INTO THE MYSTIC

Combined Sewer Overflows (CSOs) and Community Demographics in the Mystic River Watershed:

An Environmental Equity Analysis

A thesis

submitted by

Joshua Daniel Berkowitz

In partial fulfillment of the requirements for the degree of

Master of Arts In

Urban and Environmental Policy and Planning

Tufts University

August 2008

Advisor: Rusty Russell Reader: Paul Kirshen

Abstract

This thesis utilizes GIS to explore the distribution of combined sewer

overflows (CSOs) across communities in the Mystic River Watershed. Looking

principally at whether distribution of active CSOs disproportionately burdens

certain communities, it also explores land-use based exposure potential. Research

examines demographic trends related to CSO closures, including temporal

analysis of regional changes over time. Demographic differences between areas

that did and did not receive relief from CSO burdens are also examined. Further

study examines whether CSOs were sited before or after neighborhoods formed,

while community surveys are conducted to assess effects and perceptions of

CSOs.

Key research findings include that active CSOs disproportionately affect

lower-income and higher-minority populations within the watershed. Temporal

research indicates notable trends in demographic changes over time, while land

use, siting, and survey analyses provide valuable supplementary information to

aid in interpreting results. Finally, further research needs are presented along with

proposed policy and planning responses.

ii

Acknowledgements

I wish to express my sincere gratitude to the people who have supported me

during this project. In particular, I wish to thank my advisor, Rusty Russell, for

his always helpful feedback and undying enthusiasm and encouragement. I would

also like to thank my reader, Paul Kirshen, for all of his technical guidance and

oversight. Special thanks are owed to Barbara Parmenter, who tirelessly and with

good humor helped me navigate the GIS data that served as the backbone of my

research. I also extend my gratitude to all of the engineers, policy makers,

community activists and others who are too many in number to be named here,

who helped make this research possible.

I also wish to thank my family for their support, without which I would not be

here today. I want to thank my mother for her deep love and understanding. And

I want to thank my father for giving me the gifts of a thirst for knowledge and for

a work ethic that has kept me going throughout it all. I know he would be proud.

And to all my friends, near and far, thank you for understanding what has kept me

so busy this past year. It is your friendship which feeds me.

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Table of Contents

Executive Summary vii Chapter 1: Introduction and Background 2 Chapter 2: Review of the Literature 22 Chapter 3: Research Methodology 34 Chapter 4: Analytical Results and Findings 68 Chapter 5: Research Limitations and Further Research 103 Chapter 6: Conclusions and Recommendations 114 Appendices 129 References 134

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List of Tables:

Table 1: Demographic Comparisons between Block Groups Affected vs.

Unaffected by Active CSOs

Table 2: Differences in Demographic Comparisons (Affected vs. Unaffected)

Table 3: Demographic Comparisons: 1990 and 2000 (Background Levels)

Table 4: Demographic Comparisons: 1990 and 2000 (Target Block Groups)

Table 5: Percent Change in Minority Population for the Boston Metropolitan Area

1990 to 2000

Table 6: Demographic Comparisons Between 1990 Block Groups Affected by

Active vs. Closed CSOS

Table 7: Acres of Land Use within Active CSO Buffers (Year 2000)

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List of Figures:

Figure 1a: Typical CSO outfall pipe

Figure 1b: CSO outfall along Alewife Brook

Figure 2: Combined sewer system in dry and wet weather

Figure 3: Separate sewer system in dry and wet weather

Figure 4: Combined sewer overflows demographics in the U.S.

Figure 5: Mystic River Watershed

Figure 6: Mystic River corridor study area block groups

Figure 7: Active CSOs with 0.25 mile circular buffers

Figure 8: Example of manual deselection of upstream block group within 0.25

mile circular buffer of active CSO

Figure 9: Final selection of 2000 Census block groups affected (red) and

unaffected (blue) by active CSOs (representing the “whole block group”

method)

Figure 10: Segregated block group portions (where pink represents CSO-affected

(clipped) fractions of block groups)

Figure 11: Graphic representation of the “areal weighting” method

Figure 12: Affected land areas (in pink) within impact zones of active CSO

clusters

Figure 13: Affected land areas (in pink) within impact zones of active CSO

clusters

Figure 14: U.S. EPA assessment of water quality in Mystic River Watershed,

2008

Figure 15: CSO signage along Alewife Brook

Figure 16: NYCDEP CSO signage

vi

Executive Summary

Combined sewer overflows (CSOs), the discharging of combined sewer

systems directly into surface waters upon capacity overload, are a large source of

pollution of U.S. waterways. The wastewater the CSOs carry may contain

stormwater, untreated human waste and industrial waste, toxic materials and

floating debris, all of which can be harmful to human health as well as the

ecological health of the watershed. In the U.S., CSOs are especially common in

the Northeast, Great Lakes, and Pacific Northwest regions. In New England,

where more than 100 communities are burdened with CSO pipes that discharge

hundreds of millions of gallons of untreated sewage and stormwater into

waterways after heavy rains, no place is more intensely burdened by CSOs than

the Boston metropolitan area.

Combined sewer overflows are one of a number of sources of pollution

affecting the Mystic River Watershed, a 76-square-mile urban watershed

surrounding the Mystic River and its tributaries in the Greater Boston area. The

watershed is also home to many low-income and minority communities that have

been shown to be the most intensively overburdened by cumulative environmental

hazards in Massachusetts. While there has been much scholarship on

disproportionate community burdens from certain types of environmental

pollution, very little research has looked at water pollution, with still less centered

on CSOs. Furthermore, while attention has focused on the environmental burdens

the Mystic River Watershed communities face from industrial sources of air

vii

pollution, to this author’s knowledge, no studies to date have examined

community burdens from CSOs in the watershed.

This research intends to systematically investigate the distribution of

CSOs in the Mystic River Watershed to identify any related environmental

injustices -- and then to propose initial policy and planning responses.

Specifically, this thesis uses GIS to examine the distribution of combined

sewer overflows across communities in the Mystic River Watershed, looking

principally at whether distribution of active CSOs disproportionately burdens

certain communities. Examination is conducted at the Census block group level,

the smallest unit for which the Census Bureau collects and publishes detailed

social, economic and other demographic data. Utilizing a 0.25 mile downstream

circular buffer around outfalls as a proxy for CSO impact zones, GIS analysis

identifies communities as within range of CSOs if these buffers cross their block

group. Affected areas are identified by both whole block groups and by area-

weighted portions of affected block groups, whereby block groups are fractioned

into portions in and outside of buffers and their demographic data then

proportionally allocated based on these fractions. The demographic attributes of

the identified block group sets are then comparatively analyzed for differences in

key demographic variables.

This research also explores land-use based exposure potential of active

CSOs in order to identify those CSOs posing the greatest risks to communities.

This analysis is conducted by overlaying land use information on top of the active

viii

CSO-affected areas, and thereby calculating the acreage of various types of land

uses within each cluster of CSO impact zones.

Research also examines demographic trends related to CSO closures,

including temporal analysis of regional changes over time. This first looks at

changes in demographic patterns in a number of sub-areas of the watershed

between 1990 and 2000, the period during which eight CSOs were closed. Also

examined are the demographic differences between those 1990 CSO-affected

block groups which had their CSOs closed and those 1990 CSO-affected block

groups which did not receive CSO relief, and thus still host active CSOs today.

Further study examines whether CSOs were sited before or after

neighborhoods formed in the region. By comparing estimates of CSO

construction dates against data on the year that each parcel within the CSO-impact

zones was built, we may explore the history of CSO siting. Finally, community

surveys are conducted to assess effects and perceptions of CSOs throughout the

study area.

Summary of Major Findings

1. When comparing neighborhoods affected by active CSOs with those that

are not, this thesis finds that CSO-affected areas:

• have 9.3-12.1 percent higher minority populations, • include 2.1-5 percent more individuals who are not U.S. citizens, • have 2.1-4.5 percent more households that are non-English speaking, • have average median household incomes that are approximately 27

percent lower, and • have 8.7-9.3 percent more of their population below the poverty level

than do unaffected areas.

ix

Thus, this initial assessment suggests that currently active CSOs disproportionately affect lower-income and higher-minority populations within the Mystic River Watershed.

2. The longitudinal study of demographic variables between 1990 and 2000

for my areas of interest allowed an examination of the changes that had taken

place concurrent with the removal of certain CSOs. While not entirely

conclusive, this research did indicate that those areas affected by CSOs (both

active and closed) experienced the sharpest rise in minority population as a

percentage of the total population, as well as the smallest growth in median

household income, during the period 1990 to 2000. However, when considering

broader demographic trends across the region during this time, these findings

likely indicate that given only a few years in most cases between CSO closure and

the 2000 Census, not enough time had passed to account for the affects of CSO

closure on the makeup of neighborhoods.

3. When comparing demographic differences between the 1990 CSO-

affected block groups whose CSOs had closed between 1990 and 2000, and those

1990 CSO-affected block groups whose CSOs remain active to date, I found that

the 1990 block groups whose CSOs were not closed (and thus remain active

today):

• have a 6 percent higher minority population, and • have average median household incomes that are 13 percent lower

than those areas in the watershed where CSOs were closed. Thus, the areas where CSOs remained active within the watershed are higher minority and lower income than those areas in which active CSOs were closed between 1990 and 2000.

x

4. The analysis of the distribution of land use within the specific portions of

block groups that are affected by active CSOs aids in identifying those areas with

the greatest exposure potential. Focusing on residential and recreational lands,

given that these are likely to pose the greatest threats to public health, this thesis

identified the CSO-affected areas in the watershed that have the greatest acreage

of these land uses. This analysis informs the recommendations that are then

made.

5. Due to the paucity of available data, this study was unable to conclude

with any certainty that the Mystic River Watershed’s CSOs – which were

constructed before 1900 -- were sited in pre-existing residential neighborhoods.

However, this research did find that in a number of areas within the watershed

this is at least a significant possibility – thus warranting further investigation.

Areas where the majority of parcels were built prior to or around the same

time as CSOs, also warranting further investigation, include sections of Arlington

and Cambridge along Alewife Brook, and areas within the cities of Everett,

Malden, Chelsea, and Boston.

6. Community surveys indicated that CSOs are a serious concern for the

majority of surveyed community members.

The primary community concerns over CSOs are:

• public health impacts, • nuisance effects, such as odor and unsightliness, • property damage and devaluation, and • reduced recreational opportunities in and along the waterfront.

xi

In addition, a majority of respondents believed that CSO placement and impacts

were inequitably distributed in their communities. They wanted the CSOs to be

eliminated, and expressed the hope that this would expand safe recreational

opportunities on the river.

Recommendations for Policy and Planning Even though this study points to a need for further research, it has important

implications for public policy and planning right now.

These include a need for:

• Better water quality monitoring in the watershed, including

o increased breadth and frequency of monitoring, and

o monitoring that is better tailored to identification of key pollution

sources and the different roles that they play in contributing

contaminant loads – sources like combined sewer overflows

(CSOs), sanitary sewer overflows (SSOs), and stormwater runoff.

• Improved coordination and management of the collected data,

including

o a central database and clearinghouse for all of the water quality

data collected in the watershed, and

o an independent technical advisory body to oversee water quality

monitoring.

• Expedited clean up and elimination of the CSOs that most affect

environmental justice populations, especially through residential and

recreational exposure. These are the following outfalls:

o CAM001, CAM002, CAM401B, SOM001A, CHE002, CHE003,

CHE004, BOS003, BOS005, BOS006, BOS007, BOS009,

BOS010, BOS012, BOS013 and BOS014.

xii

xiii

• Targeted public education about the locations of outfalls and the

dangers of CSO exposure, through

o signage that is clearly visible, legible, non-technical, and in all

languages appropriate to local communities,

o signage that explains the risks associated with coming into contact

with the contaminated water as well as the conditions likely to

cause CSO activation, and

o a more effective public education campaign, including better

signage and the direct distribution of additional information,

building on the approaches that other cities and regions have taken.

• A more effective system of public notification about CSO activations,

including

o stricter enforcement of CSO activation notification requirements in

NPDES permits, and

o mechanisms for more widespread community notification

following each CSO event – including coverage in local media

(print, radio and television), and on easy-to-find websites, so that

individuals can make informed decisions about where and when to

work and recreate in the watershed.

• Increased funding to carry out these measures, through

o dedicated public resources, including MWRA ratepayer fees, and

federal, state and local taxes,

o placement of projects on EPA’s Supplemental Environmental

Projects (SEP) list,

o corporate sponsorship by businesses within the watershed, and the

channeling of philanthropic dollars through the nonprofit Mystic

River Watershed Association or other community groups.

INTO THE MYSTIC

Combined Sewer Overflows (CSOs) and Community Demographics in the Mystic River Watershed:

An Environmental Equity Analysis

Injustice anywhere is a threat to justice everywhere. We are caught in an inescapable network of mutuality, tied in a single garment of

destiny. Whatever affects one directly, affects all indirectly.

- Martin Luther King, Jr. -

1

Chapter One: Introduction and Background

Introduction

Combined sewer overflows (CSOs), the discharging of combined sewer

systems directly into surface waters upon capacity overload, are a large source of

pollution of U.S. waterways. The wastewater the CSOs carry may contain

stormwater, untreated human waste and industrial waste, toxic materials and

floating debris, all of which can be harmful to human health as well as the

ecological health of the watershed. Developed in the 1800s, CSOs are especially

common in regions of the country such as the Northeast, Great Lakes, and Pacific

Northwest. In New England, where more than 100 communities are burdened

with CSO pipes that discharge hundreds of millions of gallons of untreated

sewage and stormwater into waterways after heavy rains (U.S. EPA, 2007a), no

place is more intensely burdened by CSOs than the Boston metropolitan area.

As will be further explored below, combined sewer overflows are one of a

number of sources of pollution affecting the Mystic River Watershed, a 76-

square-mile urban watershed surrounding the Mystic River and its tributaries in

the Greater Boston area. The watershed is burdened by a history of pollution

from heavy industry, which continues to be active today, intensive pollution from

urbanization and stormwater runoff, and limited public access to the waterfront,

among other challenges. The watershed is also home to many low-income and

minority communities that have been shown to be the most intensively

2

overburdened by cumulative environmental hazards in Massachusetts (Faber and

Krieg, 2005).

While much research has been conducted on disproportionate community

burdens from certain types of environmental pollution, very little has looked at

water pollution. Less research still has centered on CSOs. To my knowledge, no

studies to date have examined community burdens from CSOs in the Mystic River

Watershed.

In my thesis I use GIS to examine the distribution of CSOs across

communities in the Mystic River Watershed, looking principally at whether

distribution of active CSOs disproportionately burdens certain communities. I

engage with a number of other analyses as well, including land-use based

exposure potential, demographic trends related to CSO closures, CSO siting

history, and community perceptions of CSOs. This research intends to

systematically investigate the distribution of CSOs in the Mystic River Watershed

to identify any related environmental injustices -- and then to propose initial

policy and planning responses.

Background

Congress passed the Clean Water Act1 more than 35 years ago. As

written (then as now) the act expected all U.S. waters to become fishable and

swimmable by mid-1983 and all discharge of pollutants to completely stop by

1985. Yet today our nation’s waterways remain heavily impaired (Copelan

d, 1 This law was initially enacted as the Federal Water Pollution Control Act Amendments of 1972. As a result of a 1977 amendment, it was renamed the Clean Water Act (Vigil, 2003).

3

2002). According to the EPA, approximately 40 percent of our nation’s surveyed

rivers, lakes and estuaries are not clean enough to meet basic uses such as fish

or swimming (U.S. EPA, 2002). Sewage discharges from combined sewer

overflow pipes are a major problem in large areas of this country and are a big

reason why many of the nation's rivers remain unsafe for swimming and fishing

(U.S. EPA, 2007a). Combined sewer overflows (CSOs) are the discharges from

combined sewer systems (CSSs), which were designed to carry sanitary

wastewater (domestic sewage from homes as well as industrial and commercial

wastewater) and stormwater through a single pipe (U.S. EPA, 2004). Du

heavy precipitation events (e.g., rainfall or snowmelt), the wastewater volume is

often more than the sewer system or treatment plant can handle. The system

designed to overflow when collection system capacity is exceeded, resulting in a

combined sewer overflow (CSO) that discharges wastewater directly to surface

waters such as rivers, lakes and coastal areas (see Figure 1a and 1b). The

wastewater the CSOs carry not only contains stormwater but also untreated

human waste and industrial waste, toxic materials and floating debris (U.S. EPA,

2004).

ing

ring

s are

4

Figure 1a. Typical CSO outfall pipe. Image Source: Larson Design Group. Figure 1b. CSO outfall along Alewife Brook.

Before sewer systems were created, human waste was dumped into privy

vaults and cesspools. As population and urbanization rapidly increased during the

1800s, the need for more effective sanitary systems became clear. Municipalities

began installing sewer systems to protect public health and to deal with aesthetic

and flooding concerns (U.S. EPA, 2004). There was little precedent for the

design and construction of underground sewer systems and engineers did not want

to experiment with expensive capital works (Tarr, 1996). While the first

comprehensive sewer system was designed for the city of

Chicago in 1858, extensive construction of municipal sewer systems did not start

until the 1880s2 (U.S. EPA, 2004).

Municipalities in the United States installed sewer systems using two 2 For instance, Boston’s Metropolitan Sewerage District (MSD) was formed in 1889 to build one of the first regional sewerage systems in the country (MWRA, 2008). Expansions to the sewerage system continued through the early 1900s. The system soon became recognized as one of the best in the country, despite the fact that it provided no treatment and merely collected the wastewater and sent it out into Boston Harbor. It was not until the completion of the Nut Island Primary Wastewater Treatment Plant in 1952 that sewage from the collection system received treatment (MWRA, 2008). This facility included grit and screening removal, primary sedimentation, chlorination, sludge digestion and discharge to the harbor on the outgoing tide (MIT Sea Grant College, 2008).

5

predominant design options. These were combined sewer systems -- whereby

domestic, commercial and industrial wastewater, and stormwater runoff are

collected and conveyed in a single pipe system (See Figure 2), and separate

sanitary sewer and storm sewer systems -- whereby domestic, commercial and

industrial wastewater, and stormwater runoff are collected and conveyed using

two separate systems of pipe (See Figure 3).

Figure 2. Combined sewer system in dry and wet weather. Source: U.S. EPA, 2004.

Figure 3. Separate sewer system in dry and wet weather. Source: U.S. EPA, 2004.

6

Combined sewer systems were less expensive for cities and towns needing

both sanitary and storm sewers, while SSSs were less expensive for those needing

only a wastewater collection system (U.S. EPA, 2004). Due to these differences,

large cities tended to construct CSSs, given the flood control advantages offered

by such systems, whereas smaller communities generally pursued construction of

separate sanitary and storm sewers (Melosi, 2000; U.S. EPA, 2004).

Today, across the country there are 746 communities with combined

sewer systems with a total of 9,348 CSO outfalls that are identified and regulated

as point sources by 828 NPDES permits3. Combined sewer systems are found in

32 states (including the District of Columbia) and nine EPA Regions. CSO

communities are concentrated in older communities in the Northeast, Great Lakes

and Pacific Northwest regions4, although they have a presence throughout the

country (see Figure 4). EPA estimates that about 850 billion gallons of untreated

wastewater and stormwater are released by CSOs each year in the United States

(U.S. EPA, 2004). As a comparison, this is roughly six times more than the total

amount of gasoline that is consumed in the U.S. each year. Recent studies

indicate that, in many cities, CSOs are a major contributor to water quality

degradation and are among the sources shown to be responsible for beach closings

and limiting shellfish harvests in the Northeast and Middle Atlantic states (Smith,

1996; Barton and Fuller, 1995). According to the EPA’s 2002 National Water

Quality Inventory Report to Congress (the most recent report available), bacterial

3 As authorized by the Clean Water Act, the National Pollutant Discharge Elimination System (NPDES) permit program controls water pollution by regulating point sources that discharge pollutants into waters of the United States (U.S. EPA, 2004).

4 The reason for the prevalence of CSOs in these older cities is that these combined sewage and stormwater collection systems were used extensively in the past to save money (Vigil, 2003).

7

pathogens are among the top reported causes of impairment in assessed rivers and

streams (U.S. EPA, 2002). The sewage discharge problem is especially acute in

New England, where more than 100 communities are burdened with CSO pipes

that discharge hundreds of millions of gallons of untreated sewage and

stormwater into waterways after heavy rains (U.S. EPA, 2007a). Eliminating

these discharges is an enormous financial challenge. In New England alone, the

price tag for eliminating CSOs could run as high as $4 billion (U.S. EPA, 2007a).

Figure 4. Combined sewer overflows demographics in the U.S. Source: U.S.

EPA, 2007b.

CSO discharges have widespread impacts across New England, causing

beach closings, shellfishing restrictions and limiting fishing and other recreational

activities. In some instances, CSOs discharge raw sewage into rivers that also

serve as primary sources of drinking water. For instance, this is the case with

CSOs impacting the Merrimack River, a primary drinking water source for the

city of Lowell, Massachusetts (City of Lowell, 2002). Exposure to viruses,

8

bacteria, pathogens and other CSO-related pollutants and toxics is an obvious

public health concern. Swimmers, canoeists and others exposed to CSO

contaminants are vulnerable to gastroenteritis, respiratory infections, eye and ear

infections, skin rashes, hepatitis and other diseases (U.S. EPA, 2007a). Children,

the elderly and people with suppressed immune systems are especially vulnerable.

