientific-report-2020.pdf#page=56.
73
DeGaetano, A. 2021. Projected Changes in Extreme Rainfall in New Jersey based on an Ensemble of Downscaled
Climate Model Projections. Prepared for NJ Department of Environmental Protection. Trenton, NJ.
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Indicator and Measurement Unit(s)
The presence of any Combined Sewer System in the block group.
Rationale
Over 700 U.S. cities, mostly on the East Coast, Great Lakes, and Pacific Northwest, continue to rely on
combined sewer systems.
74
Research has determined CSO from these systems is a significant source of
polycyclic aromatic hydrocarbons, organochlorine compounds, nutrients, and chemical oxygen demand. In
addition, CSOs are a potential source of wastewater micropollutants (WMPs), trace levels of synthetic organic
substances (e.g., caffeine, pharmaceuticals) released into receiving waters from human activity, with
substantially elevated WMP concentrations occurring in urban waters following CSO discharges.
CSO discharge can carry bacteria, intestinal worms, protozoa, and viruses. Contact, inhalation, or ingestion of
CSO discharge can cause diarrhea and nausea, as well as a variety of infections, including ear, respiratory, and
skin/wound.
75
In worst-case scenarios, people exposed to these discharges can also contract life-threatening
diseases, including cholera, dysentery, infectious hepatitis, and severe gastroenteritis.
New Jersey currently has individual CSO permits covering 211 outfalls in 21 jurisdictions
. Because combined
sewer systems are common in older, urban areas, there tends to be significant overlap with communities that
are already environmentally overburdened. In New Jersey, CSO-permitted areas include known
overburdened communities like Newark, Elizabeth, Patterson, Camden, and Trenton. An estimated 23 billion
gallons of a mixture of raw sewage and stormwater are dumped annually into New Jersey’s waterways
because of these CSOs.
76
Over time, as the urban population density in these areas have increased, with
more demand placed on infrastructure, CSO events have also increased.
77
Increased frequency and intensity
of storms driven by climate change make matter worse. While the goal of CSO permits is to reduce or
eliminate the CSOs by implementing Nine Minimum Controls (NMC) and developing a
Long Term Control Plan
(LTCP), plan estimates will cost billions of dollars over many years to implement.
Stressor Value Calculation Method
• Obtained New Jersey's CSO
GIS file.
• Applied ArcMap’s Intersect geoprocessing tool to identify the number of CSOs within a given block
group.
• Applied ArcMap’s Dissolve geoprocessing tool to find the count of CSOs in each block group
• Any block group with at least one CSO outfall is above the GPCGPC.
74
P. J. Phillips, A. T. Chalmers, J. L. Gray, D. W. Kolpin, W. T. Foreman, and G. R. Wall
Environmental Science & Technology 2012 46 (10), 5336-5343
DOI: 10.1021/es3001294 https://pubs.acs.org/doi/10.1021/es3001294#
75
Malmassari, J. (2019), The Dangers of Combined Sewere Overflows, Municipal Sewer and Water, April 4, 2019,
see https://www.mswmag.com/online_exclusives/2019/04/the-dangers-of-combined-sewer-overflows_sc_003d9
.
76
https://sewagefreenj.org/challenge/
77
Fu, X., Goddard, H., Wang, X., & Hopton, M. E. (2019). Development of a scenario-based stormwater
management planning support system for reducing combined sewer overflows (CSOs). Journal of environmental
management, 236, 571–580. https://doi.org/10.1016/j.jenvman.2018.12.089
.
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May cause potential public health impacts
Stressors in this category are indicators of indirect environmental and public health impacts, often referred to
as quality-of-life impacts, borne by New Jersey’s overburden communities. These include the physical and
mental stress of living in proximity to a multitude of commercial and industrial sites, poor water quality, the
effects of aging housing stock on health, and impact of limited access to natural features (e.g., urban forests)
and high quality recreational and open space resources (e.g., parks, wildlife areas).
The inverse of this last stressor is an abundance of impervious surface (e.g., roadways, parking lots,
sidewalks), which has increased inland flooding in our urban areas. Flooding will only get worse as sea levels
rise and climate-driven storms become more frequent and intense. Beyond the metrics of environmental or
public health stress are social considerations, such as education and employment levels, which act as “threat
multipliers” in our overburdened communities, further straining their resources and making environmental
and public health threats more difficult to prevent or manage.
Drinking Water
Description
In 2003, the UN Committee on Economic, Social and Cultural Rights declared access to clean water a human
right, noting that it was indispensable for leading a life of human dignity, and a prerequisite for the
realization of other human rights.
78
A 2017 review of the Environmental Protection Agency’s (EPA) Safe
Drinking Water Information System (SDWIS) federal reporting estimated that 63 million Americans had
exposure to potentially unsafe water in the past decade.
79
Unclean water can cause serious and costly health
issues, and studies have found that poor and minority communities in the U.S. are disproportionally affected
by polluted water sources.
Indicator and Measurement Unit(s)
Most New Jersey residents get their drinking water through a public water system, with only 11percent of
residents using private wells.
80
State and Federal regulations require periodic water quality monitoring and
violation notifications for community water supplies. The State collects this information and annually reports
to the EPA on violations of the national primary drinking water regulations with respect
to Maximum
Contaminant Level (MCL), Action Level Exceedances (ALE) and Treatment Techniques (TT).
While private well owners are responsible for monitoring the quality of their water and maintaining their
wells, the NJ Private Well Testing Act (PWTA)
requires testing and disclosure of water quality during real
estate transactions on properties with potable private wells. It further requires landlords to test their well
water once every 5 years. The data generated by the PWTA is provided to the homeowners/tenants and sent
to the NJDEP. About 25% of potable wells in New Jersey have been tested through the PWTA. The counts of
community drinking water violations or exceedances, or percent of PWTA exceedances were used as the
indicator for drinking water quality throughout the State.
Rationale
Drinking water can become contaminated at the water source as well as in the distribution system after
treatment. Contamination can come from naturally occurring chemicals and minerals, land uses such as
78
UN Committee on Economic, Social and Cultural Rights (CESCR), General Comment No. 15: The Right to Water
(Arts. 11 and 12 of the Covenant), 20 January 2003, E/C.12/2002/11, available at:
https://www.refworld.org/docid/4538838d11.html
[accessed 9 May 2022].
79
https://www.epa.gov/ground-water-and-drinking-water/drinking-water-data-and-reports
80
Dieter CA, Maupin MA, Caldwell RR, et al. Estimated Use of Water in the United States in 2015.; 2018.
https://doi.org/10.3133/cir1441
.
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fertilizers, pesticides, and road salt; manufacturing processes, and more; as well as contaminants leaching
into the treated water as it passes through the distribution system. Contaminated drinking water can lead to
gastrointestinal illness, reproductive problems, and neurological disorders. Specific contaminants that can
cause various health concerns include:
• 1,2,3-Tricloropropane, a persistent manmade substance found in soil fumigants, industrial processes,
and paint removers, is a potent carcinogen and mutagen.
• Arsenic, primarily from naturally occurring minerals in bedrock aquifers of Northern and Central New
Jersey, can increase the risk of lung, bladder, or skin cancer.
• Ethylene Dibromide and 1,2-Dibromo-3-chloropropane, used as pesticides, are also potent
carcinogens and mutagens.
• E. Coliform, infectious microorganisms found in human and animal feces, can cause nausea, vomiting
and diarrhea.
• Radionuclides, such as radium, uranium, and radon, come from the decay of natural rock. Radium
can increase the risk of bone or sinus cancer; uranium can affect kidney function; and radon can
cause lung cancer.
• Mercury, either naturally occurring or from septic tanks, landfills, industrial facilities, or hazardous
waste sites, may result in nervous system or kidney damage.
• Nitrates from the breakdown of human and animal wastes and chemical fertilizers, decrease the
blood’s ability to carry oxygen to organs throughout the body, particularly in infants.
• Volatile organic compounds from septic tanks, gas stations, landfills, and dry cleaning, industrial and
hazardous waste facilities affect the liver, kidney, nervous system, or heart; and increase the risk of
cancer.
Existing studies have found associations between poor drinking water quality and key environmental justice
indicators such as poverty, race/ethnicity indicators. Public water systems that serve communities with lower
median incomes, lower rates of home ownership, and higher proportions of Hispanic or non-white residents
are associated with higher levels of nitrate and arsenic. Health-based violations of the federal Drinking Water
Act are more common in poor communities with higher proportions of Hispanic or African American
residents, while the effects of race and ethnicity were not apparent in more affluent communities.