Additionally, the myriad industrial chemical waste pollutants that are discharged

into sewage collection systems and then subsequently released in CSO events

may pose a number of very serious health impacts -- including endocrine toxicity,

gastrointestinal and liver toxicity, immunotoxicity and respiratory toxicity

(Dorfman, 2004). Wildlife and aquatic habitat are also adversely affected by CSO

pollutants which lead to higher water temperatures, increased turbidity, toxins and

reduced oxygen levels in the water (U.S. EPA, 2007a).

Public Health Affects of CSOs

While construction of sewer systems greatly improved local sanitary

conditions, the direct discharge of untreated wastewater to local receiving waters

adversely affected downstream communities. For instance, the rate of typhoid

deaths during the 1880s and 1890s rose in cities with drinking water intakes

downstream of untreated wastewater discharges (Tarr, 1996). As bacterial

analysis confirmed the link between sewage pollution in rivers and epidemics of

certain diseases, views on the safety of discharging untreated wastewater directly

to receiving waters began to shift toward the end of the 19th century (Tarr, 1996).

9

Although the dangers of discharging untreated wastewater directly to

receiving waters has been partially addressed with wastewater treatment plants, in

watersheds with CSOs many of the health impacts of sewage pollution continue to

affect waterways and the public that live, work and play along their shores. Of

the many negative impacts of CSO discharges, some of the most serious and

closely studied are the impacts on public health. Researchers from the Johns

Hopkins School of Public Health report that the highest incidence of waterborne

illnesses in the United States are associated with heavy rain storms, presumed to

be due to the effects of wastewater overflows and stormwater runoff (Curriero, et

al., 2001). These results are consistent with findings from other studies such as a

study by Atherholt et al. (1998), who found that concentrations of

Cryptosporidium oocysts and Giardia cysts in the Delaware River were positively

correlated with rainfall. There has been extensive study of the contents of

untreated sewage and the other components of the CSO-discharged effluent.

Within one drop of fecal material can be found millions of microorganisms of

many types, including those that are pathogenic (Rose, et al., 1999). Microbial

pathogens in sewage can cause a range of illnesses, varying from minor stomach

cramps to deadly conditions, such as inflammation of the heart (Dorfman, 2004).

Giardiasis, a protozoan infection caused by Giardia, is the most commonly

reported intestinal disease in North America (National Research Council, 1993).

CSOs are known to be a very significant source of Giardia and Cryptosporidium

(Medema and Schijven, 2001; Gibson et al., 1998). In one study, CSO end-of-

pipe discharge was found to contain concentrations of Cryptosporidium that were

10

77 times greater than dry weather in-stream concentrations and concentrations of

Giardia that were 103 times greater than dry weather in-stream concentrations

(Gibson et al., 1998). In an article published in the International Journal of

Epidemiology, 22 epidemiological studies on health effects from exposure to

recreational water were reviewed (Prüss, 1998). This review suggests that there is

a causal relationship between gastro-intestinal symptoms and recreational water

quality, measured by indicator bacteria concentration, because they report a strong

and consistent association with temporality and dose-response relationships

(Prüss, 1998). An additional 1998 study published in the International Journal of

Epidemiology detailed that one-third of reported gastroenteritis cases and two-

thirds of ear infections were associated with swimming in sewage-contaminated

marine waters (Fleisher et al., 1998).

Additionally, raw or inadequately treated sewage can contaminate edible

filter-feeding shellfish, such as clams, mussels, scallops and oysters. These in

turn can reinfect humans with concentrations of viruses that are 100 to 900 times

greater than in surrounding waters (Dorfman, 2004). At least 100 national

outbreaks of hepatitis and viral gastroenteritis have been associated with sewage-

contaminated shellfish (National Research Council, 1993). According to studies

by the National Academy of Sciences and the Centers for Disease Control and

Prevention, most seafood-associated illnesses are caused by seafood contaminated

by raw or inadequately treated sewage (Ahmed, 1991; CDC, 1990; CDC, 1996;

CDC, 1995).

11

CSOs and other sources of untreated sewage can also affect water

resources by limiting people’s access to these water bodies once they have been

contaminated. The primary pollutants found in CSOs and SSOs affecting

recreational uses at beaches are microbial pathogens and floatables (U.S. EPA,

2004). Beach closures result from exceedances of bacterial standards, when the

water is deemed unsafe for contact recreation (i.e., swimming poses an

unacceptable risk of illness) (U.S. EPA, 2004). For instance, CSOs, SSOs and

discharges of inadequately treated sewage from treatment plants in 2002 were

responsible for 25 percent of closing and advisory days at U.S. beaches (Dorfman,

2003). In addition to national data, there is much state level data identifying

sewage pollution as the primary cause of bacterial standard exceedances leading

to beach closures. For instance, in its 2001 Annual Report, the Connecticut

Council on Environmental Quality reported on beach closures caused by

discharges of untreated or poorly treated wastewater, which Connecticut

identified as the most common cause of elevated bacteria levels (CTCEQ, 2002).

In addition to the numerous public and aquatic health risks that CSO

discharges pose, CSOs can also cause serious impairment of aesthetics in the

receiving waters (Marr and Freedman, 1997). CSOs carry an assortment of debris

from storm runoff and sanitary sewage wastes, including sanitary products,

plastics, other floatables, oils, grease and suspended solids (Marr and Freedman,

1997). CSO discharges also tend to emit the noxious odors of sewage in the

vicinity of the receiving waters, which significantly impairs the aesthetic quality

of these waters. Although aesthetic impairment may not pose direct human or

12

aquatic health risks, it can have significant socioeconomic impacts by reducing

recreational use and near-shore development (Marr and Freedman, 1997). While

quantitative analyses of aesthetic reduction are rare in the literature, they can be

done (AMSA, 1996). Even where difficult to quantify, aesthetic reduction can

impose substantial burdens on communities. Furthermore, it tends to be the most

localized impact of CSOs and has a more acute affect on the areas immediately

adjacent to outfalls.

Mystic River Watershed

One area that is heavily burdened by this type of pollution and that will

serve as the focal point of this research is the Mystic River Watershed. The

Mystic River Watershed consists of approximately 76 square miles of heavily

populated and urbanized land encompassing 21 communities north and west of

Boston, Massachusetts. The watershed is a sub-watershed of Boston Harbor and

includes a number of its own distinct sub-watersheds. Its headwaters begin in

Reading and form the Aberjona River, which flows into Upper Mystic Lake in

Winchester. The Mystic River flows roughly 7.5 miles from the Lower Mystic

Lake to the southeast through Arlington, Medford, Somerville, Everett,

Charlestown, Chelsea and East Boston, before emptying into the Boston Harbor

(see Figure 5). The main tributaries of the Mystic River include Mill Brook,

Alewife Brook, Malden River and Chelsea Creek. Since its settlement in the

1600s, the Mystic has undergone profound changes in hydrology and water

quality, all the while suffering from a long history of industrial pollution, urban

13

non-point source pollution and combined sewer overflows (MyRWA, 2006).

While the river and watershed were initially used for fishing and farming,

factories dominated the river by the 1800s, and overfishing and pollution had all

but eliminated commercial fishing along the river by 1865. Leather tanning and

finishing became a prominent industry along the river, as did chemical

manufacturing, rendering, and tool and machine-making (MyRWA, 2006).

Unfortunately, due to improper waste disposal practices, these industries released

into the watershed hazardous materials such as oil and gasoline, chlorinated and

non-chlorinated solvents, coal tar and plasticizers. These waste materials are still

present in soil and groundwater at the sites where they were released and, in some

locations, have migrated to surface waters (Durant and Abbasi, 2000). Thus, each

of these industries has left a legacy of contamination in the river, much of which

remains today (Durant et al., 1990; MyRWA, 2006). In fact, in January 2008,

after reviewing fish toxics data generated by the state Department of

Environmental Protection for the Mystic River, the Massachusetts Department of

Public Health (MDPH) issued a P6 advisory, the state’s most restrictive advisory

level, indicating that no one should consume any fish from the river. This

advisory was due to the fact that PCBs (polychlorinated biphenyls), the pesticide

chlordane, and the pesticide DDT and its derivatives were detected in fish caught

from the Mystic River in concentrations above levels that MDPH considers safe

for consumption (Winchester Star, 2008). In addition to the long-time burden of

industrial pollution, the watershed today also faces water quality issues related to

14

urban growth and development, of which sewage and stormwater runoff are the

most salient.

Figure 5. Mystic River Watershed. Source: U.S. EPA, 2007c.

According to federal estimates, approximately 84 million gallons of sew-

age and stormwater runoff were polluting the Mystic River in 2005, the last year

for which full measures are available (Nickerson, 2007). The most important

current pollutant sources throughout the watershed are likely to be general urban

15

runoff and sewage discharges from CSOs and inadequate stormwater and sanitary

sewer systems (MyRWA, 2006). Within the Mystic River Watershed, CSOs are

permitted for the following sources: Boston Water and Sewer Commission

(Chelsea Creek & Mystic River), City of Cambridge (Alewife Brook), City of

Chelsea (Chelsea Creek & Mystic River), the Massachusetts Water Resources

Authority (MWRA) (Mystic River, Alewife Brook) and City of Somerville

(Mystic River & Alewife Brook). There are also substantial numbers of Sanitary

Sewer Overflows (SSOs)5, which are illegal under the Clean Water Act, and

illegal sewer hookups6 that contribute bacteria loads to receiving waters

throughout the watershed.

Environmental Justice

While environmental burdens, such as pollution, are widespread across the

nation and across the state of Massachusetts, the communities within these areas

do not bear those burdens equally. For instance, a 2005 study of environmental

justice problems in Massachusetts showed that low-income communities in

5 Sanitary Sewer Overflows (SSOs) refer to overflows of sanitary sewer systems, which convey only domestic, industrial and commercial wastewater (sanitary sewage) to a wastewater treatment plant, and are not designed to carry large amounts of stormwater runoff (US EPA, 2004). While a significant issue in their own right, SSOs will not be a focus of this study. Data suggest that comparatively, SSOs are a significantly smaller issue than CSOs. For example, in 2004, the EPA reported that the total SSO volume discharged annually was between 3 and 10 billion gallons, far less than the 850 billion gallons from combined sewer systems -- although the SSO effluent was raw sewage, while the CSO discharges had been diluted by somewhat cleaner stormwater (U.S. EPA, 2004).

6 Illegal sewer hookups by homes and businesses direct rainwater from basement sump pumps, roof gutters and leaders into sanitary sewer pipes that can overload municipal plants and cause sewage to overflow. Despite their significance, illegal sewer hookups will not be a focus of this study.

16

Massachusetts face a cumulative exposure rate to environmentally hazardous

facilities and sites that is four times greater than high-income communities

(measured by median household income) (Faber and Krieg, 2005). In addition,

high-minority communities face a cumulative exposure rate to environmentally

hazardous facilities and sites that is over 20 times greater than low-minority

communities (Faber and Krieg, 2005).7 This study further showed that 8 out of

the 15 communities found to be the “most intensively overburdened”8 by

cumulative environmental hazards are located within the Mystic River Watershed

(Faber and Krieg, 2005).

Environmental justice is a contested and problematic concept. Thus,

defining it is no easy task (Agyeman, 2005). Within both academic discourse and

within the advocacy community, there are numerous definitions of environmental

justice communities.9 Holifield (2001) reminds us that grassroots activists and

government agencies use the term to apply to a wide variety of distributive and

procedural concerns and academics must not impose artificial limits on the scope

of the phrase. He asserts the importance of context-specific meanings of the term,

noting that environmental justice “might have one meaning for a community

fighting for cleanup of a Superfund site and another meaning for one struggling to

7 In order to determine the respective cumulative exposure rates in this study, the researchers developed a point system that weighs the average risks of each of various type of hazardous facility/site to arrive at a cumulative measure of community exposure to all potential hazards (controlling for each community’s area) (Faber and Krieg, 2005). However, the study does not explain how the comparative risks were arrived at, so it is difficult to determine the merit of this technique. A few examples of the point system for various hazards includes EPA National Priority List Sites at 25 points, DEP TIER 1A Sites at 10 points, and DEP TIER 1B sites at 8 points (Faber and Krieg, 2005).

8 Faber and Krieg (2005) define the “most intensively overburdened communities” as those containing the most hazard points per square mile.

9 Further discussion on defining environmental justice can be found in the literature review portion of this paper.

17

have a wastewater treatment plant built” (Holifield, 2001, p.82). The primary

claim of the environmental justice movement is that a variety of environmental

burdens (such as toxic waste sites, polluted air and water, dirty jobs and

underenforcement of environmental laws) have fallen disproportionately on low-

income persons and communities of color (Foreman, 1998). Put simply,

environmental justice means “that environmental hazards should be distributed

equally across society and that no individual, group, or community should bear a

disproportionate burden from this type of health threat. Second, and more ideally,

it means that no one should be forced to suffer from the adverse effects of

environmental hazards” (Stretesky and Hogan, 1998, p.268). The concept also

refers to just and equitable access to the procedural aspects of environmental

governance, such as monitoring and enforcement (Bryant, 2003). Environmental

justice is sometimes known by its more incendiary name, environmental racism,

which refers to “any policy, practice, or directive that differentially affects or

disadvantages (whether intended or unintended) individuals, groups, or

communities based on race or color. Environmental racism combines with public

policies and industry practices to provide benefits for whites while shifting

industry costs to people of color” (Bullard, 2000, p.98).

Perhaps most important, however, are the definitions used by

environmental regulatory agencies, because these have a direct bearing on how

relevant policies are made and enacted. The U.S. Environmental Protection

Agency, for instance, defines environmental justice as:

18

the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies. EPA has this goal for all communities and persons across this Nation. It will be achieved when everyone enjoys the same degree of protection from environmental and health hazards and equal access to the decision-making process to have a healthy environment in which to live, learn, and work (U.S. EPA, 2007d).

The Commonwealth of Massachusetts uses the following definition in its

own Environmental Justice Policy:

Environmental justice is based on the principle that all people have a right to be protected from environmental pollution and to live in and enjoy a clean and healthful environment. Environmental justice is the equal protection and meaningful involvement of all people with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies and the equitable distribution of environmental benefits (Massachusetts EOEA, 2002).

This definition of environmental justice is particularly useful in the context of this

study, given that my analysis takes place in Massachusetts. Furthermore, this

definition has been adopted by policymakers at the level of the state government

and thus holds traction in the relevant political arenas.

Further, according to the Massachusetts Executive Office of Energy and

Environmental Affairs (EOEEA), environmental justice populations are those that

EOEA has determined to be most at risk of being unaware of or unable to

participate in environmental decision-making, or unable to gain access to state

environmental resources. They are grouped in neighborhoods (U.S. Census

Bureau census block groups) that meet one or more of the following criteria:

• The median annual household income is at or below 65 percent of the

19

statewide median income for Massachusetts; or

• 25 percent of the residents are minority; or

• 25 percent of the residents are foreign born, or

• 25 percent of the residents lack English language proficiency,

(Massachusetts EOEEA, 2002).

Despite its somewhat arbitrary designations, this definition of environmental

justice populations is especially useful for a precision that permits the application

of spatial and non-spatial analytic tools.

Watershed communities that are characterized by low income, a high

proportion of immigrant residents, or a high proportion of minority residents often

suffer from disproportionate exposure to pollution and lack of access to

environmental amenities (MyRWA, 2006). As noted above, 8 out of the 15

communities found to be the “most intensively overburdened” by cumulative

environmental hazards are located within the Mystic River Watershed (Faber and

Krieg, 2005). Moreover, communities of color make up 63 percent of the 30 most

extensively overburdened communities in the state and 80 percent of the 30 most

intensively overburdened communities – what the researchers consider to be the

most environmentally hazardous towns in the state10 (Faber and Krieg, 2005).

Although this study addressed air pollution and hazardous waste sites, it is likely

that a similar study of water-related problems would show the same

disproportionate impacts on environmental justice communities. However, such

an analysis has yet to be performed.

10 Faber and Krieg (2005) define “most intensively overburdened communities” as those containing the most hazard points per square mile and “most extensively overburdened communities” as those containing the most hazard points per town.

20

Much literature and data exist on the disproportionate burdens of

environmental pollution on environmental justice communities in general, and of

air pollution and locally undesirable land uses (LULUs) in particular. However,

little research appears to exist on the location of CSOs (or other sources of water

pollution) in relationship to EJ communities. It appears that no such analysis has

been conducted within the Mystic River Watershed, and few such analyses have

been completed elsewhere in the country.11

Given the already environmentally overburdened nature of many of the

communities in the watershed, and the clear evidence of substantial discharge of

sewage into the Mystic River and its tributaries by CSOs, it is reasonable to

suppose that these communities may be significantly affected by this pollution.

However, it has not been determined whether those communities defined as

environmental justice populations are disproportionately burdened by such

pollution as compared with non-environmental justice communities. Given that

the majority of the municipalities in the lower (downstream) portions of the

watershed are environmental justice communities, it is likely that these

communities bear a disproportionate burden from CSO discharges into the

watershed. If such a correlation were identified and verified through sound data

analysis, it would raise numerous policy and planning questions -- both with

regard to what caused this inequity as well as how it might be rectified.

11 In my review of the literature, I found only two studies that examined this issue at all. The first, by Neltner (2005), addresses the issue of CSOs located in the primarily minority neighborhoods along Fall Creek and White River in Indianapolis, Indiana. The second, a master’s thesis by Rice (2005), uses GIS to examine environmental justice concerns related to sewer overflows in Columbus, Ohio. Both sources will be discussed further in the methodology portion of this paper.

21

Chapter Two: Review of the Literature

There is a vast and rich literature about environmental justice -- including

much scholarship simply about how the term should be defined. Readers may

look to Capek (1993) Bullard (1994), Szasz and Meuser (1997), Pellow (2000),

and Schlosberg (2007), among others, for very useful discussions on this front.

Other analyses consider problems with the conceptualization of racism (Pulido,

2000), examine the treatment of environmental justice in conceiving and

operationalizing sustainability (Agyeman, et al., 2003; Agyeman, 2005), explore

the definition of community (Williams, 1999), and examine issues of unequal

enforcement of environmental laws, including discriminatory zoning (Bullard,

1996). Still others question whether environmental injustices are merely by-

products of a market-based economy, arising more from differences in housing

markets than overt discrimination (Been, 1994; Been, 1995; Hamilton, 1995).

This particular debate has employed longitudinal studies of burdened areas over

time to try to answer the question of which came first, a specific environmental

burden or the people in the surrounding neighborhood (see, for instance, Been &

Gupta, 1997; Oakes et al., 1996; and Pastor et al., 2001). While all of the above

issues are of critical importance to understanding the socio-economic distribution

of environmental burdens, perhaps a more fundamental question is how

environmental justice violations are identified and gauged. The incendiary nature

of claims of environmental injustice (or even environmental racism) raises the

stakes and underscores the need for evidence. As Greenberg (1993, p. 236), puts

it, “the stigma of being branded a racist organization is so odious that the

22

accusation demands proof.” Moreover, to develop substantive assessments that

permit planners and policymakers to redress any revealed environmental

inequities, it is critical to understand how researchers may most effectively

examine and identify environmental injustices. Although numerous aspects of

environmental equity have been explored in the literature, I will be examining two

particularly important topics here -- the effect that spatial scale has in the study of

environmental equity, and the use of proximity analyses to assess pollutant

exposure potential.

Statistical and GIS-based studies of demographic patterns around locally

undesirable land uses (LULUs) – primarily toxic sites – form the backbone of

environmental justice research (Holifield, 2001; Foreman, 1998). Most of this

research has demonstrated that race and class are important determinants of

environmental exposure and environmental health impacts (Brown, 1995; Mohai

and Bryant, 1992). In assessing the distribution of hazards by income, the typical

approach has been to correlate the average or median household or family income

of the community – usually by U.S. Census tracts or ZIP code areas – with the

degree of exposure to the hazard (Mohai and Bryant, 1992). In assessing the

distribution of environmental hazards by race, the minority percentage of the

community has generally been utilized (Mohai and Bryant, 1992). Among such

studies, perhaps the most famous is the one sponsored by the United Church of

Christ’s Commission for Racial Justice in 1987 (UCC CRJ, 1987). This was the

first national study to examine the distribution of commercial hazardous waste

facilities and abandoned hazardous waste facilities by race and income (Mohai,

23

1995). This study compared ZIP codes that had no hazardous waste treatment,

storage or disposal facilities (TSDFs) to ZIP codes that did. The study found that

the percentage of minority residents in communities containing a hazardous waste

facility was twice as great as the percentage of minority residents in communities

not containing a facility (24 percent versus 12 percent) (UCC CRJ, 1987). It also

found that the minority percentage in communities containing more than one

facility or containing one of the nation’s five largest landfills was three times

greater (38 percent) (UCC CRJ, 1987). The study additionally found that three

out of every five Black and Hispanic Americans lived in communities with

uncontrolled toxic waste sites. It concluded: “indeed, race has been a factor in the

location of commercial hazardous waste facilities in the United States” (UCC

CRJ, 1987, p. 15). From a multivariate statistical analysis, the study found race to

be the best predictor of the location of these facilities from among other factors

examined (Mohai, 1995).

While certainly groundbreaking and influential, the UCC study has not

been without criticism and challenge (Brown, 1995; Anderton, et al., 1994,

Mohai, 1995). A 1994 study conducted at the University of Massachusetts Social

and Demographic Research Institute (SADRI) by Anderton et al. found little

difference in the minority percentages of areas containing hazardous waste

facilities and those without. This is a very significant disagreement, given that

both studies examined the distribution of commercial hazardous waste facilities

on a national scope (Mohai, 1995). The disparate findings have raised much

debate within the advocacy and academic communities and inspired a great deal

24

of scholarship examining issues surrounding environmental justice research

methodologies. Two particularly useful studies on this front include Mohai

(1995) and Been (1995), which together help illuminate important methodological

issues.

The units of analysis of a study are the objects measured or sampled in

order to determine important characteristics about larger groupings or areas

(Mohai, 1995). Many environmental justice spatial studies, such as the UCC and

UMass studies, use geographic areas as their units of analysis. Choosing different

units of analysis within the same study can have dramatic effects on the results of

a study. While the UCC study used geographic areas defined by ZIP codes, the

UMass study chose areas defined by Census tracts (UCC CRJ, 1987; Anderton, et

al., 1994). The UMass study authors argue for the use of Census tracts over ZIP

codes by insisting that:

Because geographic data can be aggregated to produce information on larger regions, it seems reasonable to begin with an analysis of areas that are as small as is practical and meaningful. Beginning with too large a geographic unit invites the possibility of ‘aggregation errors’ and ‘ecological fallacies’; that is, reaching conclusions from a larger unit of analysis that do not hold true in analyses of smaller, more refined units (Anderton, et al., 1994, p.232).

While arguing that the primary discrepancy between the UCC and UMass

studies was based on choice of comparison populations, Mohai (1995) also

highlights the importance that the choice of unit of analysis had on the studies’

outcomes. Mohai (1995) suggests that while the UMass authors acknowledge the

advantage of using smaller units of analysis as building blocks to cover larger

geographic areas, they fail to discuss the shortcomings of focusing their analysis

25

on geographic areas that may be too small. He argues that the use of such units of

analysis may underestimate the extent of the impacts on neighboring units, thus

lumping adversely impacted areas with the control population and thereby

diluting the differences between the two populations being compared (Mohai,

1995). Essentially, Mohai cautions that adverse affects from an environmental

hazard may extend well beyond a unit’s boundaries if the chosen unit of analysis

is too small. Therefore, adversely impacted areas may not be adequately

accounted for when using too small a unit of analysis.12

Numerous scholars have taken up the issue of geographic scale in

addressing inconsistencies in measurement and analysis. It has become clear that

the choice of scale of the study area (e.g., states, counties, municipalities,) and the

spatial resolution of data within that study area (such as ZIP codes, Census tracts,

Census block groups13) has a significant influence on the results of a given

investigation (Sheppard et al., 1999). Scholars have pointed out that many of the

contradictions found between similar environmental justice mapping studies can

be traced to the geographic unit of analysis used in the study (Maantay, 2002).

12 It is also important to note that even beyond purely methodological concerns, some have questioned the impartiality of certain researchers conducting environmental equity studies. The study by Anderton, et al. (1994), for example, which suggested that the waste industry is definitely not racist in making siting decisions, was funded by Waste Management Incorporated, the largest waste handler in the world (Pulido, 1996). In their study, the University of Massachusetts researchers go even as far as to suggest that hosting a toxic waste repository may provide benefits that balance out the negative effects (Anderton, et al., 1994, p.125). Therefore it can, be difficult to distinguish between the effects of varying methodologies and the possibility of bias.

13 Census tracts are small, relatively permanent statistical subdivisions of a county delineated by local participants as part of the U.S. Census Bureau's Participant Statistical Areas Program. Census tracts generally have between 1,500 and 8,000 people. A Census block group is a cluster of Census blocks and generally contains between 600 and 3,000 people. A Census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses). The population of a Census block varies greatly. Several blocks make up block groups, which again make up Census tracts (U.S. Census Bureau, 2005).

26

This incompatibility between spatial areas leads to an issue known as the

Modifiable Areal Unit Problem (MAUP) (Openshaw and Taylor, 1981), in which

is the result of a given spatial analysis depends on the arbitrary spatial basis of the

data used. An example of this can be found in the environmental equity study by

Cutter & Solecki (1996), which examined airborne toxic releases in the

Southeastern United States. When using Census tract data, these researchers

found no statistically significant association between the location of racial

minorities and economically disadvantaged persons, and toxic facilities. But

when using county-level data their findings suggested a positive correlation

between more urbanized, white, middle-income counties and toxic facilities.

Glickman (1994) also found that as the resolution in his Pittsburg study was

coarsened from Census block groups to Census tracts to ZIP code areas, the

percentage of minority population became a more significant factor in explaining

the incidence of TRI sites.

Upon modifying the geographic boundaries of the study area in their

examination of industrial hazards, Glickman and Hersh (1995, p.89) find that “the

choice of unit of analysis will affect even the most basic findings of an

environmental equity study.” Maantay (2002) points out that data aggregated at

higher levels of governmental units (such as county or city) will be less reliable as

indicators of disproportionate burdens and less accurate in identifying the affected

populations than will data aggregated by smaller units (such as Census block

groups or Census blocks). Additionally, Sheppard et al. (1999) note that coarse

spatial data often do not permit accurate assessment of the differential potential

27

exposure of different subpopulations, because of the heterogeneity of the

population within these enumeration units. This problem can be addressed by

using finer spatial resolution, such as Census block groups and blocks as opposed

to Census tracts or ZIP code areas. This, however, must be balanced against the

fact that this use of spatial resolution data which is too fine may mask trends that

emerge only at higher scales of resolution. This was the case with Glickman’s

(1994) study and the trends apparent in the United Church of Christ’s examination

of hazardous waste facilities at the ZIP code level – trends that were not apparent

at the Census tract level in the study of the same facilities by Anderton, et al.

(1994).

McMaster et al. (1997) have also demonstrated the influence of scale on

results. In their study of TRI facilities in the Twin Cities, they found a stronger

relationship between persons of color and TRI sites at the county scale, while a

stronger income-based rather than race-based pattern of inequity was observable

at the city of Minneapolis level. Bowen et al. (1995) also find contrasting results

in their environmental equity analysis for the state of Ohio and the Cleveland

metropolitan area. At the state level they find a high positive correlation between

minority populations, and toxic sites and release volumes. But at the metropolitan

scale, minority density and toxic releases are inversely related, and income-based

inequity is instead identified.

In framing their analysis of county-level TRI data, Daniels & Friedman

(1999) note that there is no reason to expect that relationships at one geographic

level, will behave in the same manner as relationships at another level and to

28

assume that they do is to commit the ecological fallacy.14 After evaluating

several studies that utilize multiple geographic levels in their examinati

environmental equity, the authors conclude that the superiority of one unit over

another cannot be inferred from substantive results and that relationships at a

variety of analytical levels are inherently interesting and so should be investigated

(Daniels & Friedman, 1999).

ons of

Geographic Information Systems (GIS) have increasingly been used

within the last two decades in environmental equity analysis (Sheppard et al.,

1999; Maantay, 2002). GIS allows for the integration of different data sources

necessary for such analyses such as location of hazardous sites, population

characteristics, application of spatial analytic techniques, integration of spatial

models of potential exposure, and the visual representation of complex data in

map form (Sheppard et al., 1999). GIS also allows for integrating greater

complexity of variables and data components into analyses in order to correct for

some of the limitations of traditional spatial studies.

For instance, to identify appropriate scales of analysis (and to avoid pre-

determined units), Fisher et al. (2006) apply a point pattern statistical approach.

This method examines the test statistic across various spatial scales to reveal the

scale at which the pattern of events is operating most strongly. Here the authors

employ a spatial point pattern based on Ripley’s K-function (Ripley, 1976), which

has been used broadly in ecological spatial patterns (Fisher et al., 2006). This

14 The ecological fallacy is a widely recognized error in the interpretation of statistical data in an ecological study, whereby inferences about the nature of individuals are based solely upon aggregate statistics collected for the group to which those individuals belong. This fallacy assumes that all members of a group exhibit characteristics of the group at large.

29

approach addresses the distributive theory of equality in questioning whether or

not certain communities are burdened with a disproportionate number of facilities

(Fisher et al., 2006). Given the numerous problems with defining the appropriate

measure of scale and the criticism that the choice of target predetermines the

evaluation of social impact, in Fisher et al’s (2006) study scale becomes a variable

rather than a pre-determined measure. The authors thus combine a spatial point

pattern with GIS in order to identify not only statistically significant areas of toxic

facility clusters but also the scales at which those clusters exist.

Maantay (2002) makes the important point that, to date, most

environmental equity mapping has been restricted to facilities and other burdens

that appear on federal lists -- and that this is so because of the availability and

standardization of these lists. Although analysis of these risks is certainly

important, it only looks at a few of the environmental burdens in many

communities. It is the small polluters, she argues, that cumulatively may be

creating more environmental risk than the large facilities, because the former are

more concentrated at the community level, while often being unregulated (and

sometimes undetected) (Maantay, 2002).

In underscoring the need for neighborhood-scale studies, Maantay (2002)

points out that, by definition, studies covering larger geographies use coarser

resolution data and cannot as accurately locate the spatial patterns and

connections that might exist. She and other researchers have emphasized that

neighborhood-scale analysis can assist communities in identifying the risks that

environmental hazards pose to different social groups in a given community. By

30

incorporating “local knowledge” into their analysis, this fosters increased

accuracy and relevance to the community, while directly involving the affected

people in the project (Maantay, 2002; McMaster et al., 1997).

Proximity Analysis and Pollutant Exposure

Although the debate surrounding efforts to select the most appropriate

scale for environmental equity studies has by no means been resolved, it has at

least received substantial attention by researchers. An equally important

methodological issue that has emerged in the field of environmental equity

research, but which has received far less attention, is the appropriate assessment

of the exposure potential of communities that surround environmental hazards.

As Cutter and Solecki (1996) note, there is a dearth of empirical evidence on the

actual pollution burdens and potential exposures arising from environmental

hazards. Maantay (2002) also posits that a common limit of many studies is their

assumption that all noxious facilities are equally noxious. She makes the

important point that emission levels, toxicity and exposure pathways in a given

community are critical to accurately assessing environmental equity across a

specific landscape (Maantay, 2002).

Some researchers have successfully incorporated exposure data into their

studies. One such study examined the exposure to air pollutants in U.S

metropolitan areas, finding that poor inner-city residents (many of whom were

African American) had the greatest exposure to such pollutants (Berry, 1977).

Another study mapped the spatial distribution of TRI releases in pounds of

31

emissions per year for the Southeast by county, examining both the quantity and

toxicity of emissions (Stockwell et al., 1993). Cutter (1995) examined risk

measures by number of toxic releases, quantity of emissions, and quantity of

hazardous waste generated at the county level in South Carolina.

Maantay (2002) criticizes as simplistic the determination of exposure

levels by whether the population is in the same geographic unit (ZIP code, Census

tract, etc) as the noxious facility. This approach doesn’t take into consideration

the possibility that a facility is at the edge of a geographic unit. In such a case,

this type of measure would thus include populations that are within that unit but in

reality might be far away from the facility, while other populations might be

directly across from the facility, but be discounted as they are in a separate

geographic unit. One means of correcting for this is through the use of proximity

measures. For instance, buffer zones of specified distances might be placed

around the facility in order to capture the demographic data for the population

within that zone, regardless of their enumeration unit. These buffer zones would

serve as surrogates for the areas of impact (Maantay, 2002), and thus depend upon

an accurate assessment of the impact zone of the particular hazard.

While proximity analysis is a more accurate means of analysis, it does not

necessarily determine the potential for exposure. As Been and Gupta (1997, p.12)

point out, “a better unit of analysis would be one that was based upon the actual

distribution of the risk of the facility, which would depend on the type of

substances the facility handled, wind patterns, the hydrology and geology of the

site, transportation routes to the facility, and many other factors.” Pollock and

32

Vittas (1995) echo this point, emphasizing that previous environmental equity

studies lack a model describing the relationship between proximity to sources of

pollution and likelihood of exposure. Some researchers, most notably

Chakraborty and Armstrong (1995, 1997), have detailed the methodology through

which to more accurately determine the demographic distribution of toxic releases

by employing a geographic plume analysis that takes a pollution dispersion model

and superimposes it on a demographic database. This approach will be explored

further in the methodology section of this thesis. While emphasizing the need for

detailed analysis like this, Maantay (2002) cautions that the many factors

influencing exposure are very complicated and often the data simply do not exist

to perform this level of analysis. Rather, she advocates the development and use

of exposure indexes that more accurately predict exposure factors for identified

hazards, and estimates total environmental loading that results from all types of

pollutants in a given area (Maantay, 2002). A fairly detailed review of the various

approaches to environmental equity assessment, including their relative strengths

and weaknesses, can be found in Mitchel and Walker (2006).

Although it is critically important to accurately assess the equity of the

distribution of noxious facilities and pollution sources, as the environmental

justice movement matures it will also be essential to demonstrate clearer linkages

between environmental burdens and adverse health affects. A survey of the

environmental justice literature suggests that while important strides have been

made on this front, there remains much ground to be gained in establishing these

unequivocal connections.

33

Chapter Three: Research Methodology

My research proceeded through several steps. First, I gathered spatial data

on the location of active CSO outfalls within the Mystic River Watershed, as well

as the location of historically remediated (closed) CSOs. I also collected data on

the demographic characteristics (at the Census block group15 level) of the

communities within the watershed so that I was able to compare demographic

characteristics of those communities that are adjacent to CSOs with those that are

not.

Once compiled, these data were projected in ArcGIS software and mapped

and analyzed in various ways in order to examine the spatial relationship between

the CSOs and the demographics of the communities in the watershed. The unit of

analysis was the Census block group, for the reasons enumerated below. The

study area consisted of a sample of block groups from within the larger watershed

-- including all block groups that abut the river and that therefore could host a

CSO outfall. Thus, the comparison population served as those block groups that

could host a CSO outfall or that could fall within their zone of influence, but

which do not. This analysis was be conducted at the Census block group level for

communities surrounding CSO outfall points, and included a 0.25 mile buffer

downstream of discharge points to capture block groups within this zone of

critical influence.16 In addition to spatial analysis, comparison of statistical

15 A Census block group is a cluster of Census blocks and generally contains between 600 and 3,000 people; Census tracts are made up of numerous Census block groups.

16 The choice of the downstream buffer zone was based on currently available data on engineering and regulatory mixing zones for CSO discharges. It is discussed in more detail below.

34

demographic data was also performed to evaluate the significance of

distributional patterns by demographic characteristics.

CSO Data Collection

This CSO point data was collected from the Massachusetts Water

Resources Authority (MWRA).17 While not all of the CSO outfalls within the

watershed are technically owned by the MWRA -- in fact, many are owned by the

municipalities in which they reside -- there was a stipulation in the Boston Harbor

Case18 that MWRA would have overall responsibility for all outfalls hydraulically

connected to their sewer system.19 As a result, MWRA amassed information and

data on all of the CSO outfalls during its planning process, including GIS point

and attribute data for all of the active CSOs, as well as most of the closed CSOs,

within the Mystic watershed. I obtained GIS data points from MWRA for 26

active CSO outfalls and 8 closed outfalls within the watershed. These CSO points

were cross checked against maps of CSO infrastructure published by MWRA and

17 MWRA is a Massachusetts public authority established by an act of the Legislature in 1984 to provide wholesale water and sewer services to 2.5 million people and more than 5,500 large industrial users in 61 metropolitan Boston communities (MWRA, 2007a).

18 Since 1985, MWRA has been subject to a Clean Water Act enforcement action to end years of wastewater pollution of Boston Harbor and its tributaries from the old Deer Island and Nut Island treatment plants and combined sewer overflows (CSOs). The enforcement case was initiated by the Conservation Law Foundation in 1983 and taken up by the U.S. Environmental Protection Agency in 1985 (MWRA, 2007b).

19 In an agreement reached last year, the Boston Harbor Case stipulation which had assigned responsibility to MWRA for all CSOs hydraulically connected to its system was modified, based on its commitment to a $900 million CSO abatement program. The new stipulation requires MWRA to implement the $900 million plan and attain the projected level of CSO control. Beyond that, the communities will be responsible for higher levels of control (Brander, 2007).

35

EPA. For the subsequent analyses these data points were then separated into

individual data files representing active and closed CSO outfalls.

Unit of Analysis

As explored in the Literature Review, choosing different units of analysis

can have a profound effect on the results of a study. Thus, researchers should

carefully choose the most appropriate unit of analysis for their particular study,

considering the individual merits of each option. I chose to use the Census block

group as my unit of analysis in order to look at the demographic characteristics of

the communities in my study area. Census block groups are a useful unit of

analysis for a number of key reasons. A Census block group is a cluster of Census

blocks and generally contains between 600 and 3,000 people (U.S. Census

Bureau, 2005). Most importantly, block groups are the smallest entity for which

the Census Bureau collects and publishes sample data -- that is, data which are

only collected from a fraction of all households. This Summary File 3 data

consists of detailed social, economic and housing characteristics compiled from a

sample of approximately 19 million housing units (about 1 in 6 households) that

received the Census 2000 long-form questionnaire (U.S. Census Bureau, 2007).

Summary File 3 data contains some of the richest and most complete statistical

data available on U.S. residents, including data on income, ancestry, citizenship

status, home values, commute time to work, occupation, education, veteran status,

language ability, migration, place of birth and many other characteristics (U.S.

36

Census Bureau, 2003). Other researchers have indicated that, as the smallest units

for which the Census Bureau reports the necessary socioeconomic information,

Census block groups ensure the best possible degree of representativeness in

geographic areas (Cutter, Holm, & Clark, 1996; McMaster et al., 1997). Given

that this study is attempting to assess the demographics of areas immediately

affected by CSO outfalls -- highly localized impacts -- it made sense to choose the

smallest unit of analysis for which community statistical data was available. As

indicated above, that is the Census block group level.

Additionally, unlike ZIP codes, which change at the convenience of the

postal service (with no published record of changes available), Census tracts and

block groups are intended to remain relatively stable(Been, 1995). When Census

units do change, the exact nature of the changes is published (Been, 1995). Thus,

they serve as a better unit of analysis for facilitating any future longitudinal

analyses of the features under examination.

Furthermore, Been (1995) has pointed out that Census tracts (which are

made up of block groups) are drawn up by local committees and so are more

likely to reflect the community’s view of where one neighborhood ends and

another begins. Most block groups were delineated by local participants as part of

the U.S. Census Bureau’s Participant Statistical Areas Program (U.S. Census

Bureau, 2005). The U.S. Census Bureau delineated block groups only where a

local, state, or tribal government declined to participate or where the U.S. Census

Bureau could not identify a potential local or tribal participant (U.S. Census

Bureau, 2005). Been (1995) further notes that Census units (be they tracts or

37

block groups) are also comparable in populations between like units, while ZIP

codes may contain widely varying numbers of people and cover areas of widely

varying sizes.

For my analysis, I used the most recent U.S. Census data from the 2000

U.S. Census, as well as data from the prior 1990 decennial Census. The U.S.

Bureau of the Census developed and distributes the Topologically Integrated

Geographic Encoding and Referencing (TIGER) System extract data sets as part

of the 2000 Decennial Census. These files serve as a geographic framework for

Census summary statistical and demographic data. The Massachusetts Executive

Office of Energy and Environmental Affairs has processed this data so that it is

consistent -- in the same data format and coordinate system -- with the existing

database kept by the Commonwealth's Office of Geographic and Environmental

Information (MassGIS). Through MassGIS, the Commonwealth has created a

comprehensive, statewide database of spatial information for environmental

planning and management. The Census Bureau also publishes tabular data files

("matrices"), which contain the demographic summaries produced in the Census,

and which are geographically linked to the TIGER files. MassGIS has extracted

and reprocessed data from the original TIGER and tabular data files for use in its

geographic information system. It was this reprocessed 1990 and 2000 Census

data that I used in my analysis of the Mystic River Watershed.

38

Defining Study Area

CSO outfalls must discharge directly into a surface water body, such as a

river or creek. This confines their location to areas in a given watershed where a

waterway like this is present. While my broader area of interest is the entire

Mystic River Watershed, I have chosen a narrower swath of block groups that

abut the river in order to compare areas affected by and not affected by CSOs.20

This may be thought of as the river corridor, which includes lands adjacent to and

including the river’s course.21 Using GIS, I was able to select the block groups

that lie within this river corridor zone. By using the Select-By-Location tool in

ArcMap, I identified the block groups that are within 200 feet of the river (see

Figure 6). This final study area consists of 63 block groups abutting Alewife

Brook, and the Mystic River and its main tributaries.22

20 Note that for this study area, I chose to exclude the uppermost reaches of the watershed, such as the Aberjona River, in favor of the contiguous section of the watershed surrounding the Mystic River corridor. This resulted in the exclusion of the municipalities of Reading, Winchester and Woburn, which are, generally speaking, higher income and lower minority than the lower sections of the watershed. There are no CSOs found in the uppermost reaches of the watershed. Thus, my choice of a study area was conservative. Had it been extended to the uppermost reaches of the watershed, it would have demonstrated an even greater disparity in community demographics. 21 This geographic delineation is consistent with other technical studies of the Mystic River Basin, such as Breault, Durant, and Robbat (2005).