81
A 2018 study found most initial drinking water violations occurred among systems serving very small (less
than or equal to 3300 inhabitants) and small (3301 to 10,000 inhabitants) populations, and lower
socioeconomic status and minority groups are associated with an increased odd ratio for initial and repeat
drinking water violations.
82
There are a wide range of natural, built, and sociopolitical factors that can cause
and perpetuate these disparities in water quality, reliability, and infrastructure, including poorer source
water quality due to closer proximity to pollution sources and diminished technical, managerial, and financial
capacity to properly manage drinking water.
83
Stressor Value Calculation Method
Obtained the appropriate source data:
81
Schaider, L.A., Swetschinski, L., Campbell, C. et al. Environmental justice and drinking water quality: are there
socioeconomic disparities in nitrate levels in U.S. drinking water?. Environ Health 18, 3 (2019).
https://doi.org/10.1186/s12940-018-0442-6 https://link.springer.com/article/10.1186/s12940-018-0442-6
82
McDonald, Y. J., & Jones, N. E. (2018). Drinking Water Violations and Environmental Justice in the United States,
2011-2015. American journal of public health, 108(10), 1401–1407. https://doi.org/10.2105/AJPH.2018.304621
.
83
Schaider, L.A., Swetschinski, L., Campbell, C. et al. Environmental justice and drinking water quality: are there
socioeconomic disparities in nitrate levels in U.S. drinking water?. Environ Health 18, 3 (2019).
https://doi.org/10.1186/s12940-018-0442-6.
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New Jersey Department of Environmental Protection
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• 3-year (2019-2021) sum of Maximum Contaminant Level (MCL) and/or Treatment Techniques (TT)
violations and/or Action Level Exceedances from annual drinking water violation
Public Drinking
Water reports.
• All private wells tested conducted under the Private Well Testing Act Data from Sept. 2002 to Dec.
2018 (census block tab) with at least one exceedance of a primary standard (arsenic, mercury,
radionuclides (gross alpha indicator), e. coli, and VOCs).
For Community Drinking Water data:
• Created a drinking water purveyor polygon file using a attribute join to link the Public Drinking Water
data to the Public Drinking Water Purveyor
GIS file using purveyor ID number.
• Applied ArcGIS’ Intersect geoprocessing tool to determine the geometric intersection between the
2021 NJ block groups and applicable tribal areas file and the drinking water purveyor polygon file
such that only the common features are represented in the output coverage.
• Applied ArcGIS’ Dissolve geoprocessing tool to the output coverage to select the drinking water area
with the maximum size area in the each block group.
• Used attribute join to link the violation records to the maximum area data.
• For a block group served by a public drinking water system, any drinking water violation or
exceedance is above the GPC.
For PWTA violations, see GPC discussion above.
For those block groups served by both a public water system and 5 or more private wells, if both the public
water and PWTA stressors are above the GPC, the values were not summed, but instead the block group was
given an overall value of 1 (yes) for combined drinking water stressor.
Potential Lead Exposure
Description
Lead-based paint and lead contaminated dust are the most hazardous sources of lead for U.S. children.
84
Lead-based paints were banned for use in U.S. housing in 1978. Therefore, all houses built before 1978 are
likely to contain some lead-based paint. The deterioration of this paint elevates levels of lead-contaminated
house dust that can be either ingested or inhaled by residents. Children under the age of 6 years old are most
at risk because they are growing so rapidly and tend to put their hands or other objects which may be
contaminated with lead dust into their mouths. Children living at or below the poverty line or children of
color who live in older housing are at even greatest risk.
Indicator and Measurement Unit(s)
Age of housing (percent of houses older than 1950 in the block group) is used as a surrogate for potential
lead paint exposure.
Rationale
Lead is a heavy metal widely used in industrial processes and consumer products. When absorbed into the
human body, lead can have damaging effects on the brain and nervous system, kidneys, and blood cells. Lead
exposure is particularly hazardous for pre-school children because it can disrupt brain development, causing
lowered intelligence, hyperactivity, attention deficits, developmental problems, and decreased hearing.
There is no safe level of lead in the blood; even trace amounts can damage brain cells.
85
International pooled
84
https://www.cdc.gov/nceh/lead/prevention/children.htm
85
Yeter, D., Banks, E. C., & Aschner, M. (2020). Disparity in Risk Factor Severity for Early Childhood Blood Lead among
Predominantly African-American Black Children: The 1999 to 2010 US NHANES. International Journal of Environmental Research
and Public Health, 17(5), 1552. MDPI AG. Retrieved from http://dx.doi.org/10.3390/ijerph17051552.
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New Jersey Department of Environmental Protection
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analysis of children 6 to 24 months of age observed a loss of 1.88 intelligence quotient (IQ) points for each
doubling of blood lead levels beginning at 2 micrograms per deciliter (µg/dL), and recent meta-analysis
demonstrated that even slight increases in blood lead levels below 3 µg/dL are still significantly associated
with a greater risk of presenting with symptoms of attention-deficit/hyperactivity disorder (ADHD) among
children 5 to 12 years of age.
The U.S. Centers for Disease Control and Prevention (CDC) estimates that children with blood lead levels at or
above the blood lead reference value of 3.5 µg/dL represent the top 2.5 percent of U.S. children aged one to
five tested for lead in their blood (when compared to children who are exposed to more lead than most
children).
86
Infants and preschool-aged children are at a higher exposure risk primarily due to their increased
body surface area, increased heart and respiratory rates, the ingestion and inhalation of contaminated dust
or soil from greater hand-to-mouth activity, pica, crawling, and their low stature to the ground.
A 2020 study found that black race is the second strongest predictor for increased blood lead during early
childhood after the risk of living in pre-1950 housing.
87
Statistically, black racial disparity continues to
significantly persists within each of the other examined risk factors, such as poverty, education, and
presences of smokers in the home, even after correcting for those other risk factors and variables. the most
pronounced disparities were observed for Black children two to three years of age, those living in poverty or
older housing built from 1950 to 1977, and those with a primary guardian who had not received a high school
diploma or GED.
Stressor Value Calculation Method
• Obtained the 2021 New Jersey American Community Survey (ACS) summary data
(New
Jersey_Tracts_Block_Groups_Only.zip) and isolated the Housing Age field data.
• Used the following data fields from Table Summary File Sequence 119 (e20215nj0119000):
o 'B25034_001': Total Housing
o 'B25034_010': Built 1940 to 1949
o 'B25034_011': Built 1939 or earlier
• Indicator calculated as:
o Built before 1950 = Built1940to1949 + Built1939orearlier
o Percent calculated as (Built before 1950/Total Housing) *100
Lack of Recreational Open Space
Description
As the most densely populated state in the Nation with a still growing population, New Jersey’s open space is
a target for increasing development. However, recognizing the environmental, social, and economic benefits
of open space, New Jersey’s government agencies and nonprofit land trusts have preserved 34 percent of the
State’s land (including farmland), an amount nearly equivalent to the percentage of developed land (33
percent). Open space protects water resources; preserves biodiversity and wildlife habitats; creates
greenways; enhances urban centers; and supports recreational opportunities. In addition, publicly available
open space encourages walking, biking, and other outside physical activity that, according to the CDC, helps
people live longer and have lower risks for heart disease, stroke, type 2 diabetes, depression, and some
cancers.
86
https://www.cdc.gov/nceh/lead/docs/lead-levels-in-children-fact-sheet-508.pdf
87
Yeter, D., Banks, E. C., & Aschner, M. (2020). Disparity in Risk Factor Severity for Early Childhood Blood Lead
among Predominantly African-American Black Children: The 1999 to 2010 US NHANES. International Journal of
Environmental Research and Public Health, 17(5), 1552. MDPI AG. Retrieved from
http://dx.doi.org/10.3390/ijerph17051552
.
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New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Indicator and Measurement Unit(s)
The population per acre of open space (i.e., municipal, county, and nonprofit parkland open space and
parkland encumbered by the NJDEP Green Acres Program and reported in the
Recreational Open Space
Inventory (ROSI) database within one quarter mile (approximately equivalent to a 10-minute walk) of the
block group.
Rationale
Open space and parkland are proven to benefit people’s health. Trees filter the air and provide shade on hot
days; wetlands and marshes clean water and protect communities from floods and storm surges; parks
provide safe havens where children can play and connect, and trails allow people to exercise outdoors.
However, access to nature is unequal for lower-income communities and communities of color compared to
affluent white communities.
A recent report from the Center for American Progress and the Hispanic Access Foundation found that
communities of color experience “nature deprivation” at three times the rate of white Americans. According
to the report, 74% of communities of color live in nature-deprived areas, with Black communities
experiencing the highest levels of deprivation.