22 These 63 block groups are based on the delineations in the 2000 Census; for the analysis of the 1990 Census data, the same study area consisted of 113 block groups.

39

Figure 6. Mystic River corridor study area block groups.

Selecting the CSO Zone of Impact

In an attempt to select the most appropriate zone of influence for my

analysis of the areas critically affected by CSOs, I surveyed the technical

engineering literature and explored how CSO discharges are treated from a

regulatory perspective. Unfortunately, there is a paucity of literature on the zone

of influence of combined sewer overflows, either technically or regulatorily.

The zone of influence of a pollutant discharge is primarily determined

through its mixing zone. According to EPA’s Technical Support Document for

Water Quality-based Toxics Control, “a mixing zone is an area where an effluent

discharge undergoes initial dilution and is extended to cover the secondary mixing

40

in the ambient waterbody. A mixing zone is an allocated impact zone where water

quality criteria can be exceeded as long as acutely toxic conditions are prevented”

(U.S. EPA, 1991, p.xx). In other words, in an engineering sense a mixing zone is

the zone in which the discharge initially mixes with the receiving water, and thus

is the region in which the initial dilution of a discharge occurs. In a regulatory

sense, it is the area where brief exceedances of water quality criteria are

permitted, so long as acutely toxic conditions are prevented. Water quality criteria

apply at the boundary of the (regulatory) mixing zone, not within the mixing zone

itself.

Surprisingly, there are no regulatory mixing zones for CSOs in the

MWRA area (Rex, 2007). In fact, although the Massachusetts Department of

Environmental Protection (DEP) does have a policy on the use of mixing zones, it

has not attempted to define a mixing zone for CSOs or to allow permittees to do

so. Rather, the mixing zone policy is typically limited to the discharge of wastes

that have received treatment and are subject to pollutant concentration limitations

(Brander, 2007). Indeed, EPA does not address mixing zones in its CSO

regulations. Although permitting CSOs through the NPDES program, EPA does

not define CSO mixing or impact zones. Instead, it recognizes “the site-specific

nature of CSOs and their impacts” and provides “the necessary flexibility to tailor

controls to local situations” (U.S. EPA, 1994, p. 18,688).23

23 The EPA has determined “inner zones” -- zones of plausible exposure -- for its Hazard Ranking System (HRS) for Superfund National Priority List (NPL) sites (U.S. EPA, 1989). Here, the four-mile perimeter is deemed the zone of plausible exposure for surface water. Although the volume and type of toxins present in CSO discharges may not be the same as in NPL sites, this buffer may at least describe the outer range at which impacts can be significant.

41

Unfortunately, the engineering literature does not provide much more

guidance. CSO mixing zones become dependent on such factors as baseflow

conditions, tidal influence, and the varying nature of the duration, pollutant load,

and volume of CSO discharges -- to name but a few (Marr and Freedman, 1997).

Other pollutant sources impact the water quality as well. This further complicates

the establishment of a CSO mixing zone (Brander, 2007). Furthermore, CSO

impact zones vary depending on the pollutant or pollutants of concern. CSOs

contribute a variety of pollutant loads to receiving waters and have various effects

on water quality, including elevated bacterial counts, decreased dissolved oxygen,

nutrient enrichment, sediment deposition, and toxicity problems -- each of which

will vary somewhat in terms of its zone of impact on receiving waters (Marr and

Freedman, 1997). For instance, Seidl et al. (1998) found that sedimentation of

suspended solids occurred during the first hours of transit of a CSO discharge and

by a downstream distance of five kilometers from the outfall. Other pollutant

loads, however, may travel farther and last much longer. For instance, the

parasitic protozoan Cryptosprodium parvum oocysts and Giardia intestinalis cysts

have been shown to survive for several months in feces and water (Medema and

Schijven, 2001; DeReignier et al., 1989; Medema et al., 1997).

When considering downstream areas affected by CSOs, it is also

important to look at what types of waterway uses one is concerned with, as this

will affect the defined zone of impact. As detailed earlier in this report, there are

numerous public health concerns posed by CSOs when direct contact is made

with contaminated water. These public health impacts appear to be better defined

42

and more readily understood than some of the less tangible effects of CSOs, such

as aesthetic impacts or insults to an adjacent community’s dignity. For instance,

Bartlett (1981) notes that for watercourses receiving CSO discharges to be used as

a potable water source, at least eight kilometers of river should normally be

allowed in order for the river to self-purify through natural mixing. While less

stringent standards exist for recreational waters than for drinking water,

conservative considerations must also be made for such recreational uses as

swimming, boating, or other activities that involve direct contact with the water.

In the first large-scale epidemiological study in the U.S. to investigate negative

health impacts associated with swimming in ocean waters affected by stormwater

discharges that were previously found to contain human fecal waste, the incidence

of illness was significantly greater (from 44 percent to 127 percent increased

incidence) for those who swam directly off the outfalls, compared with those who

swam 400 yards away (SMBRP, 1996). This study found that disease incidence

dropped significantly with distance from the storm drain and that at 400 yards and

beyond elevated disease risks were not found (SMBRP, 1996). It should be noted

that indicator bacteria in this particular study were on the order of E. coli >320

cfu/100mL (SMBRP, 1996), whereas the levels of indicator bacteria in CSOs can

be as high as 106 E. coli cfu/100mL, many orders of magnitude greater (Marsalek

and Rochfort, 2004). Therefore, it may be inferred that this zone of 400 yards

(0.22 miles) away from an outfall is likely to be inadequate in protecting

swimmers from disease risks posed by discharge from CSOs.

43

Additionally, while Alewife Brook and the Upper Mystic River are fresh

water areas, the Lower Mystic River and Chelsea Creek are influenced by the

tides from Boston Harbor and so are saline. Research has shown that this may

extend their CSO mixing zones. Hruby (1991) explains that, because coastal

CSOs discharge freshwater into salt water, the density difference between the two

may result in the formation of a lens of effluent that does not mix immediately

with the receiving waters. Measurements of dispersion in actual plumes have

shown that these density differences may significantly enlarge the mixing zone

(Hruby, 1991). In one study of CSO discharges in Jamaica Bay, New York, for

instance, plumes of effluent were still measurable more than one mile from the

discharge point (Cataldo et al., 1987). In another study that modeled conditions

for a two-week storm, results indicated that the plume would extend for over two

kilometers before 100:1 dilution was achieved (Hruby, 1991). Based on studies

he conducted, as well as review of studies in the literature, Hruby (1991)

concluded that the concept of the mixing zone for regulatory purposes may not be

very useful for CSO discharges into coastal areas, because important resources

will almost always be within the zone in which water quality standards are not

met. As a result, Hruby believes that the basic regulatory conclusion should be

that no CSO discharges are to be permitted.

The studies of the water quality impacts from CSOs in the Mystic River

Watershed have been quite limited to date. MWRA collects data as part of its

ongoing combined sewer overflow receiving water monitoring program. In the

latest such report on these data, MWRA reports that wet weather continues to

44

adversely affect all locations in the Mystic River and Alewife Brook, with the

highest bacteria counts occurring after heavy rain (Coughlin, 2007a). However,

despite the fact that “the goal of this monitoring is to identify the water quality

impacts of CSO flows on water bodies” (Coughlin, 2007a, p.1), this monitoring

appears inadequate to meet such goals. Upon consultation with MWRA about the

sampling and monitoring work it has done in the Mystic watershed, an agency

representative indicated that its monitoring is too crude to identify the true zone of

influence from CSOs in the watershed (Coughlin, 2007b). This is due to limited

sampling sites, the variability in water quality conditions from other pollution

sources, and the fact that its monitoring is not designed as a transect, radiating out

from outfall pipes (Coughlin, 2007b). MWRA’s monitoring instead aims to get a

snapshot of general water quality conditions of the entire water body (in wet vs.

dry weather), and to sample at hotspot outfalls that it knows are particularly

contaminated (Coughlin, 2007b). For these reasons, unfortunately, it is not

possible to define a precise CSO mixing zone in the Mystic River Watershed at

this time.

As explored previously, in addition to the serious public and aquatic health

risks that CSO discharges pose, CSOs can also cause significant impairment of

aesthetics in the receiving waters (Marr and Freedman, 1997). CSOs carry a

mixture of debris from stormwater runoff and wastes from sanitary sewage, as

well as conveying the noxious odors of sewage to the vicinity of the receiving

waters. All of these effects result in significant impairment of the aesthetic

quality of receiving waters. These aesthetic reductions can impose substantial

45

burdens on communities and tend to be the most localized impacts of CSOs,

having more of an acute affect on the areas immediately adjacent to outfalls.

Lacking a discretely defined near-field mixing zone, for the purposes of

my study I use a zone of influence of 0.25 miles out from CSO outfalls, where

impacts in the immediate area are likely to be the most significant. This zone is

arguably conservative and focuses on the immediate zone of impacts from

discharges, where water quality standards are not met at the point of discharge

during CSO activation and where aesthetic reductions are likely to be most

significant.

Use of Impact Buffer Zones

In order to demarcate the affected areas, a 0.25-mile circular buffer zone

was overlaid on all active CSO points in the study area (see Figure 7). These

buffers were used to select all block groups that intersected the buffers by

utilizing the “Select by Location” function within ArcMap. Where necessary, I

manually corrected for block groups that were selected in the upstream section of

these buffers. I deselected those upstream areas that were likely to be outside the

range of impact from the effluent discharges so that these block group portions

would not be counted with the obviously affected downstream areas (see Figure

8). It should be noted that this required some subjective judgment on river flow

impacts and so could introduce some degree of error into the study.24

24 Subsequent studies might employ a more advanced geographic plume analysis model, taking into consideration the hydrologic and hydraulic conditions of the river, in order to more accurately

46

Figure 7. Active CSOs with 0.25 mile circular buffers.

model the trajectory of the discharged effluent. This has been done extensively for air pollution and to a lesser extent with water pollution. One such tool designed for water modeling, CORMIX, is a U.S. EPA-supported mixing zone model and decision support system for environmental impact assessment of regulatory mixing zones resulting from continuous point source discharges (Cormix, 2007). The system emphasizes the role of boundary interaction to predict steady-state mixing behavior and plume geometry (Cormix, 2007). Recently, the engineering and consulting firm Symbiont was retained by the city of Rock Island, Illinois, to perform a water quality modeling study of a CSO outfall mixing zone on the Mississippi River (ESRI, 2007). As part of the overall project, a dye study was planned using GIS and GPS at one of the city's CSO outfalls to characterize CSO discharges and to evaluate plume mixing and dispersion under select river flow conditions. A fluorescent dye was utilized to determine how quickly a wastewater stream mixes with Mississippi River water. The tracer mimics the behavior of the discharged wastewater. Using various tools in ArcGIS, researchers were able to accurately illustrate the zones of dilution and create cross-sectional plume profile graphs. Based on the results of the dye study, the city was able to document that wastewater discharged to the receiving stream during a CSO event was dispersed and well mixed within 150 feet downstream from the outfall and that the maximum plume width was less than 50 feet from the outfall structure. These results helped determined long-term CSO control alternatives for the city's planning strategies (ESRI, 2007). Of course, mixing in the Mississippi River could be quite different from mixing in the Mystic River and, thus, a similar study would be needed in the Mystic to determine its own CSO mixing zone. However, this level of analysis is beyond the scope of this study.

47

Figure 8. Example of manual deselection of upstream block group within 0.25 mile circular buffer of active CSO.

Establishing Affected Areas

Once CSO buffers were applied, I then used two different methods to

establish the affected areas in order to examine the demographics of their

populations. First, I selected all of the block groups which were identified as

affected by the CSO buffer overlay (once manually corrected) and segregated

these into their own group. Similarly those block groups which were deemed

unaffected by the CSO buffer overlay were also segregated into their own group.

I then compared the demographic attribute data of these two groups of whole

48

block groups. I will refer to this as the “whole block group” method (see Figure

9).

Figure 9. Final selection of 2000 Census block groups affected (red) and unaffected (blue) by active CSOs (representing the “whole block group” method).

One obvious issue with this whole block group method, however, is that

because the buffer zone of impacts tends to be smaller than our unit of analysis,

here the block group, identifying whole block groups as affected by CSOs may be

too gross a measure of affected areas. While a block group may be identified as

impacted if even a small portion of it is found within the CSO buffer zone, the

majority of a given block group may, in fact, be unaffected by the effluent

discharges. Thus, the “whole block group” method is an imperfect measure of the

affected populations.

49

However, because we do not have gridded population data for Census

units, we cannot know what specific population is contained within any given

portion of a block group. And due to privacy concerns, the U.S. Census Bureau

does not collect detailed demographic data on populations at any unit finer than

the block group level. Thus, in order to be able to say with any confidence what

the demographic characteristics of a given area’s population are, we cannot

evaluate any area smaller than the block group level.

The estimation of small area populations and small area counts of other

socio-demographic and economic characteristics is a core problem in urban

research, where there is a frequent need to combine data aggregated to

incompatible sets of areal units (Reibel and Agrawal, 2005). By looking only at

demographic data within CSO impact buffers, we could get a more accurate

measure of CSO-affected areas. However, one drawback to this method is that

the underlying Census data units must be subdivided (clipped) to obtain the buffer

shape (Chakraborty and Armstrong, 1997) (see Figure 10).

50

Figure 10. Segregated block group portions (where pink represents CSO-affected (clipped) fractions of block groups).

When geographic units are only partially contained within the buffer, the

underlying Census data must be corrected for this areal modification. Whereas

there is no currently accepted data processing standard for combining data from

incompatible zone systems as a preliminary stage in urban research and analysis

(Reibel and Agrawal, 2005), one method commonly used to address this issue is

that of areal interpolation. Areal interpolation refers to the process of transferring

information from one set of boundaries to another (Goodchild and Lam, 1980;

Lam, 1983). As Goodchild et al. (1993) point out, the need for areal interpolation

is particularly relevant to water research, as the scale of water data, which is

51

typically gathered and distributed according to hydrologic study areas, is

incompatible with most socioeconomic data, which is gathered by civil divisions.

Thus, in order to analytically compare the data, some form of areal interpolation

often must be performed. This areal interpolation method is the second method I

used to examine areas affected by CSOs.

While there are a number of statistical methods for performing areal

interpolation (Goodchild et al., 1993), the simplest and most common method

used for computing populations within buffer zones is the areal weighting method

(Chakraborty and Armstrong, 1997). In this approach, the two sets of zones

(source and target zones) are intersected and the source zone counts are

fractionally assigned to their corresponding intersection zones as a function of the

proportion of the source zone’s area contained within the territory of the

intersection zone (Reibel and Agrawal, 2005) -- prorating based on overlapping

area. Here, the data held for a set of source zones s have to be allocated to a set of

target zones t. This is done by assuming that each source zone's data are

homogeneously distributed across their areas. Based on this assumption, the data

for each zone of intersection can be estimated for count or frequency data using

the formula:

where is the estimated value for the target zone, ys is the value for the source

zone, As is the area of the source zone, At is the area of the target zone, and Ast is

the area of the zone of intersection between the source and target zones

(Goodchild & Lam, 1980).

52

In the case of this study, the block groups are the source zones and the

0.25-mile circular buffers are the target zones. The intersection zones are then

reaggregated to the target zone geography, and each target zone’s associated

fractional source counts are summed to yield the estimated source variable counts

of the target zone units (Reibel and Agrawal, 2005). Essentially, by determining

what area fraction of the whole block group is contained within the buffer zone

around a CSO, we can then multiply that area fraction against the block group's

original population (or any other numeric demographic characteristic) in order to

estimate the numbers of people (or the associated demographic measure) within

the impacted zone. It is important to note, however, that this technique is based

on the assumption that population is distributed uniformly and heterogeneously

within each Census data unit (Chakraborty and Armstrong, 1997). This

assumption has been criticized as erroneous by some researchers who suggest that

allocating population based on the size of the geographic area is a viable solution

only when no other information is available about the actual distribution of

population within the areal unit (Reese-Cassal, 2007).25 Zimmerman (1994)

proposes that although this assumption might work with total population figures,

it is not likely to work well with subpopulations, which tend to cluster

geographically, and are not typically distributed homogenously. This assumption

thus introduces potential error into this method of estimating population and

25 Some researchers have attempted to overcome this limitation by employing a land use weighted areal interpolation methodology, whereby vector land use regulatory (zoning) data (or some other measure of land use) and U.S. Census data are used to derive land use weights via OLS regression or other algorithms (Reibel and Agrawal, 2005; Reese-Cassal, 2007). Based on the idea that land use data are a proxy for the distribution of population across the built environment, the derived weights are used to estimate interpolated population counts from the underlying census data unit.

53

demographic distribution across a given area. Despite this potential for error,

however, areal weighting is commonly used in environmental health research.

The areal weighting methodology is, in fact, the method employed by the U.S.

EPA in its own population estimation work for its Environmental Justice

Geographic Assessment Tool, which is the tool the agency uses to provide

information relevant to assessing adverse health or environmental impacts,

aggregate or cumulative impacts, unique exposure pathways, and vulnerable or

susceptible populations (U.S. EPA, 2007e). Therefore, despite the inherent

methodological limitations to areal weighting analysis, the use of this method in

studies informing policy and planning outcomes has strong precedent.

In this “areal weighting” method, I separated the whole block groups

identified with the buffer overlays into their aggregate parts (based on area inside

and outside of buffer zones). Then, based on this fractioning, I calculated the

proportional estimation of the population and accompanying demographic

characteristics contained within each area. The block group fractions outside of

the buffers were added to the whole block groups initially identified as entirely

outside of the buffers (and thus unaffected by CSOs). For example, in Figure 11

below, the block group fractions outside of the buffers, represented by the red

zones, are added to the whole block groups identified as entirely outside of the

buffers, which are represented by the blue zones. Thus, this new area represents

the total area deemed unaffected by CSO discharges, while the fractions of block

groups that are contained within the CSO buffers (the pink areas in Figure 11)

represent the CSO affected areas. The demographic characteristics of the

54

population within the aggregate area deemed unaffected by CSO discharges are

then compared to the demographic characteristics of the population within those

fractions of block groups that are contained within the CSO buffers in order to

quantitatively assess the differences between the groups.

Figure 11. Graphic representation of the “areal weighting” method. Examination of Closed CSOs and Temporal Studies

In examining the closed CSOs in the watershed, a number of analyses

were of interest. Of the eight CSOs that have been closed in the watershed, all

were closed between 1990 and 1996. Therefore, given that we have demographic

55

data for the region from both the 199026 and 2000 decennial Census, we are able

to compare the demographic characteristics of the region over time in a number of

different ways. First, it is interesting to look at general comparisons of the

demographic make up of the areas of concern between 1990 and 2000. As will be

presented in the Results section, I compared key demographic variables between

the time periods for the following subsets of my areas of interest, which I was

able to isolate using GIS: the entire Mystic River Watershed, the river corridor

study area, the block groups affected by the closed CSOs, and the block groups

not affected by the closed CSOs. The block groups that were affected vs. non-

affected by the closed CSOs were identified using the same methodology as with

the active CSOs, which is detailed above. Note, however, that for the analysis of

the affect of the closed CSOs, only the “whole block group” method was utilized

as opposed to also using the “areal weighting” method. This choice was made

based on the methodological limitations of this latter method, outlined above, as

well as to keep the analysis relatively simple.

Once the relevant block groups were isolated, their demographic

information was extracted for analysis. The demographic variables included total

population, percent minority, percentage growth in minority population 1990 -

2000, and median household income (adjusted to 1999 dollars27 to be consistent

with other data presented in this analysis). The reason for conducting this

26 The 1990 Census block group data was downloaded from MassGIS, which had processed Census data for use in GIS (available at http://www.mass.gov/mgis/cen1990_blockgroups.htm). Prior to analyzing these data, I removed duplicate data values existing in the original data set. The study area for the 1990 Census data consisted of 113 block groups abutting Alewife Brook, and the Mystic River and its main tributaries.

27 Dollar conversions were conducted using the U.S. Department of Labor’s Consumer Price Index Inflation Calculator (available at: http://www.bls.gov/cpi/).

56

analysis is to gain an understanding of the demographic changes in the region

during the time frame within which these CSOs were closed. Although the 10-

year time frame is likely to be short relative to observable demographic shifts, this

examination allows a longitudinal study of the watershed and the sub-areas of

interest to see what changes took place concurrent with the removal of certain

CSOs.

Another type of analysis that can be conducted with these data is to

examine demographic differences between those 1990 CSO-affected block groups

which had their CSOs closed and those 1990 CSO-affected block groups whose

CSOs remain active to date. By selecting out the different block groups with the

CSO buffers around both the closed and active CSOs, we can isolate these areas

for demographic analysis. This will tell us if there are significant demographic

differences between those 1990 CSO-affected block groups that had their CSO

burden relieved and those that did not. I intended this analysis to provide insight

into the question of whether the demographics of an affected community

influenced the decision of outside actors (e.g., state or local officials) in closing

these sewer outfalls and thus relieving the burden on the affected communities.

Therefore, I sought only to investigate those CSOs that were closed by outside

actors.28

28 Thus, I chose to exclude one CSO, CHE017, which was closed around 1990 by a disgruntled citizen of Chelsea in an act of civil disobedience. This citizen, whom I spoke to about his experience living and working in the vicinity of an active CSO, told me that he cemented the outfall shut only after years of unrequited complaints and requests to city officials. His responses will be further explored through the survey portion of my research. However, because this outfall was not closed by city or state officials but instead by illegal citizen action, I excluded it from those CSOs considered closed for this particular analysis.

57

I then isolated all 1990 block groups affected by the CSOs that would be

closed within the subsequent six years. I also isolated all 1990 block groups

affected by CSOs in the watershed that remain active today. At that point, I

extracted the demographic variables of interest from each group for analysis.29

These variables included total population, percent minority, and median

household income (adjusted to 1999 dollars). The findings from this analysis can

be found in the Results section of this paper.

Generating Demographic Data

In preparation for analysis, all of the tabular attribute data for the relevant

areas was exported out of ArcGIS and into Microsoft Excel. Although ArcGIS is

a superior software for working with spatial data, it is an inferior tool for

analyzing tabular data. Therefore, I used Excel to compare key attributes between

the segregated areas.

For my analysis of the active CSOs, using the 2000 Census data I

conducted comparisons between the areas identified as affected by CSOs and not

affected by CSOs for the block group sets identified by both the “whole block

group” method and the “areal weighting” method. The demographic data for the

entire watershed serve as a reference point against which all areas may be

compared. Data for each area were generated for the following attributes:

• total area (acres),

29 It should be noted that there was some overlap between these groups, given that there are areas where CSOs have been closed that are still affected by active CSOs. Thus, there is some duplication of population between these two groups.

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• total population, • total households, • total non-English speaking households, • percent non-English speaking households, • total number of minority (non-white) population, • percent minority (non-white) population, • total number of people without US citizenship, • percent of population without US citizenship, • average median household income by block group (not applicable for the

fractionally proportioned areas because median measurements cannot be fractionally interpolated with any meaning),

• total population below poverty level, and • percent population below poverty level.

These data can be found in the Results section of this thesis.

For my analysis of the closed CSOs, based on the demographic data that

was available from the 1990 Census files that had been processed for use with

GIS, which was much less detailed than with the 2000 Census, I was able to

compare the following demographics: total population, percent minority, and

average median household income (converted to 1999 dollars so as to be

comparable with the 2000 Census data). These comparisons can be found in the

Results section (chapter four).

As noted above, demographic variables were also compared between the

1990 block groups affected by the CSOs that would be closed within the

subsequent six years and the 1990 block groups affected by CSOs in the

watershed that remain active today. These variables included total population,

percent minority, and median household income (adjusted to 1999 dollars). The

findings from this analysis can also be found in the Results section (chapter four).

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Land Use Analysis

While CSO distribution by community demographic makeup is useful as

one type of equity analysis, as noted above it does not necessarily represent

exposure to residential populations, given that populations do not necessarily

reside within the portions of block groups that are affected by CSOs. Another

way to get at exposure is to examine the distribution of land use within the

specific portions of block groups that are affected by active CSOs. Of particular

importance and concern are residential land uses, as these are likely to mark the

zone of maximum human risk posed by CSOs. By overlaying land use

information on top of the CSO affected areas,30 we can calculate the various types

of land uses within each cluster of CSOs.31 Rather than examine each CSO

individually, I chose to evaluate clusters of CSOs where their impact zones were

overlapping, as this represented a more accurate area of impact (see Figure 12).

The resulting information, which will be explored in the Results section (chapter

four), is very useful in assessing the relative impacts of the CSOs on communities

within the watershed.

30 Specifically, this involved performing a union overlay between the MassGIS state land use layer and the active CSO clusters, which themselves had previously been intersected with the affected block group portions. These data were then exported into Microsoft Access for analysis through summary and crosstab queries.

31 Note that this analysis was performed only for those block group portions still affected by active CSOs in 2000 and not for areas in which CSOs had been closed. As can be seen in Figure 11, the areas here considered as affected by CSOs are only the portions of block groups falling inside of the CSO buffers, as opposed to whole block groups that are crossed by these buffers. Thus, the affected land use areas are calculated based on the area inside of CSO buffer zones, and their accuracy therefore depends on the accuracy of the chosen CSO buffers.

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Figure 12. Affected land areas (in pink) within impact zones of active CSO

clusters.

Siting Investigation

Once a disproportionate distribution of environmental burdens across

communities has been established, the next question is whether these

environmental burdens were intentionally and knowingly sited in these particular

communities or if subsequent factors account for the community demographics

that now surround these sites. A good deal of scholarship has focused on whether

environmental injustices are merely by-products of a market-based economy and

due more to differences in land and housing values -- thus (at least potentially)

constituting indirect discrimination, rather than more direct discriminatory animus

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(Been, 1994; Been, 1995; Hamilton, 1995). Researchers have performed

longitudinal studies of burdened areas over time to try to understand whether the

given environmental burden or the people in the surrounding neighborhood came

first (see, for instance, Been & Gupta, 1997; Oakes et al., 1996; Pastor et al.,

2001).

In the case of CSOs in the Mystic River Watershed, it is useful to examine

the history of siting in order to determine whether these CSOs were put in place

prior to or after neighborhoods formed in the region. Rough estimates of the CSO

infrastructure construction dates were determined by consultation with the

MWRA. Assessor parcel data were obtained for each of the municipalities

hosting CSOs and affected block groups in order to examine the year that each

parcel’s structure (be it a residential or commercial structure) was built for the

areas within the CSO buffers. Where possible, as with Boston, Somerville, and

Chelsea, GIS-compatible assessor data were overlaid on the mapped CSO impact

zones. For the cities of Arlington, Cambridge, Medford, Malden and Everett,

these data were not available in GIS-compatible form, but instead in an external

database. From the GIS maps, I determined which streets were within the CSO

impact zones and, for these streets, extracted the assessor data from the relevant

databases. From these data, I was able to determine the year that each parcel’s

structure was built, where that information was provided. The affected parcels

were analyzed in terms of whether their structures were built prior to or after the

CSOs were put in place in order to understand whether the CSOs were sited in

particular communities versus in areas undeveloped at the time of CSO

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construction. In cases where parcels were developed prior to CSO construction,

attention was further given to whether parcels hosted residential or non-residential

properties as an indicator of the type of settlements that likely existed at the time

of siting. Although it would also be informative to study changes in

neighborhood demographics in relation to siting of CSOs, this level of analysis

was outside the scope of this study.

Surveys

I also conducted a small survey of selective representatives from the

affected communities in the watershed to assess their perceptions of the problem

of combined sewer overflows. The survey respondents included a sampling of

individuals but especially drew from community activists and leaders of

community-based organizations active within the watershed. Most of the contacts

were identified as individuals with at least some knowledge of CSO issues.

Survey respondents included individuals from within community groups, city

government, and the private sector within the watershed. Although the survey

population represented a diversity of individuals in terms of community location,

educational training, and profession, the sample set was somewhat biased in that

all individuals were already familiar with the issue of CSOs. Nonetheless,

respondents provided valuable insight into the effects and perceptions of CSOs in

the community.

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I conducted surveys of individuals over email, supplemented with phone

discussions in the case of one individual wanting to respond via phone as well as

in writing. I initially contacted 23 people that I had identified. Survey

respondents identified an additional 13 people to survey. Of the 36 people

contacted with surveys, I received responses from 14 individuals. It should be

noted that as an anonymous survey, quotes will not be attributed to individuals.

The survey itself can be found in Appendix A. The results of these surveys will

serve as supplementary qualitative information to aid in interpreting the results of

my quantitative analyses.

Other Studies in the Literature

As noted previously, there is a paucity of literature examining water

pollution from an equity perspective. Sparser still is the literature involving CSOs

and equity. There were only two papers that I was able to find that dealt

specifically with CSOs from a social equity perspective. In framing my own

study and justifying its methodology, it is useful to take a critical look at these

two pieces of research.

As part of her master’s thesis at the Ohio State University, Rice (2005)

used GIS to examine environmental justice concerns related to sewer overflows --

both combined and sanitary overflows -- in Columbus, Ohio. Using data provided

by the City of Columbus, 20 CSO outfall locations and 44 SSO outfall locations

were mapped with 2000 Census data for race and median household income

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(1999) in Franklin County, Ohio, with analysis performed for the 883 Census

block groups in the county. While noting that CSO and SSO outfalls must

discharge directly into a water body such as a river or creek, which requires that

their locations be confined to areas in Franklin County where waterways are

present, Rice does not narrow her study area to reflect such areas but instead uses

the entire county as a frame of comparison. While a county-wide study area (or

watershed-wide in the case of my own research) is a useful frame of reference

against which to asses demographic trends of CSO exposure, I argue in my own

methodology that a more accurate study area would consist of only those block

groups that could host such an outfall. Thus, while analyzing demographic

information at the watershed level to serve as one point of reference, my own

study area includes a much smaller swath of block groups that make up the river

corridor, as it is only these block groups that can physically host such a sewer

outfall. Furthermore, Rice conducts exposure analysis for the actual block group

that contains the sewer overflow, and for all block groups that are within a 1000-

foot buffer of the overflow, but does not offer any justification for the choice of

this impact buffer zone other than the fact that “environmental and health risks

associated (with) CSOs and SSOs are most prevalent in areas…very close to the

actual sewer overflows outfall locations” (Rice, 2005, p.55). A stronger

justification of the choice of buffer zone would enhance the research effort. Rice

(2005) examines the block groups affected by sewer overflows by use of just two

demographic variables, percent non-white and average median household income.

Including additional variables would strengthen the analysis.

65

In what is more of a law and advocacy article than a social science study,

Neltner (2005) details the case of the neighborhoods along Fall Creek and White

River in Indianapolis, Indiana, downstream of Indianapolis’ combined sewer

overflows. The Fall Creek and White River neighborhoods consist of primarily

minority residents and are heavily affected by Indianapolis’ CSOs. In framing the

administrative complaint his organization would file with the EPA’s Office of

Civil Rights, Neltner (2005) highlights how the affected areas consist of more

than 85 percent African American residents -- 3.6 times higher than Marion

County’s average of 23.5 percent based on the 1990 Census.

While an invaluable article in terms of available advocacy options once a

disproportionate burden by CSOs has been proven, it does little to detail the

methodology used to establish such environmental inequity. More detailed

information, however, is available in the formal complaint letter that Neltner

submitted to then EPA Administrator Carol Browner. Here Neltner details that

the Census information was derived from Land View III Environmental Mapping

Software published by the United States Environmental Protection Agency; the

National Oceanic and Atmospheric Administration; and the United States

Department of Commerce, Economics and Statistics Administration, Bureau of

the Census (Neltner, 1999). Neltner compared the Census tract information from

the 1990 Census to maps of the streams and the locations of the combined sewer

overflows. For his unit of analysis, Neltner (1999) chose to use Census tracts,

noting that tracts typically extended 1/4 to 1/2 mile from the stream, which is the

rough distance that children in the neighborhood would walk to play in the

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stream. Thus Neltner chose an impact zone based on recreational access to the

river, as opposed to a residential or a plume-based measure. Neltner notes that

mileage was roughly calculated from available charts and rulers, thus introducing

some potential error in plotting. Use of more accurate mapping software, such as

GIS, would improve the accuracy of mapping and analysis. Additionally, use of a

smaller unit of analysis, such as the Census block group, would allow a finer

analytic investigation without compromising the level of demographic data

available to the study. Finally, while selecting a CSO buffer zone based on

estimated limits to recreational access by children is an interesting approach, it

would be useful to include additional information on how these measures were

estimated as well as to employ some zonal measure of CSOs’ physical impacts

downstream of outfalls. It would also be useful to include other impact vectors

and distances to affected populations (e.g., those based on smell, access to fishing,

boating, etc.).

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Chapter Four: Analytical Results and Findings

As explained in the Research Methodology, in order to examine the equity

of distribution of combined sewer overflows in the Mystic River Watershed, I

conducted a number of investigations of CSOs across spatial and temporal

distributions. First, I examined CSOs that are currently active in the watershed,

using 2000 Census data. This was done by comparing areas affected by CSOs

and not affected by CSOs, for area sets identified by both the “whole block

group” and the “areal weighting” methods. The demographic data for the entire

watershed serve as a reference point against which all areas may be compared to

give a broader regional benchmark. Data for each area were generated for the

following demographic attributes:

• total area (acres), • total population, • total households, • total non-English speaking households, • percent non-English speaking households, • total number of minority (non-white) population, • percent minority (non-white) population, • total number of people without US citizenship, • percent of population without US citizenship, • average median household income by block group (not applicable for the

fractionally proportioned areas because median measurements cannot be fractionally interpolated with any meaning),

• total population below poverty level, and • percent population below poverty level.

This demographic information can be found in Table 1 below.

Table 1. Demographic Comparisons between Block Groups Affected vs. Unaffected by Active CSOs*

Demographic Variables Entire Watershed Affected Block Groups

Unaffected Block Groups

Area Inside Buffers All Other Area

Total Area (acres) 62,702 3,995 4,313 1,082 7,226

Total Population 585,487 26,341 44,291 14,792 55,840 Total Households 235,287 11,388 18,663 6,349 23,702 Total Non-English Speaking Households 63,490 3,582 5,473 2,140 6,915 Percent Non-English Speaking Households 27.0 31.5 29.3 33.7 29.2 Total Number of Minority (Non-white) Population 129,394 9,272 11,451 5,755 14,968 Percent Minority (Non-white) Population 22.1 35.2 25.9 38.9 26.8 Total Number of People without US Citizenship 75,907 4,187 6,118 2,738 7,567 Percent of Population without US Citizenship 13.0 15.9 13.8 18.5 13.6 Average Median Household Income by Block Group (1999 $) 56,496 39,313 53,823 NA NA Total Population Below Poverty Level 54,496 4,912 4,512 3,055 6,369 Percent Population Below Poverty Level** 9.5 18.9 10.2 20.8 11.5

*Based on relationship to active CSOs using 2000 Census data.**Percent Population Below Poverty Level was calculated by normalizing the Total Population Below Poverty Level by the Total Population for Whom Poverty Status is Determined.

Whole Block Group Method Areal Weighting Method

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A summary of the quantitative comparisons can be seen in Table 2. It is

important to note that while in most cases absolute numbers (of individuals) for

the various demographic characteristics are higher for those areas deemed

unaffected by CSOs than for those areas deemed affected, this is not a

representative measure from which to draw trends. That is because the total area

and population of the unaffected block groups are significantly larger than for

those affected by CSOs. For instance, the total size of the areas unaffected by

CSOs is 318 acres larger in the case of the “whole block group” method, and

6,145 acres larger in the case of the “areal weighting” method. Similarly, total

population within these areas is also proportionate to the difference in acreage,

with unaffected areas hosting populations that are 17,950 larger in the case of the

“whole block group” method, and 41,049 larger in the case of the “areal

weighting” method.

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Table 2. Differences in Demographic Comparisons (Affected vs. Unaffected)*

Demographic Variables Whole Block Group Method Areal Weighting Method

Total Area (acres) 318 6,145 Total Population 17,950 41,049 Total Households 7,275 17,353 Total Non-English Speaking Households 1,891 4,774 Percent Non-English Speaking Households (2.1) (4.5) Total Number of Minority (Non-white) Population 2,179 9,213 Percent Minority (Non-white) Population (9.3) (12.1) Total Number of People without US Citizenship 1,931 4,829 Percent of Population without US Citizenship (2.1) (5.0) Average Median Household Income by Block Group (1999 $) 14,510 NATotal Population Below Poverty Level (400) 3,314

Percent Population Below Poverty Level** (8.7) (9.3)

*Based on relationship to active CSOs using 2000 Census data.**Percent Population Below Poverty Level was calculated by normalizing the Total Population Below Poverty Level by the Total Population for Whom Poverty Status is Determined.Note: differences are derived by subtracting affected block group values from non-affected block group values; thus, positive balancesrepresent higher values for non-affected block groups while negative values represent higher values for affected block groups.

Differences in Demographic Variables

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Because of the difference in size and population between the affected and

unnaffected areas, the most relevant data to examine are those that normalize each

absolute count by the total population sample within each composite area. For

instance, although the total minority population of block groups unaffected by

CSOs (11,451) is larger than that of affected block groups (9,272), the percent

minority of the affected block groups (35.2 percent) is larger than that of the

unaffected block groups (25.9 percent). Thus, the relative proportions (expressed

as percentages) for each demographic characteristic are more accurate measures

of the differential burden that CSOs have on communities within the watershed.

As can be seen in Table 2 above, the key findings in this regard can be

summarized as follows:

• Areas affected by CSOs have 9.3-12.1 percent higher minority populations

than unaffected areas (35.2-38.9 percent for CSO-affected areas vs. 25.9-

26.8 percent for unaffected areas)

• CSO-affected areas have populations that include 2.1-5.0 percent more

individuals who are not U.S. citizens than do unaffected areas (15.9-18.5

percent for CSO-affected areas vs. 13.8-13.6 percent for unaffected areas)

• In CSO-affected areas 2.1-4.5 percent more of the households are non-

English speaking than in unaffected areas (31.5-33.7 percent for CSO-

affected areas vs. 29.3-29.2 percent for unaffected areas)

• CSO-affected areas have average median household incomes that are 27

percent lower than the average median household income of unaffected

areas, ($39,313 vs. $53,823), a difference of about $14,500

• In CSO-affected areas, 8.7-9.3 percent more of the population is below the

poverty level than in unaffected areas (18.9-20.8 percent for CSO-affected

areas vs. 10.2-11.5 percent for unaffected areas).

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Thus, while there are some methodological limitations to this study, this

initial assessment suggests that currently active CSOs disproportionately affect

lower-income and higher-minority populations within the Mystic River

Watershed.

Although only a quantitative analysis as performed above can definitively

demonstrate a disproportionate impact of CSOs on lower-income and higher-

minority populations, it may also be instructive to inspect the distribution

visually. For a visual appreciation of the demographic trends in the watershed as

they relate to the location of active CSOs, we can map block groups according to

their distribution by percent minority and median household income. Such

distributions can be seen in Appendix B (Median Household Income by 2000

Census Block Group) and in Appendix C (Percent Minority by 2000 Census

Block Group). Additionally, we may inspect the distribution of CSOs as they

relate to EOEEA-designated Environmental Justice populations in the watershed,

which can be seen in Appendix D. This clearly shows the CSOs correlating

closely with these EJ communities, which are predominantly located in the lower

watershed.

Examination of Closed CSOs and Temporal Studies

A number of analyses were of interest in my examination of CSOs that

have been closed within the watershed. These included two principal studies. The

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first study looked at changes in demographic patterns in a number of subareas of

the watershed between 1990 and 2000, the period during which eight CSOs were

closed. The second study examined demographic differences between those 1990

CSO-affected block groups which had their CSOs closed and those 1990 CSO-

affected block groups which did not receive CSO relief, and thus still host active

CSOs to date.

Temporal Studies

Because all eight CSOs that have been closed in the watershed were

closed between 1990 and 1996, I could compare the demographic characteristics

of the region over time. The reason for conducting this analysis is to gain an

understanding of the demographic changes in the region during the time frame

within which these CSOs were closed. Although the 10-year time frame is likely

to be short relative to observable long-term demographic shifts, this examination

allows a longitudinal study of the watershed and the sub-areas of interest to see

what changes took place concurrent with the removal of certain CSOs.

In order to do this, I compared changes in key demographic variables

between 1990 and 2000 for the following subsets of my areas of interest: the

entire Mystic River Watershed, the river corridor study area, the block groups

affected by the closed CSOs, the block groups not affected by the closed CSOs,

and the block groups affected by active CSOs.32 The demographic variables

32 The block groups that were affected vs. non-affected by the closed CSOs were identified using the same methodology as with the active CSOs, which is detailed above. Note, however, that for the analysis of the affect of the closed CSOs, only the “whole block group” method was utilized as opposed to also using the “areal weighting” method. This choice was made based on the

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examined include total population, percent minority, percent change in minority

population between 1990 and 2000, and average median household income

(adjusted to 1999 dollars to be consistent with other data presented in this

analysis). The results of this analysis can be seen in Tables 3 and 4 below.

methodological limitations of this latter method, outlined above, as well as to keep the analysis relatively simple. Once the relevant block groups were isolated, their demographic information was extracted for analysis.