88
Similarly, 2019 study by the University of British Columbia
examined 10 U.S. cities, including New York, Chicago, and Houston, and found that Latino and Black
communities have less access to urban nature than white communities.
89
Urban residents with lower access
to open space and parklands are also those who are most likely to experience poor public health outcomes
that could be mitigated by adequate exposure to urban open space.
A growing body of evidence shows that access to green space in urban areas brings considerable benefits to
the health and well-being of city residents. These benefits may include improved cognitive development and
functioning
90
, reduced severity of ADHD
91
, reduced obesity
92
, and positive impacts on mental health
93
. The
article published in the December 2008 issue of the American Journal of Preventive Medicine reported that
children living in inner city neighborhoods with higher “greenness” experienced lower weight gains compared
to those in areas with less green space. This is critical, as childhood obesity can lead to Type 2 diabetes,
88
Rowland-Shea, J., Doshi, S., Edberg, S., & Fanger R. (2020), The Nature Gap: Confronting Racial and Economic
Disparities in the Destruction and Protection of Nature in America, Center for American Progress, July 2020, see
https://americanprogress.org/wp-content/uploads/2020/07/The-Nature-
Gap4.pdf?_ga=2.198324143.1881431880.1652201468-2089605842.1637606711
89
Lorien Nesbitt, Michael J. Meitner, Cynthia Girling, Stephen R.J. Sheppard, Yuhao Lu,
Who has access to urban vegetation? A spatial analysis of distributional green equity in 10 US cities,
Landscape and Urban Planning, Volume 181, 2019,Pages 51-79,ISSN 0169-2046,
https://doi.org/10.1016/j.landurbplan.2018.08.007
.
90
de Keijzer C, Gascon M, Nieuwenhuijsen MJ, Dadvand P. Long-Term Green Space Exposure and Cognition Across
the Life Course: a Systematic Review. Curr Environ Health Rep. 2016 Dec;3(4):468-477.
https://doi.org/10.1007/s40572-016-0116-x
. .
91
Faber Taylor, A, Kuo, F.E. (Ming). Could Exposure to Everyday Green Spaces Help Treat ADHD? Evidence from
Children’s Play Settings. Applied Psychology: Health and Wellbeing, Vol. 3 Issue 3, Nov. 2011: 281-303.
https://doi.org/10.1111/j.1758-0854.2011.01052.x
.
92
“Neighborhood Greenness and 2-Year Changes in Body Mass Index of Children and Youth” by Janice F. Bell, PhD,
MPH, Jeffrey S. Wilson, PhD, and Gilbert C. Liu, MD, MS. The commentary is “Decrease in Activity From Childhood
to Adolescence: Potential Causes and Consequences” by Nicholas J. Wareham, MBBS, PhD, Kirsten Corder, PhD,
and Esther M. F. van Sluijs, PhD. Both appear in the American Journal of Preventive Medicine, Volume 35, Issue 6
(December 2008).
93
Rugel E. and Ward H. Green Space and Mental Health: Pathways, Impacts and Gaps. National Collaborating
Centre for Environmental Health. Mar. 25, 2015, see
https://ncceh.ca/documents/evidence-review/green-space-
and-mental-health-pathways-impacts-and-gaps.
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asthma, hypertension, sleep apnea and emotional distress. Obese children are likely to become obese adults,
experiencing more cardiovascular disease, high blood pressure and stroke and incurring higher healthcare
costs. Finally, the impact of urban open space and parkland exposure on the health and well-being of
marginalized communities may become even more critical as climate change worsens, raising temperatures
and increasing flooding.
Stressor Value Calculation Method
• Obtained New Jersey’s Open Space polygon
GIS files.
• Determined residential land use areas in each block group by selecting residential land use from land
use land cover 2015 and applied the Intersect geoprocessing tool to determine the geometric
intersection between that data and the 2021 NJ block groups and applicable tribal areas file such
that only the common features are represented in the output coverage.
• Used the ArcMap buffer tool to add ¼ mile buffers to the residential land use areas for each block
group.
• Applied ArcGIS’ Dissolve geoprocessing tool to the output coverage to aggregate features based on
number of acres of open space within ¼ mile of the block group.
• Used this information to calculate population density by dividing the population in the block group
by the number of open space acres within ¼ mile.
Lack of Tree Canopy
Description
Tree canopy refers to the layer of tree leaves, branches, and stems that provide tree coverage of the ground
when viewed from above.
94
The amount of tree canopy coverage is typically a reflection of a variety of
factors, including intentional planning and investment. Tree canopies have numerous benefits, particularly in
urban settings, including reducing summer peak temperatures and air pollution, enhancing property values,
providing wildlife habitat, and providing aesthetic benefits. In addition, carbon sequestration, the process by
which atmospheric carbon dioxide is taken up by trees, grasses, and other plants through photosynthesis and
stored as carbon in biomass (trunks, branches, foliage, and roots) and soils, helps to offset carbon dioxide
emissions in the atmosphere from deforestation, forest fires, and fossil fuel combustion.
95
Studies
throughout the United States have repeatedly shown that most communities are losing tree canopy through
a wide range of threats, including insects, disease, natural disasters and development.
96
Indicator and Measurement Unit(s)
The spatially weighted average of lack of tree canopy within the block group.
Rationale
Urban Tree Canopy (UTC) cover is widely regarded as an environmental good or amenity.
97
UTC cover as an
environmental amenity includes direct perceived benefits, or ecosystem services, to people and
neighborhoods where UTC cover is found, including regulation of regional climate and water cycles. In
addition to UTC, “greenness”, as an indicator of vegetation cover, has been associated with reductions in
childhood obesity rates, decreasing cognitive fatigue, improve worker attitudes on the job, and reduce stress
as well as feelings of anger, depression, or anxiety. UTC cover is also associated with improved aesthetics,
noise reduction, and stronger social cohesion and community empowerment. Therefore, lack of UTC cover
denies those benefits to the community.
94
https://www.nrs.fs.fed.us/urban/utc/
95
https://www.fs.fed.us/ecosystemservices/carbon.shtml
96
https://www.nrs.fs.fed.us/urban/utc/
97
Schwarz K, Fragkias M, Boone CG, Zhou W, McHale M, et al. (2015) Trees Grow on Money: Urban Tree Canopy
Cover and Environmental Justice. PLOS ONE 10(4): e0122051. https://doi.org/10.1371/journal.pone.0122051
.
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A 2015 study found that high-income neighborhoods in selected cities are more likely than low-income
neighborhoods to have high tree canopy cover. An earlier 2011 study show that white areas in Miami-Dade
County had greater tree density, greater tree and shrub cover, more tree diversity, and the greatest amount
of energy savings due to trees.
98
However, Hispanic areas had greater individual tree leaf area index (LAI),
more trees in excellent condition, more impervious surfaces, and more air pollution removal than the other
two areas groups.
African American areas had the lowest tree density and LAI, lowest tree and shrub cover and diversity, and
received the least amount of ecosystem services in terms of air pollution removal and energy savings.
However, African Americans had the greatest amount of potential planting space for trees and the greatest
percentage of street trees. The results of this study show that even when some urban forest structure
indicators (i.e., leaf area) are not strikingly different among areas, the ecosystem services provided by trees
can be limited and inequitable, suggesting the uneven distribution of UTC cover might be influenced by
differing levels of control over the physical environment due to housing tenure.
Stressor Value Calculation Method
• Obtained the 2016 US Forest Service “Analytical” Tree Canopy Cover (TCC) Dataset
(file name CONUS 2016 – zip) which is already a raster file.
• Created a mirror image raster file by subtracting this file from 100 to represent Lack of Tree Canopy
Cover.
• Erased water and salt marsh land uses in Land Use/Land Cover 2015 from
2021 NJ block groups and
applicable tribal areas.
• Applied Zona Statistics as a Table function in ArcMap Spatial Analyst using the Lack of Tree Canopy
raster file as the input raster and the block groups with water and salt marshes removed as the
feature zone to determine the spatially weighted average for each block group as the indicator for
percent of lack of tree cover.
Impervious Surface
Description
Impervious surfaces are areas covered in materials that do not allow water to soak into soil, such as
buildings, sidewalks, and roadways. These areas capture heat, creating what is known as the “heat-island
effect”, worsen flooding impacts, transport surface pollutants that impact water quality, and intensify the
impacts of drought by preventing groundwater refresh from occurring. Essentially an inverse of UTC cover,
research shows that precent of impervious surface is positively associated with residential density and
negatively associated with household income, meaning its typically higher in lower income areas that have
less heat-adaptive capacity (e.g., no air conditioning, rental properties without authority to take adaptive
steps such as tree planting).