Table 3. Demographic Comparisons: 1990 and 2000 (Background Levels)

Demographic Variables

1990 2000Change

1990 - 2000 1990 2000Change

1990 - 2000

Total Population 563,618 585,487 21,869 68,746 70,632 1,886

Total Minority (Non-white) Population 61,853 129,394 67,541 10,266 20,723 10,457

Percent Minority 10.97% 22.11% 11.13% 14.93% 29.34% 14.41%Percent Change in Minority Population 1990-2000*** - - 109.20% - - 101.86%

Average Median Household Income (1999 dollars) $47,994.24 $56,496.43 $8,502.19 $35,066.61 $48,295.60 $13,228.99

***Derived from change in minority population between 1990 and 2000 divided by 1990 minority population.

Entire Watershed Study Area

Table 4. Demographic Comparisons: 1990 and 2000 (Target Block Groups)

Demographic Variables

1990 2000Change

1990 - 2000 1990 2000Change

1990 - 2000 1990 2000Change

1990 - 2000

Total Population 46,040 45,027 (1,013) 22,706 25,605 2,899 22,862 26,341 3,479

Total Minority (Non-white) Population 5,523 11,417 5,894 4,743 9,306 4,563 4,827 9,272 4,445

Percent Minority 12.00% 25.36% 13.36% 20.89% 36.34% 15.46% 21.11% 35.20% 14.09%Percent Change in Minority Population 1990-2000*** - - 106.72% - - 96.20% - - 92.09%

Average Median Household Income (1999 dollars) $34,773.72 $53,029.72 $18,256.00 $35,876.77 $38,117.25 $2,240.48 $30,964.76 $39,313.33 $8,348.57

*Based on relationship to CSOs closed 1990-2000.**Based on relationship to CSOs remaining active to date.***Derived from change in minority population between 1990 and 2000 divided by 1990 minority population.

Unaffected Block Groups* (Closed) Affected Block Groups** (Active)Affected Block Groups* (Closed)

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The above tables reveal a number of notable changes within the

demographic makeup of the watershed and its sub-areas. For example, at the

watershed level (see Table 3), between 1990 and 2000 there was an increase in

population by almost 22,000 people. Here there was a 109 percent increase in the

minority population, bringing the population to 129,394 in 2000 from 61,853 in

1990.33 This growth accounted for an 11 percent increase in the minority

population as a percentage of the total population. Additionally, at the watershed

level there was an 18 percent increase in the average median household income (a

growth of $8,502).34 Within the river corridor study area (see Table 3),

population increased by almost 2,000 people. Here there was a 102 percent

increase in the minority population, bringing the population to 20,723 in 2000

from 10,266 in 1990, which accounted for a 14 percent increase in the minority

population as a percentage of the total population.35 Additionally, the average

median household income increased by 38 percent (or $13,229) within the river

corridor study area. Within block groups unaffected by CSOs that closed between

1990 and 2000 (see Table 4), population decreased by roughly 1,000 people.

Here there was a 107 percent increase in the minority population, bringing the

population to 11,417 in 2000 from 5,523 in 1990, which accounted for a 13

percent increase in the minority population as a percentage of the total

population.36 Additionally, the average median household income increased by

33 The fact that the increase in minority population is greater than the increase in total population suggests substantial losses in the white (non-minority) population during this time frame.

34 As noted, all income figures are adjusted to 1999 dollars so as to be directly comparable to one another.

35 See footnote 32. 36 See footnote 32.

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53 percent (or $18,256) within these block groups unaffected by closed CSOs.

Finally, within block groups affected by CSOs that closed between 1990 and 2000

(see Table 4), population increased by almost 3,000 people. Here there was a 96

percent increase in the minority population, bringing the population to 9,306 in

2000 from 4,743 in 1990, which accounted for a 15 percent increase in the

minority population as a percentage of the total population.37 Additionally, the

average median household income increased by 6 percent (or $2,240) within these

block groups affected by closed CSOs.

It is particularly interesting to examine changes taking place within closed

CSO-affected block groups (that is, block groups that had been affected by CSOs

that were closed between 1990 and 2000). We see that the closed CSO-affected

block groups have experienced the largest change in the minority population as a

percentage of the total population, with a 15.46 percent increase in the percent

minority between the time periods.38 These closed CSO-affected block groups

also had the highest percent minority of the groups both in 1990 (20.89 percent)

and in 2000 (36.34 percent). These block groups, however, did not experience the

largest percent increase in the minority population; with a 96 percent increase in

the minority population between 1990 and 2000, their absolute growth in minority

population was only higher than that of the block groups that are affected by

active CSOs. This is likely due to the fact that these closed CSO-affected block

groups already had the highest percent minority population as a baseline in 1990

37 See footnote 32.

38 As will be subsequently discussed, it warrants noting that the increase in percent minority for the block groups that had been affected by CSOs that were closed between 1990 and 2000 is only slightly larger (at 15.46 percent) than for the block groups that are affected by active CSOs (at 14.09 percent).

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and gained a relatively smaller increase in total population during the ensuing

decade. These closed CSO-affected areas also experienced the smallest increase

(6 percent or $2,240) in average median household income, indicating that the

households in these areas received the smallest portion of the economic benefits

that accrued to the entire watershed. The latter, in the aggregate, experienced an

18 percent (or $8,502) increase in the average median household income between

1990 and 2000. Alternatively, as noted, the block groups that were unaffected by

these CSO closures experienced the biggest increase in income, with an aggregate

rise in average median household income of 53 percent (or $18,256). Although

these block groups experienced a smaller increase in the minority composition

(seeing a 13 percent increase in the minority population as a percentage of the

total population), they did, however, experience the second largest percentage

growth in absolute minority population (at 107 percent). This growth came while

experiencing a total population loss of 1,013. Thus, the minority population grew

considerably while the total population of this area declined.

When considering these findings, however, it is important to note that the

areas which are unaffected by closed CSOs contain a wide spectrum of block

groups, including those low-income, high-minority communities hosting CSOs

that are still active. They also include block groups in the upper watershed that

are unaffected by any CSOs and that have, in general, lower minority and higher

income populations. Thus, the areas that are unaffected by closed CSOs tend to

mirror general trends within the watershed and river corridor study area, and

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therefore may not be a useful measure against which to compare the changes in

the closed CSO-affected block groups.

In order to gain a sense of how these upper watershed groups might be

skewing the results, we can look explicitly at the demographic changes between

1990 and 2000 in the block groups that are affected by active CSOs (found in the

far right column of Table 4 above). Here we see that the block groups in the

watershed affected by active CSOs closely resemble trends shared by the block

groups affected by closed CSOs. We see, for instance, that the average median

household income in these block groups increased by $8,300, the second lowest

increase in income in absolute terms, only higher than those block groups that are

affected by closed CSOs. The changes in minority population as a percentage of

the total population within active CSO-affected block groups also closely

resemble those changes within closed CSO-affected block groups, experiencing a

14.09 percent increase from 21.11 percent in 1990 to 35.20 percent in 2000 for

active CSO-affected areas, as compared with a 15.46 percent increase from 20.89

percent in 1990 to 36.34 percent in 2000 for closed CSO-affected areas. In other

words, the data appear to show that the block groups in the upper watershed that

are unaffected by any CSOs and which have, in general, lower minority and

higher income populations, are skewing the results of the changes in the block

groups unaffected by closed CSOs. As a result, it is more useful to compare the

changes in the closed CSO-affected block groups with those in the active CSO-

affected block groups.

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What these findings likely indicate is that given only a few years in most

cases between CSO closure and the 2000 Census, there was not enough time to

account for the affects of CSO closure on the demographic makeup of

neighborhoods. This is especially true for those areas still containing other active

CSOs that were not closed, as these areas would not likely experience effects

associated with relief of CSOs. It is also important to remember that CSOs are

not the only issue that these neighborhoods face that may affect demographic

makeup and numerous other factors may be influencing observed demographic

patterns. Perhaps most instructive is to examine the 1990 to 2000 changes for the

areas affected by CSOs (both active and closed) as compared to the rest of the

watershed. These areas experienced the sharpest rise in minority population as a

percentage of the total population as well as the smallest growth in median

household income. While we would need to examine a number of other factors in

order to definitively understand the cause of this trend, we may posit a

relationship to depressed housing values in these areas, which may themselves be

related or unrelated to affects of the CSOs in their vicinity.

Furthermore, when interpreting these specific demographic trends, it is

instructive to look at geographically broader demographic trends during this time

period. It is important to note that the 1990 and 2000 demographic data are based

on the tabular data extracted from the Census by MassGIS and processed for use

in GIS. These data were then isolated into areas of interest within the watershed

for subsequent analysis. It is difficult to get easily comparable Census data for

these areas given that the watershed and its sub-areas do not represent political

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boundaries but instead are arbitrary aggregations that (for purposes of this study)

have been mapped onto hydrologic geographies. Nonetheless, we may compare

these figures with Census data for the cities and towns in the watershed as a

general proxy for demographic changes during this decade.

For instance, although a 109 percent increase in minority population in the

watershed may at first glance look surprisingly high, it appears more reasonable

when viewed in light of broader demographic trends in the Boston Metropolitan

Area during the 1990 to 2000 period. During this period a number of

smaller/high density cities in the greater Boston area -- including the Mystic River

Watershed cities of Cambridge, Chelsea, Everett, Malden and Somerville, as well

as the non-Mystic cities of Brockton, Lowell, Lynn, and Waltham -- experienced

very significant growth in minority populations. From 1990 to 2000, these cities

collectively lost 85,000 white residents, while experiencing very high minority

growth rates (see Table 5), thereby becoming the areas of the Boston

Metropolitan Area experiencing the greatest rates of racial change (McArdle,

2002). Of these areas, the Mystic River Watershed cities of Boston, Chelsea,

Everett, Somerville and Malden experienced especially high minority growth

rates (see Table 5) (McArdle, 2002).

City/Region

Black Population Latino Population Asian PopulationOther Central/High Density Cities* 63.10% 56.50% 87.20%Boston 10.50% 37.30% 58.30%Chelsea n/a 88.30% n/aEverett 161.00% 161.00% 163.80%Somerville 47.00% 41.80% 97.80%Malden 143.40% 193.80% 193.80%

*Includes Brockton, Cambridge, Chelsea, Everett, Lawrence, Lowell, Lynn, Malden, Somerville and Waltham.Data adapted from McArdle (2002).

Percent Change in Minority Population, 1990 - 2000Table 5. Percent Change in Minority Population for the Boston Metropolitan Area 1990 to 2000

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Thus, it is important to note that minority growth rates between 1990 and

2000 were particularly high for the areas throughout the Boston Metropolitan

Area, and were not confined only to those locales within the watershed and river

corridor study area. In fact, the block groups within the study area in many cases

grew more slowly than much of the surrounding urban areas in terms of

percentage growth in minority populations. Thus, it is far from clear that the

significant increases observed in minority populations within the CSO-affected

areas can be directly tied to the affects of CSOs without taking into account the

broader demographic shifts occurring during this time period, which themselves

may be caused by a host of factors.

Demographics of Closure Areas

An additional analysis may help in understanding the relationship between

CSO closure and community demographics. The object here is to examine

demographic differences between those 1990 CSO-affected block groups which

had their CSOs closed and those 1990 CSO-affected block groups whose CSOs

remain active to date. By selecting out the different block groups using the CSO

buffers around both the closed and active CSOs, we can isolate each of these

areas for demographic analysis. This may indicate whether significant

demographic differences exist between 1990 CSO-affected block groups that had

their CSO burden relieved, and those that did not.39 The demographics from the

39 As noted in the Research Methodology section, because I intended this analysis to provide insight into the question of whether the demographics of an affected community influenced the decision of outside actors (e.g., state or local officials) in closing these sewer outfalls and thus relieving the burden on the affected communities, I chose to exclude one closed CSO, CHE017,

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isolated block groups affected by the CSOs that would be closed and those that

remain active today are compared in Table 6 below.

Demographic Variables

Hosting CSOs that Closed* Hosting CSOs Remaining ActiveTotal Population 19,908 22,862 Percent Minority 14.89% 21.11%Average Median Household Income (1999 dollars) $35,710.17 $30,964.76

*Does not include CHE017, which was intentionally excluded from this analysis due to its irregular closure.

Table 6. Demographic Comparisons Between 1990 Block Groups Affected by Active vs Closed CSOs1990 Block Groups Affected by CSOs

What this analysis shows is that those 1990 block groups where CSOs

were not closed (and thus remain active to date):

• have a 6 percent higher minority population (21.11 percent compared with

14.89 percent), and

• have average median household incomes that are 13 percent lower than

those areas in the watershed where CSOs were closed, ($30,964.76 vs.

$35,710.17), a difference of about $4,700.

Thus, the areas where CSOs remained active within the watershed are higher

minority and lower income areas than those areas where CSOs were closed.

While these data do suggest a disproportionate allocation of closures correlating

with lower minority and higher income communities, it is important to note that

correlation does not necessarily indicate causality and a more detailed and

which was closed illegally by a citizen in an act of civil disobedience. Because CSO CHE017 was excluded from this analysis, the resulting block groups being considered as affected by closed CSOs for this analysis is a slightly smaller set than was considered above as affected by closed CSOs for the purposes of the temporal change study (see Table 4). Hence, the slightly different demographic data between these groups is intentional.

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nuanced analysis would be needed in order to fully understand the reasons behind

specific closures of CSOs.

Land Use Analysis

The analysis of the distribution of land use within the specific portions of

block groups that are affected by active CSOs yields some interesting results (see

Table 7). As noted in the Research Methodology section, these CSO-affected

areas are only the portions of block groups falling inside of the CSO buffers, as

opposed to whole block groups that are crossed by these buffers. Thus, the

affected land use areas are calculated based on the area inside of CSO buffer

zones, and their accuracy therefore depends on the accuracy of the chosen CSO

buffers. Again as noted, this analysis was performed only for those block group

portions still affected by active CSOs in 2000 and not for areas in which CSOs

had been closed. And rather than examine each CSO individually, I evaluated

clusters of CSOs where their impact zones were overlapping, as this represented a

more accurate area of impact.

Table 7. Acres of Land Use within Active CSO Buffers (Year 2000)CSO Cluster Name Commercial Industrial Open Land Participation Recreation Residential Transportation Urban Open Wetland

ALEWIFE 20.32 75.19 19.29 31.07 101.54 29.84 16.36 11.74BOS014 2.32 6.41 7.51 4.96 24.10 3.19BOS017 12.68 23.29 8.72 4.31 8.41 5.94BOS019 3.94 5.71 41.73 33.14CHELSEA CREEK TOP (CHE008) 21.18 26.00 3.52CHELSEA MAIN CLUSTER 59.65 7.11 33.79 79.99 33.54LOWER EAST BOSTON 0.20 8.74 12.45 156.68 3.54MIDRIVER BELOW MALDEN 39.13 10.59 16.84 23.99

Total 95.17 165.20 29.88 67.09 162.74 383.61 123.22 11.74

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In terms of residential land use within clusters of active CSOs, we see that

the area with the most residential land affected by CSOs is along Alewife Brook,

where 102 acres of residential land are affected. Another area with significant

residential acreage is denoted in Figure 13 as “Chelsea Main Cluster,” which

consists of areas along the mouth of Chelsea Creek and the lower stem of the

Mystic River. Here 34 acres of residential land are impacted by CSOs. These

areas of high residential land are likely to pose the most significant health risks to

the public as people are living within close proximity to the active CSOs. While

people may choose whether or not to voluntarily put themselves into contact with

the water in the river itself, if one’s basement or yard is flooded with water

containing raw sewage, one is involuntarily exposed.

Figure 13. Affected land areas (in pink) within impact zones of active CSO

clusters.

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Additionally of concern are areas of land designated as “participation

recreation”, which include golf courses, tennis courts, playgrounds, and the like

that could result in significant exposure to contaminants in the event of CSO

activations. The area along Alewife Brook has 31 acres of this type of land use,

along with another 35 acres of open land, both of which are likely to host

significant recreational activities that could expose people to CSOs. Alewife’s 12

acres of wetlands may also pose opportunities for land- or water-based recreation,

increasing exposure risk to humans. Other areas with significant recreational and

open land include the Chelsea Main Cluster (41 acres), the East Boston side of

Chelsea Creek around outfall BOS014 (11 acres), East Boston along the lower

Mystic River (12 acres), and in Somerville near outfall BOS017 (15 acres). Each

of these areas should be carefully considered for public health affects from CSO

events.

The most direct contact with CSO impacted waters may, however, occur

during water-based recreational activity, be it boating, fishing, or swimming. The

results of a survey of recreational uses of the Mystic River conducted by the

Mystic River Watershed Association (MyRWA) provide useful insight into this

issue. The survey revealed extensive boating on the Mystic River, including

motorboating, sailing, canoeing and kayaking (MyRWA, 2006). The survey also

found that fishing is widespread throughout the watershed, with at least some

fishermen and their families eating their catch (MyRWA, 2006). Additionally, it

was found that swimming is occurring in the Little Mystic Inlet (MyRWA, 2006),

which is impacted by CSO outfall BOS019. There are also anecdotal reports of

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swimming, especially by children, at other locations in the lower watershed --

including Chelsea Creek, the Blessing of the Bay Boathouse, the Chelsea Mystic

River shoreline, and under the Route 99 bridge (MyRWA, 2006). Swimming and

wading in these areas can pose serious public health hazards due to high bacteria

levels -- particularly those associated with rain events -- as well as other

contaminants such as metals and toxins.

Also of concern are areas with commercial land that are within the zones

of exposure of the active CSOs in the watershed. Most notably these include 60

acres of commercial land in Chelsea along the mouth of Chelsea Creek and the

lower stem of the Mystic River, 20 acres of land along Alewife Brook, and 13

acres in Somerville surrounding outfall BOS017. The proximity of CSO

activations to these commercial lands poses potential negative economic

consequences to these communities given that the CSOs may adversely impact

commercial business interests and activity in these regions. Negative effects are

associated with noxious smells and other aesthetic impairments, physical damage

to business infrastructure (such as docks, pilings, or shoreline), and public health

dangers, all posed by the CSO discharges. The CSOs may also interfere with

work along the waterfront by causing unpleasant and unsafe working conditions

in the areas where they discharge. As will be explored further in the survey

results, there are a number of business owners in Chelsea and East Boston who

reported being negatively affected by CSO discharges in the vicinity of their

commercial properties.

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Siting Investigation

In the case of CSOs in the Mystic River Watershed, it is useful to examine

the history of siting in order to determine whether these CSOs were put in place

prior to or after neighborhoods were developed in the region. Rough estimates of

the CSO infrastructure construction dates were determined by consultation with

the MWRA. While advising that it would take weeks of research to determine

when the existing outfalls were first put into service -- if the information existed

at all -- an expert at the MWRA did state that most of Boston’s CSO outfalls were

constructed in the 1870s, although they were preceded by wastewater/stormwater

conduits built dozens of years earlier (Kubiak, 2007). Thus, given that exact

construction dates for each outfall were not available, I choose as the ‘siting’ date

of outfalls a conservative estimate of 1900, and compared this to the actual dates

of nearby residential construction.40

As noted, where possible, as with Boston, Somerville, and Chelsea, GIS-

compatible assessor data were overlaid on the mapped CSO impact zones. For

the cities of Arlington, Cambridge, Medford, Malden and Everett, these data were

not available in GIS-compatible form, but instead in an external database. From

the GIS maps, I determined which streets were within the CSO impact zones and,

for these streets, extracted the assessor data from the relevant databases. From

40 Another reason why it is difficult to assess historical equity issues with regards to CSO siting, is that, historically, provision of sewerage services was beneficial to communities, and, thus, largely desired. Many CSOs were replacing (or upgrading) even older outfalls that were the only means of disposal of wastewater and stormwater, prior to regional sewer systems and treatment. Thus, CSO siting may have been perceived as beneficial and desirable -- by those doing the siting as well as by the receiving communities -- at the time of CSO construction.

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these data, I was able to determine the year that each parcel’s structure was built,

where that information was provided.

The affected parcels were analyzed in terms of whether their structures

were built prior to or after the CSOs were put in place in order to understand

whether the CSOs were sited in particular communities versus in areas

undeveloped at the time of CSO construction. In cases where parcels were

developed prior to CSO construction, attention was further given to whether

parcels hosted residential or non-residential properties as an indicator of the type

of settlements that likely existed at the time of siting.

In the subsequent analysis it is important to note that I was examining only

parcels within the actual CSO buffer zones, and thus identification of CSO-

affected parcels is only as accurate as the chosen CSO impact zone. The accuracy

of this analysis also depends on the reliability of assessment data, including the

year initial construction occurred. Given that no exact dates were available for

outfalls and that a conservative date was instead chosen for comparison, the best

that this analysis can provide is a rough sense of whether further investigation is

warranted.

Based on assessment data from the City of Somerville, very few parcels

were built prior to 1900, with no clearly established neighborhoods dating to

before this time. While there are sections abutting the river for which no year-

built data was available, it is clear that the majority of parcels were built between

1910 and 1930, well after the CSOs were constructed.

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Based on available information, it appears that the parcels in CSO-affected

areas in Medford were built subsequent to CSO siting -- with the majority of

parcels being built after 1910. Many of the parcels in Everett and Malden were

built around 1900, with some built in the late 1800s, thus warranting further

investigation.

Most of the parcels in Arlington that are within the vicinity of CSO impact

zones were also built well after the CSOs were constructed (with an average year

built of around 1940). There is one area along Alewife Brook containing 4 CSOs

(SOM001, SOM001A, CAM001, CAM401B) where the adjacent parcels were

built between 1880-1900. This sub-area warrants closer investigation to

determine whether these parcels were developed prior to CSO siting.

Although most of the parcels in Cambridge that are within the vicinity of

CSO impact zones were built well after the CSOs were constructed, there are a

few streets with houses built in the late 1800s that may have been developed prior

to CSO siting. This area (surrounding outfalls CAM400, CAM002, CAM401B,

CAM001) is on the Cambridge side of Alewife Brook, across from the section of

Arlington that is also affected by these outfalls and which may also have been

developed prior to CSO siting. Given that the areas on both sides of Alewife

Brook are affected by these CSOs and were both developed in the late 1800s,

further investigation of these areas should occur to determine how their

development relates to the siting of CSOs.

There are a number of areas in Chelsea (those areas impacted by CSO

outfalls CHE002, CHE003 and CHE004) where parcel development dates to the

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late 1800s and early 1900s. In these areas, as of today roughly 80 percent of the

parcels are residential properties. Although we can determine whether CSO

impacted parcels are currently zoned for residential or commercial uses, another

limitation to this study is that it is difficult to determine how zoning changed

between the time of parcel development and now. For instance, we cannot say

with any certainty that properties with commercial uses now were commercial at

the time of construction. These properties may have originally been residential

and subsequently converted to commercial use. More detailed analysis involving

the zoning at the time of parcel development would be needed in order to

determine whether these areas were residential at the time of CSO construction.

The results for Boston are equally inconclusive. While there are a large

number of riparian areas in Charlestown where parcels were developed around the

late 1800s and early 1900s, these parcels are almost exclusively zoned as

commercial as opposed to residential properties. Again, while this does offer up

the possibility that the CSOs were constructed in commercial as opposed to

residential areas, more detailed analysis is required to confirm whether, and the

extent to which, this is the case.

When examining parcels in East Boston, we find substantial parcels of

both residential and commercial property that were built between the 1880s and

early 1900s. Visually estimating the composition of East Boston parcels within

the CSO impact zones, the impacted areas appear to be composed of

approximately 60 percent commercial to 40 percent residential parcels (again

noting uncertainties in historical zoning). While this type of analysis is useful for

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drawing general conclusions, a more accurate analysis would need to determine

the date of origin of each CSO by reviewing construction records, and confirm the

accuracy of the year-built information from the assessors’ data.

Thus, it is difficult to conclude with any certainty whether or not CSOs

were sited in pre-existing residential developments. There are a number of areas

within Boston, Chelsea, Arlington and Cambridge where this is at least a

significant possibility. Subsequent analysis would require obtaining exact

construction dates for each sewer outfall, a more detailed zoning history of

affected parcels indicating what type of building use existed at the time of initial

construction, and -- importantly -- information on the demographics of the

residents occupying those structures.

Surveys

As noted in the Research Methodology, I conducted surveys of individuals

over email, supplemented with phone discussions in one case. I selected most of

the survey contacts based on my knowledge about the watershed, identifying

individuals active with at least some knowledge of CSO issues. Additional

contacts were identified by initial survey respondents. Of the 36 people surveyed,

I received responses from 14 individuals. The survey respondents

included individuals from within community groups, city government, and the

private sector, but especially drew from community activists and leaders of

community-based organizations active within the watershed. The survey itself

can be found in Appendix A. As an anonymous survey, quotes will not be

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attributed to individuals. The results of these surveys will serve as supplementary

qualitative information to aid in interpreting the results of my quantitative

analyses.

Community members overwhelmingly expressed serious concern about

the CSOs in their cities and towns. In fact, 12 out of 14 respondents were “very

concerned” by the CSOs in the watershed, while the additional two were

“somewhat concerned.” Twelve of 14 respondents reported noticing negative

effects of the CSOs in their own communities. The concerns primarily centered

on public health impacts, nuisance effects, reduced recreational opportunities and

property damage caused by the CSOs. There was much concern about direct

health impacts that people might incur from coming into contact with raw sewage

and the associated bacteria contamination -- whether it be in their backyards or in

the river itself. One resident who lived within flooding proximity to the CSOs

was particularly concerned that the discharges into his yard and home would

make him sick. He was also concerned by the effects CSOs had on lowering

property values. This resident had, in fact, conducted a study of property values

in Arlington and found that parcels abutting Alewife Brook experienced

comparatively lower sales values.41 Also frequently noted were the unpleasant

aesthetic effects from the CSOs, including foul and noxious odors, floating debris,

solids, and trash, such as toilet paper, condoms, and sanitary pads in the water.

Twelve of 14 respondents reported directly observing such effects while an

41 The study entailed plotting sales price vs. assessed value and putting the information on a map, whereby gains and losses were mapped by a color scheme. The study found that most of the losses were grouped around Alewife Brook. While these trends in housing values might be attributable to proximity to the Brook, further study would be needed to determine the extent to which this was the causative factor.

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additional 2 people reported hearing about these effects within their communities.

Additional concerns related to the negative effects CSOs had on natural

ecosystems within the river -- harming the plant community, decreasing dissolved

oxygen, and spreading toxic chemicals to sediments, fish, birds and benthic

invertebrates.

Perhaps the most frequently noted concerns involved the effects that CSOs

had in reducing recreational opportunities along the river. Eight respondents

explicitly noted that CSOs were preventing, interfering with, or inhibiting

recreational opportunities along the river, although 10 people subsequently

indicated that they would take advantage of additional recreational opportunities

if the CSOs were cleaned up. It was noted that the CSO discharges impaired use

of the river and its surrounding lands for activities like walking, running, biking,

kayaking, canoeing, fishing and jet skiing. Most respondents felt that CSOs

prevent people from using and experiencing the Mystic in a healthy way. One

resident stated that CSOs “prevent large numbers of people who live nearby from

enjoying a vital natural resource in their backyard that could be a very useful

recreational and educational resource.” That individual went on to express

distress that “people are not concerned with their own river and streams because

they are degraded by CSOs” and that CSOs are therefore “creating a continuing

cycle of neglect and degradation.” Another respondent noted:

the knowledge that raw sewage can sometimes discharge directly into the stream causes us -- rightly so -- to be afraid of the water and of making contact with it. The river begins to be considered as a conduit for pollution and waste and people begin to write it off in their minds as hopeless. Because of this, the river has become disassociated from our lives -- it's fenced up in many

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places, or piped underground and out of sight, or barricaded with riprap. This certainly has negative effect on wildlife habitat and biodiversity, and I think it does something negative psychologically to us, as well.

A related concern was that the public is not adequately, consistently, or

effectively notified in any meaningful way about the dangers of CSOs and the

timing of activations. Municipalities in the watershed are also inconsistent with

how they notify citizens. It was felt that people need to know right away about a

CSO event, so that they can make educated decisions about the types of exposure

they are comfortable with.

In some areas of the watershed, particularly in Chelsea and East Boston,

where access to Chelsea Creek is extremely limited, some citizens felt that while

CSOs were quite alarming and interfered with recreational use of the river, their

impact on the community was not as evident, given that there is so little access to

the river in the first place. Three community activists in Chelsea felt that the

general population in their city did not even know that the CSOs exist, due to a

combination of severely limited access to the waterfront and the greater salience

of stationary sources of industrial air and water pollution along the Creek (such as

oil companies, heavy industry, and a huge salt pile). This is a very interesting

finding, suggesting that, while CSOs are an important issue, they may be dwarfed

by more pressing concerns (such as lack of access to the waterfront entirely) in

some areas of the lower Mystic, or that the public has not been adequately

educated about the threats they pose. However, it was also pointed out that,

despite the many obstacles, people -- and especially children -- can and will get to

the river. One respondent put it:

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Despite all the attempts to hide the river away from us city dwellers, people can and will access the river. It’s pretty tough to keep kids out of a river. The health risk associated with this is therefore very real and needs to be addressed.

Not surprisingly, when asked what they would like done about CSOs in

their community, respondents nearly unanimously wanted to see the CSOs

eliminated and cleaned up. Eleven of the 14 respondents wanted the CSOs

eliminated (of which 5 wanted discharges to be cleaned and treated at the very

least).42 Some, with more technical expertise, specified that at the very least the

CSOs should get treated with UV or chlorine to kill bacteria and viruses and to

have the floatables separated and collected. Three respondents also explicitly

indicated a desire to see public funds dedicated to the proper infrastructure work

in the watershed. One respondent also wanted to see a massive public awareness

campaign about the problem, including signs and educational material posted and

made available to inform nearby residents of the public health hazards.

Additionally, it was suggested that when CSOs are activated, there should be a

brief notice in the local newspaper or report on the evening news to let the public

know.

When asked in what additional ways, if any, they would use the river if the

CSOs that affected their neighborhood were cleaned up or removed, the majority

of respondents (10 of 14) focused on taking advantage of renewed recreational

42 Two people marked this question as “not applicable” because their particular community did not host active CSOs. One respondent indicated that he was unsure of what the options were for dealing with the CSOs.

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opportunities on the river.43 People wanted to see more access for all types of

recreation, including riverside walking, running, and biking, and in-river

kayaking, canoeing, and, ideally, fishing and swimming. Given the central goal

of the Clean Water Act is to restore water bodies to fishable and swimmable

standards (Vigil, 2003), it is only fitting that watershed residents express a similar

desire. Both of the two affected business owners who were surveyed noted that

CSO removal would greatly improve their operations -- by reducing noxious

odors, reducing erosion to their property caused by flowing discharges, decreasing

required maintenance, and making it easier to load and unload cargo along the

riverfront.

In terms of residents’ perceptions of fairness in the distribution of CSOs,

10 of 14 respondents believed there to be inequity in distribution. Three

respondents did not believe there to be unfairness in CSO distribution, and one,

having no active CSOs in her community, marked this question as “not

applicable.” Of those respondents noting no unfairness in CSO distribution, one

believed (erroneously) that CSOs could be found all across the Mystic River

waterfront and, thus, that the burden was distributed equally across communities.

Some believed it particularly unfair that most CSOs on the Mystic River are in

areas of lower income and minority communities and that due to CSO flows these

already disadvantaged residents cannot use a water resource that is within walking

distance. One respondent noted the irony that Arlington’s only EOEEA-

43 Two respondents marked this question as “not applicable” because their particular community did not host active CSOs. Another individual noted that there would need to be more cleanup of other sources of water pollution to the river beyond just CSOs before appreciable changes in river use could be experienced.

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designated environmental justice area bears the brunt of the CSO discharges in

that town. That individual also pointed out that properties near Alewife Brook

consistently have lower assessed values than other equivalent homes in Arlington

-- presumably due to CSO activity that floods homes with raw sewage. Another

source of inequity cited is that those homeowners abutting the brook are also

forced to spend money to maintain sanitary conditions on their property after

flood events. The two business owners with CSOs on their properties also cited

the unfair burden of property damage and increased maintenance costs caused by

CSO discharges.

A few respondents also raised questions about transboundary inequities.

For instance, it was noted that on the Alewife Brook, it is unfair that Arlington

should be burdened with CSO overflows from Somerville. One respondent called

attention to the fact that many CSOs were removed from the Charles River in

Cambridge (a wealthier area) but still exist on Cambridge’s section of Alewife

Brook and so questioned why Cambridge allotted its infrastructure funding to

prioritize CSO removal on the Charles River rather than Alewife Brook.

Interestingly, one community member in Chelsea felt that the unfairness is

not so much in CSO location as in how revenues are allocated in eliminating

them.44 This raises critical questions about preferential spending of public

44 This respondent explained: “The MWRA is further funding projects that were not originally included in the court-approved CSO plan. The two projects most recently approved are the $9.7M Brookline Sewer Separation and the $4.7M Bulfinch Triangle Sewer Separation (area around the BankNorth Garden in Boston), which were recommended by the MWRA in 2005. Other projects such as the $227M North Dorchester Bay, $80M East Boston Sewer Relief, and $57M Cambridge CAM002-004 Sewer Separation project have been approved for cost increases. The MWRA has a program for Inflow and Infiltration Removal. It has been funded at $86.594M in six phases. Out of the $86.594M funding, $86.507M has been distributed in grants and zero-interest loans to member communities based upon the communities’ share of sewer flow. No further phases are funded at

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resources that should be explored further in future research. Additionally, as one

respondent noted, although CSOs are concentrated in poorer, more urban areas, it

is unclear whether this is simply because CSOs exist where municipal

infrastructure is older, or whether it reveals intentional discriminatory siting. This

underscores the importance of conducting rigorous, analytic studies of CSO

distribution and history -- both in terms of placement and remediation.

I surveyed two business owners whose properties include active CSOs

along the Chelsea Creek waterfront. The first, who is based in Chelsea, claims

that years of ineffectual complaining to a number of city officials drove him to

take direct illegal action in cementing closed the outfall to stop it from flowing

into the Creek. He noted that, before being closed, effluent from this pipe was

constantly flowing into the Creek, a problem that intensified after rain events.

Some of the negative effects the business owner noted included extreme foul

odor, the discharge of debris and solids, substantial damage to business property,

and the killing of clams, mussels and fish in the Creek. However, of the many

serious effects noted, the gravest was the impact of sewage on public health,

which reportedly led to the death of one individual. The respondent stated that,

while this individual was working on his boat in the Creek directly off of the

respondent’s property, effluent from the outfall pipe flowed into the river, and

made direct contact with the man. This individual subsequently contracted this time. The city of Chelsea desires continued funding of this program in new phases to allow the city to move forward with further separation of combined flows tributary to CSOs. All the projects above are funded by rate revenue from all MWRA member sewer communities. Boston Water and Sewer Commission has indicated an unfavorable view of further funding. The town of Brookline with the project added in 2005 completed its separation. The inherent unfairness in this is that BWSC has substantial reserves and a much larger rate base to fund projects and the town of Brookline has a much higher per capita income level to fund projects than a community like the city of Chelsea.”

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hepatitis and died. While this was the most extreme case of the reported public

health threats from CSOs, the dangers to public health posed by CSOs were

frequently noted as a serious concern by survey respondents.

Despite being a small survey population, discernible trends emerged,

indicating a number of key elements of agreement among members of the affected

communities. Their concerns included public health impacts, nuisance effects

such as odor and unsightliness, property damage and devaluation, and reduced

recreational opportunities. Additionally, most respondents felt that there was

unfairness in the distribution and impacts of CSOs in their communities. Finally,

a majority of respondents wanted the CSOs to be eliminated and hoped that this

would expand safe recreational opportunities on the river.

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Chapter Five: Research Limitations and Further Research

While all efforts were taken to make this study as rigorous and exact as

possible, there are, nonetheless, limitations. It is important to acknowledge these

limitations, as well as to explore the ways in which future research could be

conducted. This is a topic area ripe for further research. This research could

focus on any number of angles, including the technical components of the CSO

infrastructure and exposure potential, the demographic dynamics of CSO

distribution, and the numerous ways of assessing environmental equity by

incorporating other spatial attributes of combined sewer overflows.

Spatial Scale and Exposure Potential

Selecting the appropriate “study area” from which to draw my comparison

population was challenging in that it involved some judgment as to which areas

should be considered able to host a CSO that would affect the resident population.

This was sometimes difficult to assess using existing orthophotography and could

more accurately be done by incorporating ground truth data from site surveys as

well as detailed hydrologic characterizations of the watershed. Generally

speaking, it makes sense to utilize a unit of hydrologic significance such as a river

basin or watershed when conducting water-based research. However, the

watershed, while the logical hydrologic unit of analysis, does not necessarily

make the most sense from a policy or planning perspective. Perhaps more

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appropriate would be to conduct analysis at the level of the sewershed, defined as

all the land area that is drained by a network of sewers, or at a more politically

relevant civil unit, such as the city, county, or state. Better still would be for the

policy and planning arenas to themselves operate at a level or unit of analysis that

is more logical from a hydrologic or land use perspective, although this may be a

less likely transformation.

The sample size for the 2000 study area was limited to those 63 block

groups abutting the Mystic River and its main tributaries. A small sample size

limits the reliability of trends found in the data and also limits the degree to which

the study may render statistically significant results. A wider geographic area

(e.g., several watersheds across the Boston Metropolitan Area, the state, or the

nation) would offer a larger sample size from which to draw out trends in the data.

A particularly interesting equity study would entail a comparative analysis of the

demographics of exposure as well as preferential investment in treatment and

clean up of combined sewer overflow infrastructure within, across, and between

the Mystic, Charles, and Neponset River watersheds, all of which are under the

jurisdiction of the MWRA for sewer service.

The need for this research is underscored by the fact that a Chelsea city Public

Works employee indicated that the unfairness is not so much in where CSOs are

located, but instead in an unbalanced allocation of rate payer revenues toward

eliminating CSOs in the ratepayer service area. Therefore, a detailed analysis

should be conducted looking at preferential spending of public resources on

infrastructure projects across the MWRA ratepayer service area.

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Additionally, there are limits to the accuracy of both the “whole block

group” method and the “areal weighting” method employed in this analysis in

terms of accurately capturing affected populations. As detailed in the

Methodology, neither method is an entirely precise means of analyzing the

demographics of impacted areas. The main issue with the “whole block group”

method is that because the buffer zone of impacts is smaller than our unit of

analysis, here the block group, identifying whole block groups as affected by

CSOs is too gross a measure of impacted area. The limitations specific to the

“areal weighting” method relate to the fact that we must make assumptions about

the uniform distribution of population across the block groups that may not be

accurate. Such a limitation could perhaps better be dealt with in future studies by

employing a land use weighted areal interpolation method in order to construct

more accurate estimations of where the population within a block group truly

resides.

As far as exposure assessment, the currently employed buffer analysis

may not be sufficient for accurately assessing exposure potential to CSOs. While

this was based upon available information, for reasons enumerated in the

Research Methodology section, there are inherent limitations to this approach.

Additionally, due to their differing hydrologic and fluvial features, using the same

fixed CSO buffer zone for both the Mystic River and Alewife Brook may make

less sense than choosing CSO buffer zones unique to each watercourse.

Furthermore, use of a circular buffer for water pollution point sources may not

represent the best proxy for exposure. A more nuanced analysis that takes into

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account hydrologic and meteorological factors, such as using geographic plume

analysis, might more accurately assess geographic impacts of CSO events. While

this is a relatively new area for research, a few prior studies may aid in developing

an appropriate methodology (see Pun and Davidson, 1999; Cormix, 2007; ESRI,

2007; and Doneker and Jirka, 2007).

Other proximity measures that could be employed include characterizing

the CSO impact zone based on the access radius to the river, such as done by

Neltner in his 1999 study of CSOs in Indianapolis. For his unit of analysis,

Neltner (1999) chose to use Census tracts, noting that tracts typically extended

one-quarter to one-half mile from the stream, which is the rough distance that

children in the neighborhood would walk to play in the stream. Thus, Neltner

chose an impact zone based on recreational access to the river, as opposed to a

residential or a technical plume-based measure.

Future research on CSOs in the Mystic River Watershed could take a

similar approach by defining CSO impact zones based on recreational access to

the river in order to better capture the full extent of the impact on the surrounding

communities. This research could draw upon the existing studies of recreational

use of the river conducted by the Mystic River Watershed Association, as well as

employ additional research on human traffic flows to the river from the

surrounding communities to understand which groups are using the river and in

what ways they are using it. This information would facilitate a better

understanding of the risks posed to community members by the CSOs and would

inform creation of a more nuanced, and perhaps more practical, impact zone.

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It is, thus, critical to assess the demographics of river uses so as to

determine which community members, whether or not they actually live near the

river, are being most affected by the CSO-polluted waters, and in what specific

ways they are being affected. For instance, it is known that many minority

individuals fish in the Lower Mystic River and may be consuming their catch,

which is unsafe given the high pollutant levels in the water. There are also many

boaters (using canoes, kayaks and other low-to-the-water boats) who may

experience direct contact with the water. There have also been reports of children

swimming in sections of the Lower Mystic River, which would pose very serious

health threats to those children. Thus, being able to assess health impacts from

river uses across communities in the watershed would be another useful measure

of environmental equity in the watershed and would aid in effective planning to

ensure safe recreational use of the waterways.

Subsequent research could also utilize other measures of differential

environmental equity in regards to CSOs. For instance, in making his case for the

disproportionate burden borne by certain minority communities in the

Indianapolis area, Neltner (1999) also examined the amount of sewer overflow

per area under optimal conditions (that is the “best case” scenario) as well as

preferential capital investment by the city into areas with low minority

populations. Future research could incorporate data on the frequency and volume

of discharges from the various CSOs in the watershed to assess the differential

impact that each of these outfalls has on the surrounding community, either

through residential or recreational exposure. While I began compiling discharge

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data for CSO outfalls within the watershed, I encountered much difficulty in

gathering these data due to the decentralization of CSO administration, with each

CSO owner (municipality, agency, etc.) independently maintaining its own CSO

monitoring and data collection process without coordinated standards or

procedures.45 More specific, standardized criteria and requirements for

monitoring and reporting CSO activation events should be issued, and these data

should be compiled and centrally managed by the Massachusetts Department of

Environmental Protection so that it is available for analysis by internal and

external reviewers. Not only would this information allow better analysis of

human and ecological exposure but would also allow assessment of the extent to

which specific CSOs are contributing pollutants to the watershed and thus which

outfalls should be prioritized for treatment or elimination.