99
Indicator
Percent of impervious surface in a block group.
98
Flocks, J.; Escobedo, F.; Wade, J.; Varela, S.; Wald, C. Environmental justice implications of urban tree cover in
Miami-DadeCounty, Florida. Environ. Justice 2011, 4, 125–134, see
https://www.researchgate.net/publication/228268481_Environmental_Justice_Implications_of_Urban_Tree_Cove
r_in_Miami-Dade_County_Florida.
99
Drescher M. (2019). Urban heating and canopy cover need to be considered as matters of environmental justice.
Proceedings of the National Academy of Sciences of the United States of America, 116(52), 26153–26154. Advance
online publication. https://doi.org/10.1073/pnas.1917213116
.
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Rationale
Impervious surfaces create several environmental and public health threats, including exacerbating heat
impacts, worsening flooding, transporting surface pollutants into water sources deteriorating water quality,
and intensifying droughts by preventing groundwater refresh from occurring. Each of these threats impacts
overburdened communities more acutely. For example, various studies have looked at the characteristics of
populations in certain urban settings that are more vulnerable to heat-related mortality. Fine-scale, remotely
sensed data shows that impervious surfaces are important predictors of intra-urban variation in temperature,
and the degree of impervious surfaces generally increases with population density.
100
Several authors have also found that the extent of impervious surface is greater in neighborhoods with low
socioeconomic status and a high proportion of minority residents, although these studies have been limited
to a single U.S. city or state. A 2006 study of neighborhood microclimates in Phoenix that looked at
population, community, and biophysical characteristics to simulate an outdoor human thermal comfort index
(HTCI) (an indicator of heat stress) as a function of local climate variables found that lower socioeconomic
and ethnic minority groups were more likely to live in warmer neighborhoods with greater exposure to heat
stress.
101
Further, the study found that the vulnerability of these warmer neighborhoods was exacerbated by
a resident’s lack of adequate social and material resources to cope with extreme heat.
Studies that have looked at the connection between water quality and the percentage of land cover in a
watershed have correlated high stream concentrations of inorganic nitrogen and phosphorus, two of the
three main ingredients in artificial fertilizer spread, with both urban and agricultural land use.
102
A 2003 study
from the University of Connecticut indicated that the percent of impervious land in a watershed is
significantly related to all water characteristics
103
, and some studies suggest that paving over anything above
10 to 20 percent of the landscape negatively impacts water quality. For comparison, estimates of the
percentage of impervious surface in urban areas range from 50 percent of moderately dense suburban
dwellings to over 94 percent in Mid-Manhattan West. Flooding exacerbates water contamination,
particularly in areas where CSOs are overwhelmed resulting in human contact with raw sewage.
Stressor Value Calculation Method
Due to the size of the impervious surface files, obtained each county file separately off DEP’s Open Data site
and then combine into a complete state file. Searched for “Impervious Surface” to find the county files.
• Erased water and salt marsh land uses in Land Use/Land Cover 2015 from
2021 NJ block groups and
applicable tribal areas.
• Applied ArcGIS’ Intersect geoprocessing tool to determine the geometric intersection between the
block groups with water and salt marsh land uses removed and impervious cover data file to link the
amount of impervious surface to each block group.
• Applied ArcGIS’ Dissolve geoprocessing tool to aggregate features to calculate acres of impervious
surface each block group.
• Calculated the percent impervious surface as acres of impervious surface/acres in block group
excluding water and salt marshes.
100
Jesdale, B. M., Morello-Frosch, R., & Cushing, L. (2013). The racial/ethnic distribution of heat risk-related land
cover in relation to residential segregation. Environmental health perspectives, 121(7), 811–817.
https://doi.org/10.1289/ehp.1205919
.
101
Sharon L. Harlan, Anthony J. Brazel, Lela Prashad, William L. Stefanov, Larissa Larsen, Neighborhood
microclimates and vulnerability to heat stress, Social Science & Medicine, Volume 63, Issue 11, 2006,
Pages 2847-2863, ISSN 0277-9536, https://doi.org/10.1016/j.socscimed.2006.07.030
.
102
https://news.climate.columbia.edu/2010/07/13/no-more-pavement-the-problem-of-impervious-surfaces/
103
Center for Watershed Protection (2003), Impacts of Impervious Cover on Aquatic Systems, March 2003, see
https://clear.uconn.edu/projects/TMDL/library/papers/Schueler_2003.pdf
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Flooding (Urban Land Cover)
Description
According to the United States Geological Survey, 1,368 square miles, or 15% of New Jersey’s total area is
made up of water.
104
The 2019 State hazard mitigation plan estimates that 18.65% of the State is in a flood
hazard area.
105
Both estimates of New Jersey’s watercourses and flood hazard areas likely underestimate
potential flooding across the State. Flood damage is, and will continue to be, the most frequent and costly
natural hazard in New Jersey. Flooding, particularly in urban areas with large impervious surfaces that
prevent water absorption, results in property loss, disruptions in electricity transmission that cause problems
for critical infrastructure such as water treatment plants and hospitals, and damage to roads impeding aid,
emergency care, and access to food.
Flooding can also result in loss of life. 2020’s Tropical Storm Ida claimed the lives of 30 New Jerseyeans,
second only to 2012’s Superstorm Sandy for storm-related deaths. According the 2019 State Hazard
Mitigation Plan, with $5.8 billion in total flood insurance claims, New Jersey ranks third in the nation in claims
paid since 1978 in Special Flood Hazard Areas (SFHA). The flood-related hazards most likely to affect New
Jersey are riverine (inland) flooding and coastal flooding.
106
Flooding can occur days after a large storm, or it
can happen much more quickly, such as when streams are subject to flash flooding. The quick timing of flash
flooding increases the risk. Sea-level rise and increases in rain event frequency and intensity driven by climate
change have already increased flooding in New Jersey and will continue to do so. This risk of flooding also
increases during periods of drought when the soil is too dry to absorb large amounts of rain in a short period
of time.
Indicator and Measurement Unit(s)
Percent of urban land area prone to flooding in a block group.
Rationale
While most EJ and flood-related research has focused on post-flood conditions, more recent studies are
taking a pre-flood approach and focusing on vulnerable social groups living in flood prone areas
107, 108, 109, 110
.
Other research has framed flood risks in the U.S. and elsewhere as a question of environmental inequality
104
http://ready.nj.gov/mitigation/pdf/2019/mit2019_section4_State_Profile.pdf
105
https://nj.gov/njoem/mitigation/pdf/2019/mit2019_section5-6_Flood.pdf
106
New Jersey Department of Environmental Protection (NJDEP) (2020), 2020 New Jersey Scientific Report of
Climate Change, June 30, 2020, Chapter 4.2 Precipitation, see
https://www.nj.gov/dep/climatechange/docs/nj-
scientific-report-2020.pdf#page=56
107
Chakraborty et al., Social and Spatial Inequities in Exposure to Flood Risk in Miami, Florida, Natural Hazards
Review, Vol, 15, Issue 3, August 2014, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000140
108
Fielding, J. and Burningham, K. (2005) Environmental inequality and flood hazard, Local Environment, Vol. 10,
Issue 4, https://doi.org/10.1080/13549830500160875
109
Maantay, J., & Maroko, A. (2009). Mapping Urban Risk: Flood Hazards, Race, & Environmental Justice In New
York". Applied geography (Sevenoaks, England), 29(1), 111–124. https://doi.org/10.1016/j.apgeog.2008.08.002
110
Mahbubur Meenar, Richard Fromuth & Manahel Soro (2018) Planning for
watershed-wide flood-mitigation and stormwater management using an environmental justice
framework, Environmental Practice, 20:2-3, 55-67, https://doi.org/10.1080/14660466.2018.1507366
.
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and injustice
111,
112,
113
to better understand the why poor and marginalized communities are often more
severely impacted than other communities.
The awareness of flood risk and knowledge of how best to respond in the event of a flood varies by socio-
economic group, with those lower socio-economic groups having lower awareness of risk than those in
higher socio-economic groups.
114
. In addition, poorer people are more likely to occupy housing which by its
nature is less resilient to flooding (e.g., older, and mobile homes) and less able to afford products which can
be installed to protect homes against some sorts of flood.
115
Defending the home in this way is also rarely
available to those who rented properties.
Research shows that the health impact of flooding varies with preexisting health status, which is often worse
in underprivileged neighborhoods. These impacts range from the immediate risk of injury and death to
diverse symptoms associated with the proximity of flood water and living in damp accommodations
(exacerbation of asthma, skin rashes, gastroenteritis
116
to longer term psychological problems including panic
attacks, agoraphobia, depression, tiredness, stress, and anxiety
117
118
119
120
). Specifically, garbage and
sewage as well as other contaminant caught in flood waters raise the risk of waterborne illness. A flood can
also uproot trees, float motor vehicles, and collapse other structures in its path, turning debris into
projectiles that lead to further damage downstream. Flood water can also seep into buildings, affecting
sewer pipes and causing indoor mold growth.
Stressor Value Calculation Method
• Obtained the Flooding (Urban Land Cover) Layer
. This is a unique new GIS file that includes the
acres of urban land use flooded in each block group by combining aspects of three existing GIS
data sources
(NJ Land Use 2015 (Urban type) Source Data, Total Climate Adjusted Flood Elevation,
and FEMA 0.2% (500 Year) Flood Hazard Areas Source Data) as follows:
111
Bullard, R.D. and Wright B. (2009), Race, Place, and the Environment in Post-Katrina New Orleans, Chapter 1,
DOI: 10.4324/9780429497858-1, see
https://www.taylorfrancis.com/chapters/edit/10.4324/9780429497858-
1/race-place-environment-post-katrina-new-orleans-robert-bullard-beverly-wright.
112
Dixon, J. and Ramutsindela, M., (2006) Urban resettlement and environmental justice in Cape Town, Cities,
Volume 23, Issue 2, 2006, Pages 129-139, ISSN 0264-2751, https://doi.org/10.1016/j.cities.2005.08.003
113
Ueland, J. and Warf, B. (2006), Racialized Topographies: Altitude and Race in Southern Cities, Geographic
Review, Vol. 96, Issue 1, https://doi.org/10.1111/j.1931-0846.2006.tb00387.x
114
Fielding, J. and Burningham, K. (2005) Environmental inequality and flood hazard, Local Environment, Vol. 10,
Issue 4, https://doi.org/10.1080/13549830500160875
115
Environment Agency (2009) ‘Prepare Your Property for Flooding: A Guide for Householders and Small
Businesses’, see http://publications.environment-agency.gov.uk/pdf/GEHO1009BRDL-e-e.pdf
116
Ohl, Christopher & Tapsell, S.M.. (2000). Flooding and human health. BMJ (Clinical research ed.). 321. 1167-8.
10.1136/bmj.321.7270.1167, https://doi.org/10.1136/bmj.321.7270.1167
.
117
Thrush, D., Burningham, K. & Fielding, J. (2005) Flood Warning for Vulnerable Groups: literature review
(Bristol, Environment Agency), see
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/290691/scho
0505bjbs-e-e.pdf.
118
Few, Roger & Ahern, Mike & Matthies, Franziska & Kovats, Sari. (2004). Floods, Health and Climate Change: A
Strategic Review, see
https://www.researchgate.net/publication/228377613_Floods_Health_and_Climate_Change_A_Strategic_Review
.
119
Hajat, Shakoor & Ebi, Kristie & Kovats, S & Menne, Bettina & Edwards, Sally & Haines, Andy. (2003). The human
health consequences of flooding in Europe and the implications for public health: a review of the evidence. 1.
120
Tapsell, S. M., Tunstall, S. M., Penning-Rowsell, E. C. & Handmer, J. W. 1999 The health effects of the 1998
Easter flooding in Banbury and Kidlington. Report to the Environment Agency, Thames region. Flood Hazard
Research Centre, Middlesex University, Enfield, see http://eknygos.lsmuni.lt/springer/154/185-196.pdf
.
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o Combined two FEMA flooding data layers to determine a Future Coastal and Inland Flooding
Potential Layer.
o Intersected the Future Coastal and Inland Flooding Potential Layer with
2021 NJ block
groups and applicable tribal areas to create Urban Flooding Layer.
The Urban Flooding Layer is not designed to inform obligations and requirements under the DEP’s DLRP rules.
• Determined acres of urban land use in each block group using Land Use/Land Cover 2015
• Joined the Flooding (Urban Land Cover Layer with urban land use to determine flooded urban land
use in each block group
• Calculated percent of urban flooding by dividing the flooded urban area by the total urban area in
the block group.
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Proximity Stressors
Description
Overburdened communities often coexist with numerous commercial facilities and industrial sites, both large
and small. While the potential emission impacts from these sites (e.g., air emissions, water pollution, toxic
releases etc.) are captured by other EJ stressors, the mere presence of multiple pollution sources within a
block group is itself a stressor. The Ironbound section of Newark, for example, is home to multiple garbage
incinerators and waste transfer stations, two fossil fuel power plants, numerous factories and warehouses,
chemical refineries, the largest fat rendering plant in the U.S., a large sewage treatment plant, and an EPA
Superfund site. This density of pollution sources becomes its own psychological stress on the community. In
addition, these facilities add other indirect stressors to the community, such as noise, odors, dust, and
increased truck traffic, that impinge on the residents’ quality of life.
Indicator and Measurement Unit(s)
Overall, the Department includes six specific density/proximity-related stressors to help evaluate the impact
that the volume of facilities has on a community. Three of these density-based stressors were discussed
above: KCS, Scrap Metal Facilities and Solid Waste Facilities. Three other density-based stressors: permitted
air sites, NJPDES sites, and emergency planning sites, are discussed in greater detail below.
121
Each density-
based indicator shows the number of applicable sites per square mile, and for all but the NJPDES sites are
evaluated individually as part of the CST (meaning an OBC could get a 1 (yes) for each one of these five
stressors for a maximum total of 5). The NJPDES sites also includes residual sludge processing facilities, and it
is possible for a facility to have a NJPDES permit and a sludge processing permit, giving it a total value of 2 for
this one density stressor category. If a facility had all 7 types of proximity stressors, it would get counted a
total of 7 times. The Department’s rationale for counting facilities multiple times is that their impacts on the
community are significantly higher than a facility that a facility that is only impacting one medium (e.g., air).
For air permitted facilities, each facility has a Program Interest (PI) Number (also referred to as Pref ID Num)
established by a DEP program. The PI Number represents a scenario that requires a new record to be
entered. The PI Number created by a DEP program is unique to that specific DEP program and is not linked to
another program’s data. As the PI Number establishes new records based on regulated activities, it presents
a more complete picture of a facility’s impact within its density stressor. Therefore, the PI Number is utilized
for the air facility density stressor to capture the environmental burden present in a block group. The
permitted air sites proximity stressor includes approximately 230 sites that are considered “major” air facility
types regulated under the EJ Law (e.g., fossil fuel power plants and large-scale chemical and manufacturing
facilities) and a subset of “minor” air sources classified under one of 56 different Standard Industrial
Classification (SIC) codes identified as causing the most frequent community complaints or enforcement
actions. The minor source list includes approximately 3,500 facilities, including concrete and granite
operations, flavors and fragrances, adhesives and paints, gas stations and chemical preparations.
Similar to the permitted air facilities proximity stressor, the PI Number was utilized for the NJPDES and sludge
processing facilities density stressor to capture the environmental burden present in a block group. The
NJPDES sites proximity stressor includes all major facilities with NJPDES permits and
NJPDES Residual
Category V sludge processing facilities.
The PI Number equivalent for the emergency planning stressor to the Facility ID (FAC_ID). This ID is used to
identify one facility that is represented in one or more of the CRTK, DPCC, or TCPA datasets. Similar to the PI
Number, the Facility ID will not be counted more than once even if the record is present in all three datasets.
121
While the solid waste, scrap metal and site remediation facility stressors are also density/proximity based, these
are designed to capture the direct emissions from these facilities as well as the indirect impacts such as noise and
odor.
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The emergency planning sites proximity stressor includes all registered sites under the Toxic Catastrophe
Prevention Act (TCPA) program rules (N.J.A.C. 7:31); the major sites under the Discharge of Petroleum and
other Hazardous Substance (DPHS) program rules (N.J.A.C. 7:1E); or the Worker and Community Right to
Know (CRTK) rules (N.J.A.C. 7:1G) that are federally required to do Emergency Response Plans (ERPs),
excluding “battery only” (e.g., locations with industrial batteries used to power forklifts, computer banks,
etc.). These batteries, if damaged, could cause occupational concerns for workers on-site, but are unlikely to
present any concerns for the community at large since they are enclosed within the facility. As such, “battery
only” sites were excluded.
Rationale
The Law recognizes that the concentration of regulated facilities in an overburdened community is a stressor
on that community. The facilities identified above can contribute to increased truck traffic, dust, odor, and
noise. A 2011 literature review identified several studies that “found that living near hazardous waste sites,
industrial sites, cropland with pesticide applications, highly trafficked roads, nuclear plants, and gas stations
or repair shops is related to an increased risk of adverse health outcomes”
122
.” Moreover, this review found
that “[a]lthough their results are mixed, many studies found significant relationships between residential
proximity to environmental hazards and adverse health outcomes, such as adverse pregnancy outcomes
(including increased risks for central nervous system defects, congenital heart defects, oral clefts, renal
dysplasia, limb malformations, chromosomal anomalies, preterm births, low birth weight, small-for-
gestational-age births, fetal deaths, and infant deaths), childhood cancers (including leukemia, brain cancer,
germ-cell tumors, non-Hodgkin's lymphoma, and Burkitt lymphoma), asthma hospitalizations and chronic
respiratory symptoms, stroke mortality, PCB toxicity, end-stage renal disease, and diabetes.”
While another stressor considers the seriousness of the direct emissions and indirect health and safety
impacts from increased truck traffic in a community, these vehicles can increase dust, and create odors and
noise, that can be equally impactful on a community’s health and wellbeing. In 2021, the New Jersey Clean
Air Council examined the health impacts from “fugitive” dust and found that while large dust particles that
settle out near the source site are merely a nuisance, fine particles can reach greater distances from the
source site and pose significant health problems because they can be “inhaled into the respiratory tract,
affecting the nasal passages, sinuses, and more deeply into the lungs.”
123
While exposure to odor resulting
from human activity is generally recognized to be a nuisance, persistent malodor exposure is considered an
environmental stressor, capable of generating negative impacts for health and well-being due to stress-
related symptoms and illnesses, even if the odorous air is not toxic.
A 2019 study extended previous work that identified a relationship between proximity to odor emitting sites
and higher levels of odor annoyance in the Waterfront South neighborhood of Camden, especially in
comparison to residents of North Camden.
124
Specifically, the study determined that the presence, intensity,
and spatial pattern of three primary odor types (waste treatment, industrial activity, diesel/auto emissions)
observed in Waterfront South, suggested odor pollution continues to function as an environmental stressor.
The measurement, regulation, and human health impacts from noise pollution are well known. Noise levels
deemed acceptable (safe and won’t cause hearing loss) by EPA (70 decibels or below over a 24-hour period)
and the National Institute for Occupational Safety and Health (NIOSH) (85 decibels or below over a 24-hour
122
Jean D. Brender, Juliana A. Maantay, and Jayajit Chakraborty, 2011, Residential Proximity to Environmental
Hazards and Adverse Health Outcomes, American Journal of Public Health 101, S37_S52,
https://doi.org/10.2105/AJPH.2011.300183
.
123
https://www.nj.gov/dep/cleanair/pdfs/cac2021report.pdf
124
Kitson, Jennifer, Monica Leiva, Zachary Christman, and Pamela Dalton. 2019. "Evaluating Urban Odor with Field
Olfactometry in Camden, NJ" Urban Science 3, no. 3: 93. https://doi.org/10.3390/urbansci3030093
.
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period) are well above recommendations made by the European Union (40 decibels at night and 50 decibels
during the day). For context, NYC Midtown Manhattan has reach 94 decibels. According to a 2017 study led
by the School of Public Health at the University of California at Berkeley, people in poorer and racially
segregated neighborhoods live with higher levels of noise than other people.
125
Neighborhoods with median
annual household incomes below $25,000 were nearly two decibels louder than neighborhoods with incomes
above $100,000, and communities where at least 3 in 4 residents are black had median nighttime noise levels
of 46.3 decibels — four decibels louder than communities with no black residents.
Finally, a recent study also found that “[n]egative perceptions of environmental hazards and reported
cultural stressors were significantly associated with fair/poor self-rated health among residents in a low-
income majority-minority community…”
126
Since poor self-rated health is often related to chronic health
conditions and premature mortality, and minority populations are the most likely to report poor health, the
study looked at how both resident perception of neighborhood environments and chronic health conditions
individually and collectively influence health in a majority-Hispanic urban population.
Stressor Value Calculation Method
• Obtained the appropriate data source GIS file for each proximity stressor:
o EJ Air Facilities
o EJ Major Water Facilities
o EJ Sludge Facilities
o EJ TCPA Facilities
o EJ DPCC Facilities
o EJ CRTK Facilities
• Combined the EJ Major Water and EJ Sludge Facilities files to get one water sites file for analysis.
• Combined the EJ TCPA, DPCC, and CRTK Facilities files to get one Emergency Planning file for analysis.
• Where applicable, applied ArcGIS’ Delete Identical data management tool to the output coverage to
remove duplicates in the data based on either the PI Number (Pref ID Number) or Facility ID fields
• Applied ArcGIS’ Kernel Density
function using the each proximity data source file (EJ Air Facilities, EJ
Combined Water file and EJ Combined Emergency Planning) separately as the input with the
following parameters:
o Search radius of 5 kilometer (approximately 3 miles), which is consistent with the distance
requirements in EPA’s EJSCREEN User Guide
.
o Grid size of 100 ft.
This calculated a raster density file for each proximity stressor.
• Applied Zonal Statistics as a Table function in ArcMap Spatial Analyst
using each separate raster
density file as the input to determine the spatially weighted average density for each 2021 NJ block
groups and applicable tribal areas as the indicator for proximity to each site.
125
Joan A. Casey,Rachel Morello-Frosch,Daniel J. Mennitt,Kurt Fristrup,Elizabeth L. Ogburn,and Peter James
2017, Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the
Contiguous United States, Environmental Health Perspectives 125:7 CID: 077017 https://doi.org/10.1289/EHP898
.
126
Ou, J.Y., Peters, J.L., Levy, J.I. et al. Self-rated health and its association with perceived environmental hazards,
the social environment, and cultural stressors in an environmental justice population. BMC Public Health 18, 970
(2018). https://doi.org/10.1186/s12889-018-5797-7
.
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Social Determinants of Health
The U.S. Department of Health and Human Services defines those conditions in the environments where
people live and work that adversely affect health, functioning, and quality-of-life outcomes and risks as social
determinants of health or “SDOHs.”
127
Three primary SDOHs (low-income households, minority status, and
limited English proficiency) comprise the definition of an overburdened community under the New Jersey
Environmental Justice Law. However, two other SDOHs (unemployment and education) are often referenced
as key “upstream” factors directly tied to low-income/poverty, which in turn impact health and create
disparities by shaping the distribution of money, power, and resources. These SDOHs increase social
vulnerability, and reduce capacity to anticipate, confront, repair and recovery from externalities such as
natural and human-caused disasters, and disease outbreaks.
128
Unemployment
Description
Unemployment impacts people’s health, well-being, and quality-of-life. Many people live in poverty because
they cannot find employment. In addition, some workforce participants are “underemployed”, including
involuntary part-time employment, poverty-wage employment, and/or insecure employment. In either case,
these people struggle to afford healthy foods, health care, and safe, affordable housing, and lack the time
and resources for a healthy lifestyle (e.g., exercise, mediation, stress reduction).
Indicator and Measurement Unit(s)
Percent unemployed in a block group.
Rationale
Some adults have great difficulty finding and holding jobs even when overall economic conditions are good.
These individuals often have low levels of formal education, skills, and other characteristics (e.g., criminal
records) that negatively impact their employment prospects.
129
Unfortunately, these individuals are also
more likely people of color; that is, Hispanics and black individuals have substantially higher unemployment
rates than white individuals across both male and female categories.
130
New Jersey’s pre-pandemic 2019
data shows more than twice as many unemployed black people as white people.
131
In the first quarter of
2020, that unemployment gap widened slightly to 6.9% black vs. 2.6% white.
132
These figures align with national data, which shows that for the first quarter of 2020, African Americans had
the highest unemployment rate, double that of white and Asian workers. In fact, since the US Bureau of
Labor Statistics started collecting data on the African American unemployment rate in 1972, this rate has
127
https://www.cdc.gov/socialdeterminants/index.htm
128
Flanagan, B. E., Hallisey, E. J., Adams, E., & Lavery, A. (2018). Measuring Community Vulnerability to Natural and
Anthropogenic Hazards: The Centers for Disease Control and Prevention's Social Vulnerability Index. Journal of
environmental health, 80(10), 34–36, see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7179070/
.
129
Barden, B., Juras, R., Redcross, C., Farrell, M., and Bloom, D. (2018). New Perspective on Creating Jobs – Final
Impacts of the Next Generation of Subsidized Employment Programs. Washington, DC: Office of Planning,
Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human
Services.
https://www.acf.hhs.gov/sites/default/files/opre/etjd_sted_final_impact_report_2018_508compliant_v2_823201
8_b.pdf.
130
Cajner, Tomaz, Tyler Radler, David Ratner, and Ivan Vidangos (2017). “Racial Gaps in Labor Market Outcomes in
the Last Four Decades and over the Business Cycle,” Finance and Economics Discussion Series 2017-071.
Washington: Board of Governors of the Federal Reserve System, https://doi.org/10.17016/FEDS.2017.071
.
131
https://www-doh.state.nj.us/doh-shad/indicator/view/Demographics.Employ.html
132
https://www.epi.org/indicators/state-unemployment-race-ethnicity-2020q1q2/
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often been twice that of the white unemployment rate.
133
While some studies determined that the large,
persistent black-white unemployment rate gap isn’t readily explained by observable characteristics (e.g.,
education)
134
, others showed that African American males who graduated from high school were ~70% more
likely to be involuntarily unemployed than their white counterparts with the same educational
background.
135
This disparity increased to over 120% for individuals who had completed 4 or more years of
college. The Hispanic-white unemployment gap, which is smaller by comparison, is largely explained by lower
educational attainment and language barriers.
In addition to providing income, employment can offer other benefits such as health insurance, paid sick
leave, and parental leave, all of which affect the health of employed individuals.
136
Health insurance provides
access to affordable medical care and financial protection from unexpected health care costs, while paid sick
leave allows employees to seek medical care for themselves or dependent family members without losing
wages.
Unemployment can also result in negative health consequences.
137
Those who are unemployed can suffer
from report depression, anxiety, low self-esteem, demoralization/ worry, and physical pain. Unemployed
individuals also have more stress-related illnesses such as high blood pressure, stroke, heart attack, heart
disease, and arthritis. In addition, experiences such as perceived job insecurity, downsizing or workplace
closure, and underemployment also have implications for physical and mental health.
Stressor Value Calculation Method
• Obtained New Jersey’s 2021 American Community Survey (ACS) summary data
Summary File
Sequence Table 78 e202115nj0078000 and used the following fields:
o Civilian labor force: B23025_003
o Unemployed: B23025_005
• Calculated Unemployment as ([unemployed]/[civilian labor force])*100
Education
Description
Insufficient education is a socio-economic factor that contributes directly to unemployment, and indirectly to
low-income status. In addition, insufficient education can exacerbate limited English proficiency, which itself
contributes to unemployment and poverty.
Indicator and Measurement Unit(s)
Percent without a high school diploma in a block group.
133
Federal Reserve Economic Data, “Unemployment Rate: Black or African American,” Federal Reserve Bank of St.
Louis, available at https://fred.stlouisfed.org/series/LNS14000006
.
134
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-
resources/employment#36
135
Cajner, Tomaz, Tyler Radler, David Ratner, and Ivan Vidangos (2017). “Racial Gaps in Labor Market Outcomes in
the Last Four Decades and over the Business Cycle,” Finance and Economics Discussion Series 2017-071.
Washington: Board of Governors of the Federal Reserve System, https://doi.org/10.17016/FEDS.2017.071
.
136
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-
resources/employment
137
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-
resources/employment#36
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Rationale
A high school diploma is a standard requirement for most jobs and all higher education opportunities.
However, disparities in high school completion rates exist among racial and ethnic groups in the United
States.
138
According to data for the 2018-2019 school year, 93 percent of Asian/Pacific Islander, 89 percent of
white, 82 percent of Hispanic, 80 percent of black, and 74 percent of American Indian/Alaskan Native
students attending public high schools graduated within 4 years of beginning the 9th grade.
139
In New Jersey,
the Adjusted Cohort Graduation Rate gap between white and black public high school students is more even
pronounced at 12 percent (95 percent for while students and 83% for black students).
Education is not only linked to differences in employment type, but also working conditions, income amount
and benefits.
140
Individuals with less education have fewer employment choices, driving them into positions
with low levels of control, job insecurity, low wages, and limited or no additional benefits. Individuals with
less education are also more likely to have jobs that are physically demanding or include exposure to toxins.
Students fail to complete high school for a variety of reasons, including the impacts of poverty, and teen
pregnancy and parenthood.
141
Students who do not graduate high school are more likely to self-report
overall poor health. They are also more likely to suffer from at least 1 chronic health condition such as
asthma, diabetes, heart disease, high blood pressure, stroke, hepatitis, or stomach ulcers. Ultimately,
finishing more years of high school, and especially earning a high school diploma, decreases the risk of
premature death.
Stressor Value Calculation Method
• Obtained New Jersey’s 2021 American Community Survey (ACS) summary data Summary File
Sequence table 42 e202115nj0042000 and used the following fields:
o B15003_001 Total Population 25 years and over
o B15003_017 Regular high school diploma
o B15003_018 GED or alternative credential
o B15003_019 Some college, less than 1 year
o B15003_020 Some college, 1 or more years, no degree
o B15003_021 Associate degree
o B15003_022 Bachelor's degree
o B15003_023 Master's degree
o B15003_023 Master's degree
o B15003_024 Professional school degree
o B15003_025 Doctorate degree
• Calculated Population below high school diploma
o Total Population 25 and over – (sum of fields B15003_017 to B15003_025)
• Calculated Percent Unemployment
o ([Population below high school diploma]/[Total Population 25 years and over])*100
138
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-
resources/high-school-graduation#7
139
https://nces.ed.gov/programs/coe/indicator/coi
140
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-
resources/employment#36
141
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-
resources/high-school-graduation#7
61 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Appendix A: Air Quality Monitoring Coordinates
Coordinates for all Air Quality Monitors Included in the Ozone and PM Stressor Calculations
State_Code
County_Cod
Site_Num
Parameter_
POC
Latitude
Longitude
State_Name
09
001
0017
44201
1
41.003611
-73.585
Connecticut
09
001
0017
44201
1
41.004657
-73.585128
Connecticut
09
001
1123
44201
1
41.399167
-73.443056
Connecticut
09
001
3007
44201
1
41.1525
-73.103056
Connecticut
09
001
9003
44201
1
41.118333
-73.336667
Connecticut
09
005
0005
44201
1
41.821342
-73.297257
Connecticut
10
001
0002
44201
1
38.986672
-75.5568
Delaware
10
003
1007
44201
1
39.5513
-75.732
Delaware
10
003
1010
44201
1
39.817222
-75.563889
Delaware
10
003
1013
44201
1
39.773889
-75.496389
Delaware
10
003
2004
44201
1
39.739444
-75.558056
Delaware
10
005
1002
44201
1
38.6539
-75.6106
Delaware
10
005
1003
44201
1
38.7791
-75.16323
Delaware
34
001
0006
44201
1
39.464872
-74.448736
New Jersey
34
003
0006
44201
1
40.870436
-73.991994
New Jersey
34
007
0002
44201
1
39.934446
-75.125291
New Jersey
34
007
1001
44201
1
39.68425
-74.861491
New Jersey
34
011
0007
44201
1
39.422273
-75.025204
New Jersey
34
013
0003
44201
1
40.720989
-74.192892
New Jersey
34
015
0002
44201
1
39.800339
-75.212119
New Jersey
34
017
0006
44201
1
40.67025
-74.126081
New Jersey
34
019
0001
44201
1
40.515262
-74.806671
New Jersey
34
021
0005
44201
1
40.283092
-74.742644
New Jersey
34
021
9991
44201
1
40.3125
-74.8729
New Jersey
34
023
0011
44201
1
40.462182
-74.429439
New Jersey
34
025
0005
44201
1
40.277647
-74.0051
New Jersey
34
027
3001
44201
1
40.787628
-74.676301
New Jersey
34
029
0006
44201
1
40.06483
-74.44405
New Jersey
34
031
5001
44201
1
41.058617
-74.255544
New Jersey
34
041
0007
44201
1
40.92458
-75.067815
New Jersey
36
005
0110
44201
1
40.816
-73.902
New York
36
005
0110
44201
1
40.81618
-73.902
New York
36
005
0133
44201
1
40.8679
-73.87809
New York
36
027
0007
44201
1
41.78555
-73.74136
New York
36
061
0135
44201
1
40.81976
-73.94825
New York
36
071
5001
44201
1
41.52375
-74.21534
New York
36
079
0005
44201
1
41.45589
-73.70977
New York
36
081
0124
44201
1
40.73614
-73.82153
New York
36
085
0067
44201
1
40.59664
-74.12525
New York
36
087
0005
44201
1
41.18208
-74.02819
New York
62 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
State_Code
County_Cod
Site_Num
Parameter_
POC
Latitude
Longitude
State_Name
36
103
0002
44201
1
40.74529
-73.41919
New York
36
103
0009
44201
1
40.82799
-73.05754
New York
36
103
0009
44201
2
40.82799
-73.05754
New York
36
111
1005
44201
1
42.14403
-74.49431
New York
36
119
2004
44201
1
41.05192
-73.76366
New York
42
011
0006
44201
1
40.51408
-75.789721
Pennsylvania
42
011
0011
44201
1
40.38335
-75.9686
Pennsylvania
42
017
0012
44201
1
40.107222
-74.882222
Pennsylvania
42
029
0100
44201
1
39.834461
-75.768242
Pennsylvania
42
045
0002
44201
1
39.835556
-75.3725
Pennsylvania
42
069
0101
44201
1
41.479116
-75.578186
Pennsylvania
42
069
2006
44201
1
41.442778
-75.623056
Pennsylvania
42
077
0004
44201
1
40.611944
-75.4325
Pennsylvania
42
079
1100
44201
1
41.209167
-76.003333
Pennsylvania
42
079
1101
44201
1
41.265556
-75.846389
Pennsylvania
42
089
0002
44201
1
41.08306
-75.32328
Pennsylvania
42
091
0013
44201
1
40.112222
-75.309167
Pennsylvania
42
095
0025
44201
1
40.628056
-75.341111
Pennsylvania
42
095
8000
44201
1
40.692224
-75.237156
Pennsylvania
42
101
0004
44201
1
40.008889
-75.09778
Pennsylvania
42
101
0024
44201
1
40.0764
-75.011549
Pennsylvania
42
101
0048
44201
1
39.991389
-75.080833
Pennsylvania
42
101
1002
44201
1
40.035985
-75.002405
Pennsylvania
36
085
0111
44201
2
40.58027
-74.19832
New York
42
101
0004
44201
2
40.008889
-75.09778
Pennsylvania
63 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Appendix B: Glossary of Terms
Action Level Exceedance (ALE): When testing shows that at least 10 percent of homes on the same public
water supply have more than 15 parts per billion (pbb) of lead and copper. When tests show an ALE has
occurred within a community, the water purveyor must take actions to reduce lead and/or levels in the
water. Actions include, water quality monitoring, adjusting water treatments and/or replacing pipes, as well
as public education. (Refer to NJDEP’s Division of Water Supply and Geoscience Violation reports
for more
information)
Adjacent Block Groups (ABGs): Any block group identified by the U.S. Census Bureau with a population of
zero that are also immediately next to one or more statutorily defined overburdened communities. (EJ Rule
)
Adverse cumulative stressors: When the combined stressor total of an overburdened community is higher
than 50
th
percentile non-OBC comparison point or would be made higher than 50
th
percentile non-OBC
comparison point.” (EJ Rule)
Adverse Health Effect: A change in cell structure, or body chemistry and/or function, that may cause disease
or health issues. (Technical Support Document, EPA’s Air Toxics Screening Assessment
)
Air toxic: Pollutants known to cause or suspected of causing cancer or other serious health problems. Air
toxins are also referred to as toxic air pollutants or hazardous air pollutants (HAPs), and can include benzene,
found in gasoline; perchloroethylene, produced from dry cleaning facilities; vinyl chloride, used to make
polyvinyl chloride (PVC) plastic and vinyl products; and ethylene oxide, emitted from commercial and hospital
sterilizers. (EPA
)
ArcGIS: Geospatial software developed and maintained by ESRI that is often used for creating, managing, and
analyzing geographic data. (ESRI
)
Census block group: Statistical divisions of census tracts that typically contain between 600 and 3,000 people
and are used to present data and control block numbering. Block groups consist of clusters of blocks found
within the same census tract that share the same first digit of their four-digit census block group number.
Block groups never cross state, county, or census tract boundaries. (Census.gov
)
Census tract: Small statistical subdivisions of a county or statistically equivalent entity. Census tracts usually
have a population size between 1,200 and 8,000 people and cover a contagious area. (Census.gov
)
Combined Stressor Total (CST): The total number of adverse stressors in an overburdened community. (EJ
Rule)
Disproportionate Impact: Situations where a facility cannot avoid either: (1) creating adverse cumulative
stressors in an overburdened community as a result of the facility’s contribution; or (2) contributing to an
adverse environmental and public health stressor in an overburdened community that is already subject to
adverse cumulative stressors. (EJ Rule
)
64 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Geographic Information Systems (GIS): A computer system designed to analyze and display geographically
referenced information. (USGS.gov
)
Geographic point of comparison (GeoPC): The lower (e.g., most protective) of the non-OBC state or relevant
county stressor values. If an OBC block group’s combined stressor total is higher than the 50th percentile
non-OBC comparison point, that OBC is subject to adverse cumulative stressors. (TAG)
Ground Level Ozone: A harmful air pollutant that forms when Volatile Organic Compounds (VOCs) and
Nitrogen Oxides (NO
x
) react in the presence of sunlight. Negative health effects caused by the presence of
ground level ozone includes swelling in the lungs and increased vulnerability to people with lung related
deficiencies. (DEP Air Quality Evaluation and Planning
)
Hazardous Waste: Waste with properties that are dangerous or potentially having harmful effects on human
health or the environment. (EPA
) Waste considered to be hazardous must be transported and disposed in
authorized hazardous waste facilities. (Solid and Hazardous Waste Management Program Guidance
Document for Waste Classification)
Limited English Proficiency: A household without an adult that speaks English “very well” as determined
annually by the United States Census Bureau. (EJ Law
)
Low-income Household: A household that is at or below twice the poverty threshold as determined annually
by the United States Census Bureau. (EJ Law
)
Maximum Containment Level (MCL): an enforceable federal water quality standard for a particular
substance (such as arsenic, benzene, lead) that the USEPA considers virtually attainable. Often times, the
MCL is equivalent to the Maximum Contaminant Level Goal (MCLG) established by the USEPA as a non-
enforceable public health objective. the USEPA determined that it is most likely impossible to completely
eliminate carcinogenic contaminants but does not set an MCL at "zero." Instead, the USEPA sets an attainable
level that can be achieved given available technology and resources. (Refer to NJDEP’s Division of Water
Supply and Geoscience Violation reports
for more information).
Minority Population: A population of people who do not identify as single race white and non-Hispanic.
Minority populations include: Black, Hispanic, Asian-American, American Indian or Alaskan Native (
EPA EJ
Glossary and Definitions from 52:27H-21.18).
New Jersey Pollutant Discharge Elimination System (NJPDES): a program that protects New Jersey’s water
quality by assuring the treatment and discharge of wastewater and stormwater from different types of
facilities including industrial and municipal wastewater dischargers, shopping centers, and schools (
NJDEP-
Division of Water Quality - NJPDES Program).
New Jersey Environmental Management System (NJEMS) - The NJ Department of Environmental
Protection’s database that supplies coordinates and descriptive attributes from several tables used to
generate GIS layers (NJEMS Meta Data
)
New Jersey Private Well Testing Act (PWTA): - a New Jersey consumer information law that requires testing
and disclosure of water quality during real estate transactions on properties with potable private wells. It also
requires landlords test well water for rental properties once every five years. (
The New Jersey Private Well
Testing Act: An Overview)
65 Page of 65
New Jersey Department of Environmental Protection
EJMAP: Technical Guidance April 12, 2023
Overburdened Community (OBC): According to The Law “Any census block group, as determined in
accordance with the most recent United States Census, in which: (1) at least 35 percent of the households
qualify as low-income households; (2) at least 40 percent of the residents identify as minority or as members
of a State recognized tribal community; or (3) at least 40 percent of the households have limited English
proficiency.”
Parcel: A parcel is an area of land, or property, including its associated structures, with set boundaries
for local property tax and land use zoning purposes
PM 2.5: Dine inhalable particles, with diameters that are generally 2.5 micrometers and smaller. (
Particulate
Matter (PM) Basics | US EPA).
Stressor: One of the twenty-six environmental and public health indices incorporated into New Jersey’s
methods for its environmental and public health comparative impact analysis. (TAG
)
Treatment Techniques: When a public water system fails to comply with treatment or operational
requirements intended to reduce the levels of contaminants. (Refer to NJDEP’s Division of Water Supply and
Geoscience Violation reports
for more information).