While assessing exposure potential based on proximity to CSO outfalls or

by differential discharge volume and frequency is one useful means of measuring

environmental equity in the watershed, in future studies it would be of use to

incorporate actual water quality data for the river. This would allow examination

of whether there are differences in the pollution levels in the water adjacent to

different communities. Such an analysis could serve to indicate water quality

45 EPA has a guidance document on the Nine Minimum Controls included in the federal and state CSO policies, which sets forth recommendations for CSO monitoring and public notification measures. While this document makes recommendations for monitoring and public notification best practices, it is up to individual permitting agencies to include them as enforceable permit conditions. The reporting requirements for CSO permittees, typically established in their NPDES discharge permits, often require an annual or quarterly report documenting CSO activations and volumes. For the Mystic River CSOs, the permits also reference the CSO variance requirements, which include criteria for CSO monitoring and public notification. However, there is no clearly articulated standard requirement for CSO monitoring and reporting. In general, Mass DEP tries to include in permits immediate notification to any resource managers (public water suppliers, beach monitors, etc.) when a CSO discharge may impact a sensitive use resource (Brander, 2008).

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impacts of specific CSOs as well as to demonstrate the larger context of

disproportionate pollution burdens in the watershed.

Although water quality will fluctuate somewhat across time and weather

conditions, better, more frequent monitoring would allow an approximation of

water quality conditions along the river that can be analyzed for residential and

recreational exposure potential. Although I would argue that its sampling data

were insufficient, the EPA characterized water quality for its Mystic River

Watershed Report Card by using samples collected by the Mystic River

Watershed Association (supplemented with some data collected by the

Massachusetts Water Resources Authority). Based on this sampling, in April

2008, in its second public reporting on the condition of the Mystic River since

announcing a collaborative effort last year to address water quality issues in the

river, EPA gave the Mystic River Watershed a grade of "D" (U.S. EPA, 2008).

Based on bacterial contamination, EPA’s assessment concluded that over the past

year the Mystic River Watershed met swimming standards 46 percent of the time

and boating standards 79 percent of the time. As can be seen in Figure 14, there

are a number of sections of the watershed that, based on bacterial contamination,

clearly have poor water quality. Unfortunately, all of the blue colored areas, such

as the majority of the lower watershed, are missing data and so at this point

cannot be assessed for comparative water quality. While some recently-added

monitoring points will aid in bridging these gaps, large sections of the river will

continue to go unmonitored. In order to conduct a reliable equity analysis of the

demographics of exposure to varying pollutant levels in the watershed, these gaps

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in water quality data must be bridged. Thus, as will be explored further,

increasing the breadth of water quality monitoring should be a high priority for

the watershed.

Figure 14. U.S. EPA assessment of water quality in Mystic River Watershed, 2008. (Image courtesy of United States Environmental Protection Agency New England).

Additional research could include a more detailed longitudinal analysis of

community demographics over time with respect to CSO areas. For instance, this

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could look at demographic changes in the watershed with respect to CSO closures

over more than a 10-year time frame -- particularly as communities developed

alongside CSOs. Another component of this research could assess affects on

housing prices from CSOs, looking at property values in CSO-affected areas

compared with other sections of the watershed.

In order to fully assess any inequities in the siting of CSOs, a more

detailed analysis than was completed in this thesis is needed. As noted

previously, this would first require identifying exact construction dates for each

CSO outfall. This would likely require examining historical construction plans

for the sewer infrastructure across multiple municipalities, which would pose

numerous data gathering challenges. Researchers would need to obtain detailed

parcel development data for all land located within the established impact zone of

CSOs. These data would need to indicate the year each parcel was originally

built, as well as what type of development took place at that time. This would

likely be best conveyed by zoning designation at the time of initial development.

Additionally, to the extent available, data on the demographic makeup of these

affected parcels would be needed. A detailed analysis would then allow

assessment of whether there were any inequities in siting of CSOs at the time they

were developed.

Measures of Significance

In addition to simply comparing the demographic data for each of the

areas identified as affected or not affected by CSOs, it would be useful to perform

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a statistical regression analysis to evaluate significance of distributional patterns

by demographic characteristics. To do this, a larger sample set would be

beneficial. Then one could employ a logistic regression model, which is a

statistical tool used for prediction of the probability of occurrence of an event.

Logistic regression is one of a class of models known as generalized linear

models (Agresti, 2002). It allows one to predict a discrete outcome, from a set of

variables that may be continuous, discrete, dichotomous, or a mix of any of these.

Generally, the dependent or response variable is dichotomous, such as

presence/absence or success/failure. In this case, one could examine the statistical

significance of various demographic characteristics on the likelihood of living in

an area affected by CSOs. Thus, the dependent variable would be binary as the

presence or absence of a CSO impact zone overlaying a block group. The

independent (predictor) variables could be any number of demographic

characteristics at the block group level such as percent non-English speaking

households, percent minority (non-white) population, percent of population

without US citizenship, average median household income by block group, and

percent population below the poverty level. By employing a regression analysis,

we would be better able to determine if the correlation of CSOs occurring with

certain demographic characteristics is statistically significant.

Despite some noted limitations to this research, it creates a solid

foundation for investigating the equity of CSO distribution across communities in

the Mystic River Watershed. Furthermore, there are many important

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opportunities for further research in this arena that will aid in examining

environmental equity issues pertaining to CSOs in the watershed. This research

will expand our understanding of the social demographics of water pollution

while also providing valuable insight into strategies for effective management of

these environmental and social justice problems.

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Chapter Six: Conclusions and Recommendations

Even though this study indicates a need for further research on a number

of aspects of the demographic distribution of CSOs, it nonetheless has important

implications for public policy and planning right now. These include a need for

better water quality monitoring in the watershed, as well as improved

coordination and management of the collected data. Also important is the

expedited elimination of those CSOs affecting environmental justice populations,

especially through residential and recreational exposure. Finally, targeted public

education about the dangers of CSO exposure and a more effective system of

public notification about CSO activations are critical to addressing the impacts of

CSOs on communities.

Water Quality Monitoring

As is evident from Figure 14, which displays the monitoring sites in the

watershed that served as the basis for EPA’s water quality grading as well as the

areas of the river for which no water quality data were available at the time of

assessment, there is an inadequate number of monitoring sites in the watershed.

This is particularly true of the lower sections of the watershed. Increased breadth

and frequency of monitoring is needed in order to more accurately characterize

the water quality across the watershed. In addition, monitoring should also be

better tailored to understand the various pollution sources so as to understand the

differing roles that CSOs, SSOs, and stormwater runoff play in contributing

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contaminant loads to the watershed. If environmental managers had a better

understanding of which particular outfalls or non-point sources were contributing

the greatest pollutant loads to the watershed, they could better focus limited

resources to address these priority sources.

Water quality monitoring within the Mystic River Watershed is currently

conducted by MWRA, MyRWA, and Mass DEP, without any coordinated effort

to centrally manage these data. This greatly limits the value that could be gained

from these data were it a more comprehensive collection. There should be a

central database and clearinghouse for all of the water quality data collected in the

watershed. The most logical agencies to manage this information would be Mass

DEP or EPA given their independent regulatory authority. In addition to a

centralized data clearinghouse, an independent technical advisory body should be

established to ensure quality control and standardization of this data collection

and analysis. This body, to be made up of water resource experts across various

industries and sectors, should also ensure that monitoring is adequate to cover the

correct types of contaminants of concern in the watershed and to cover a full

geographic range of sample sites throughout the watershed, paying particular

attention to areas where the public is most vulnerable to contact with

contaminated water. These high-priority sites should include residential and

recreational areas identified through land use analysis, as well as specific areas

community members identify as putting people at risk. These include areas of the

river known to be popular swimming holes or fishing spots, regardless of their

zoned status.

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CSO Clean Up and Elimination

While all active CSOs should be eliminated, special focus should be paid

to those CSOs that are within particularly vulnerable communities. These

communities can be identified as those block groups that are composed of high-

minority, low-income, high-foreign born or high non-English speaking

populations. Examining the map of EOEEA-designated environmental justice

populations overlain by active CSOs (Appendix D), I have determined that the

CSOs affecting EJ communities are CAM001, CAM002, CAM400, CAM401B,

SOM001A, SOM007A/MWR205A, MWR205, CHE002, CHE003, CHE004,

CHE008, BOS003, BOS004, BOS005, BOS006, BOS007, BOS009, BOS010,

BOS012, BOS013, BOS014, BOS019. These CSOs should be prioritized for

removal, as noted more particularly below.

Attention and resources for CSO removal should also be prioritized based

on proximity to residential and recreational land use areas as these pose the

greatest risk for putting humans in direct contact with polluted water. Based on

the previously conducted land use analysis, I determined which areas are of

greatest concern for residential land use within clusters of active CSOs. I see that

the areas with the most residential land affected by CSOs are along Alewife

Brook (102 acres) and the “Chelsea Main Cluster” area along the mouth of

Chelsea Creek and the lower stem of the Mystic River (34 acres). These areas

include outfalls CAM004, MWR003, CAM401B, CAM002, CAM001,

SOM001A and CAM400 in the case of Alewife Brook, and outfalls CHE002,

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CHE003, BOS013, BOS012, BOS010, BOS009 and CHE004 in the case of the

“Chelsea Main Cluster.” These relatively large residential areas are likely to pose

significant health risks to the public given their close proximity to the active

CSOs. Thus, special attention should be paid to treating or eliminating these

outfalls.

Recreational lands are also of top concern. The area along Alewife Brook

has 31 acres of land designated as “participation recreation,” along with another

35 acres of open land and 12 acres of wetlands, all of which are likely to host

significant recreational activities that could expose people to CSOs. Other areas

with significant recreational and open land include the Chelsea Main Cluster (41

acres), the East Boston side of Chelsea Creek around outfall BOS014 (11 acres),

East Boston along the lower Mystic River around outfalls BOS007, BOS006,

BOS004, BOS003, and BOS005 (12 acres), and in Somerville near outfall

BOS017 (15 acres). Each of these areas should be carefully considered as a

priority area for CSO elimination due to potential public health impacts from CSO

events.

As noted, river use surveys have shown extensive recreational uses of the

river, including walking, running, boating, fishing and swimming. Given the

substantial land- and water-based recreation in the Mystic River Watershed,

special attention should be paid to these recreational access areas. Whether

identified through land use analysis or by community survey, these recreational

access areas should be carefully monitored for contamination and should be

prioritized for CSO clean-up and removal.

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Those CSOs which affect environmental justice communities as well as

areas of significant residential or recreational lands include CAM001, CAM002,

CAM401B, SOM001A, CHE002, CHE003, CHE004, BOS003, BOS005,

BOS006, BOS007, BOS009, BOS010, BOS012, BOS013 and BOS014. Given

that these CSOs affect both particularly vulnerable communities as well as types

of land use that offer the most significant public health risks to community

members, these CSOs should be most immediately targeted for clean up and

elimination.

Targeted Public Education and Notification

Protection of public health requires a more effective system of public

education and outreach about the dangers of CSOs and the ways to minimize

exposure to the contaminants that they convey. The current system of education

provides very limited information about the threats from CSOs. At present, CSO

locations are essentially denoted by signs placed adjacent to each CSO outfall,

including some variation of the following message: “Wet Weather Sewerage

Discharge Outfall # XX.” The technical language found on these signs is difficult

for most people to understand. Moreover, in many cases the signs are so old and

weathered that the text is not legible or the signs are covered by plant growth.

The images below are of two CSO signs along Alewife Brook, one at the edge of

an urban park in Somerville and one along Alewife Brook Reservation in

Cambridge (see Figure 15). Adjacent to many of the outfalls along Alewife

Brook are openings in the fence separating the brook from the parkland, thereby

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providing easy access to the brook. As a testament to the inadequacy of the

public notification system, often children play here along the banks of the brook

directly above the sewage outfall pipes. A walk along the banks also shows other

indications of recreational use, including a worn walking trail, makeshift benches,

and firepits. As was echoed in the community surveys, no matter how well

barricaded the river is, citizens in search of contact with the natural world

frequently will find ways to reach it. Thus, it is critical to adequately educate the

community about how to safely coexist with CSOs.

Figure 15. CSO signage along Alewife Brook.

Signage should be far less technical so that average citizens understand

what is being identified, and should also explain the risks associated with coming

into contact with the contaminated water as well as the conditions likely to cause

CSO activation. Additionally, given the high minority (especially Hispanic)

populations of the communities in the watershed, these signs should at least be

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translated into Spanish, if not other languages as well. While effective signage

should be placed at every outfall in the watershed, it is especially critical in areas

where recreational access is pervasive and thus exposure potential is high.

Individual CSO identification signs should ideally be part of a larger

public education campaign. This campaign should fully inform the public about

CSO issues, as well as to engage individuals in the monitoring process. In

response to New York state’s 1995 passage of the Discharge Notification Act

(DNA), which required that signs be installed at all permitted combined sewer

overflow discharge points, New York City’s Department of Environmental

Protection (NYCDEP) embarked on an ambitious plan to implement this mandate

(Rozelman, Lutz, & Loncar, 2001). The NYCDEP program both educates citizens

and involves them in monitoring and identifying problems. It mainly did this

through educational signage. Figure 16 below is an example. Citizens can notify

NYCDEP at a given phone contact point so that NYCDEP can investigate

problems. Thus, the sign enlists citizens as additional environmental monitors as

well as involves them in community environmental affairs.

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Figure 16. NYCDEP CSO signage. Image source: NYCDEP.

Similar signs could be installed along heavily trafficked portions of the

Mystic River waterfront, such as in designated riparian parks and recreational

areas. These signs could inform the public of the function of CSOs, alert people

of the risks associated with sewage contaminated water, and enlist them in

monitoring dry weather discharges at outfalls. With explanatory signs like these

placed in key locations, individual identifier signs at each outfall will make more

sense. These identifier signs would also inform people so that they can make

informed choices about when and where to recreate, and would identify each

outfall for the purposes of reporting on any dry weather discharges.

Although signage that identifies CSOs in the Mystic River Watershed is

inadequate, the system for notification of CSO activations is even more

insufficient. Although there is no statute or regulation requiring public

notification about CSO activations, the Nine Minimum Controls (NMCs) included

in the federal and state CSO policies make reference to "public notification"

(Brander, 2008). The nine minimum controls are identified in EPA’s CSO

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Control Policy as minimum technology-based controls that can be used to address

CSO problems without extensive engineering studies or significant construction

costs, prior to the implementation of long-term control measures. EPA has a

guidance document on the NMCs which sets forth recommendations for public

notification measures. The permittees are encouraged to select the most "cost-

effective" method for notifying the public “that provides reasonable assurance

that the affected public is informed in a timely manner” (U.S. EPA, 1995, p.9-1).

The vagueness of this guidance allows for a lot of interpretation by NPDES

permitting authorities and affected municipalities.

The reporting requirements for CSO permittees are typically established in

their NPDES discharge permits and mostly include an annual or quarterly report

to Mass DEP documenting CSO activations and volumes (Brander, 2008). For

the Mystic River CSOs, the permits also reference the CSO variance

requirements46, which also include requirements for CSO monitoring and public

notification. Mass. DEP’s reporting requirements specific to the Mystic River

Watershed CSOs generally require immediate notification to resource managers

(public water suppliers, beach monitors, etc.) when a CSO discharge may impact

a sensitive use resource (Brander, 2008). However, one resource manager in the

watershed indicated that compliance with public notification requirements is not

consistent, and that only one municipality within the watershed consistently

provides notification when one of its CSOs discharges (Dechant, 2008).

46 MWRA has been granted a variance by Mass DEP from having to meet water quality standards in the Lower Charles River Basin and in the Alewife Brook/Upper Mystic River; the variance is expected to be extended until MWRA fully implements its plan to reduce the impacts of CSOs in the harbor and rivers.

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Even if permittees did consistently notify resource managers when CSO

activations occur, this practice does little to reach those who are at the greatest

exposure risk, such as those living or recreating by the river without knowledge of

the risks they may be facing. Because most recreation along the Mystic River and

its tributaries does not occur in easily defined beach areas -- instead involving

boating, fishing, and swimming at diverse access points (MyRWA, 2006) --

resource managers need to do more than issue beach closings. Rather, they must

transmit information among a number of communities that use the river in varying

ways. Therefore, a mechanism of widespread community notification should be

employed following each CSO event. This could be done through coverage in the

local newspaper or television news reporting, or through some other means

known to have wide reach throughout the community. Regardless of the exact

means chosen, there needs to be prompt, clear and extensive notification of

community members about any CSO activations that occur so that individuals can

make informed decisions about where and when to work and recreate in the

Mystic River and its tributaries.

Additionally, in order to most effectively manage public health risks and

ensure safe recreational opportunities for all community members in the face of

these constraints, additional study is needed on how different groups are using the

river. An updated study expanding on the report prepared by MyRWA on river

usage should be funded and administered by the Massachusetts Department of

Conservation and Recreation as part of its current Mystic River Corridor planning

efforts. Particular attention should be paid to how minority groups are using the

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river and its adjacent lands in ways that may not be obvious to planners. A 2007

study commissioned by the Barr Foundation examined the specific ways in which

recent immigrants to Boston connect to public parks and open spaces (Lanfer &

Taylor, 2007). This and other related research should be utilized as an integral

part of planning for safe and culturally appropriate recreational opportunities for

the diverse communities of the Mystic River Watershed.

In order to fund the above measures, additional public funds, including

MWRA ratepayer fees, and federal, state and local taxes should be utilized. In the

event that public financial resources are unavailable to implement all of the CSO

elimination, education and notification projects that are needed, projects should be

compiled as part of a running list of Supplemental Environmental Projects (SEP).

A SEP is an environmentally beneficial project that a violator of environmental

laws voluntarily agrees to perform, in addition to actions required to correct the

violation(s), as part of an enforcement settlement by EPA. While EPA provides

oversight to ensure that the violator carries out the project, the violator must

provide all funds used to finance the project. CSO-related projects could fall

under the categories of “Public Health” or “Other” projects with environmental

merit that are acceptable SEPs (U.S. EPA, 2007f). Additionally educational and

notification projects might be funded by corporate sponsorship or philanthropic

dollars channeled through the nonprofit Mystic River Watershed Association.

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Final Conclusions

This research has attempted to investigate several aspects of the

distribution of CSOs across communities in the Mystic River Watershed. It first

looked at whether the distribution of active CSOs disproportionately burdened

certain communities. Despite some noted methodological limitations, this initial

assessment suggests that currently active CSOs do disproportionately affect

lower-income and higher-minority populations within the Mystic River

Watershed.

In order to assess which CSOs likely pose the most significant public

health risks to the community, I examined the distribution of land uses within the

specific portions of block groups that are affected by active CSOs. These findings

allowed me to make suggestions for targeted CSO removal in the watershed.

In addition, my research examined a number of demographic trends

related to CSO closures in the watershed. This included a temporal analysis of

the changes in demographic characteristics of the region over the timeframe

within which CSOs were closed. While not entirely conclusive, this research did

indicate that those areas affected by CSOs (both active and closed) experienced

the sharpest rise in minority population as a percentage of the total population as

well as the smallest growth rates in median household income during the period

1990 to 2000. Additional research would be needed to determine what role CSOs

played in shaping these demographic trends, especially when considering broader

demographic trends across the region. This research also included examining

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demographic differences between those 1990 CSO-affected block groups that had

their CSO burden relieved and those that did not. This particular analysis showed

that the areas within the watershed where CSOs were not closed (and thus remain

active to date) are higher minority and lower income areas than those areas where

CSOs were closed.

Further study examined the history of CSO siting in order to determine

whether the Mystic River Watershed CSOs were put in place prior to or after

neighborhoods formed in the region. While I was unable to conclude with any

certainty whether or not CSOs were sited in pre-existing residential

neighborhoods, I did find that there are a number of areas within the watershed

where this is at least a significant possibility and thus where additional research is

warranted.

Finally, surveys of select community members provided valuable insight

into the effects and perceptions of CSOs in the community. Commonly reported

concerns included public health impacts, nuisance effects such as odor and

unsightliness, property damage and devaluation, and reduced recreational

opportunities. Most respondents felt that there was unfairness in the distribution

and impacts of CSOs in their communities and wanted the CSOs to be eliminated,

hoping that this would expand safe recreational opportunities on the river.

While not surprising, the findings of this study are nonetheless alarming

and raise numerous policy and planning questions -- both with regard to what

caused this inequity as well as how it might be rectified. It is clear that further

126

research will be necessary to better understand the causes of the inequities

explored in this study. Some of these research opportunities have been laid out

above in the hopes of encouraging further investigation of these issues.

While outlining a comprehensive policy and planning response is outside

the scope of this thesis, several immediate action steps have been proposed.

These include the immediate closure of those CSOs which affect environmental

justice communities as well as areas of significant residential or recreational

lands. Given that these CSOs affect both particularly vulnerable communities as

well as types of land use that offer the most significant public health risks to

community members, these CSOs should be most immediately targeted for clean

up and elimination.

In addition to targeted CSO removal, protection of public health requires a

more effective system of public education and outreach about the dangers of

CSOs and the ways to minimize exposure to the contaminants that they convey.

As detailed above, this includes improved signage that is clearly visible, easily

comprehendible, and adequately informative about the risks associated with

coming into contact with the contaminated water as well as the conditions likely

to cause CSO activation. CSO identification signs should be part of a larger

public education campaign designed to fully inform the public about CSO issues.

It is particularly important to employ a mechanism of widespread community

notification following each CSO event so that individuals can make informed

decisions about where and when to work and recreate in the Mystic River and its

tributaries.

127

The Mystic River and its surrounding watershed have long suffered

neglect and abuse at the hands of industrial society. For far too long this vital

water resource has been mistreated and taken for granted by those unable to see

its potential as an invaluable public asset. Just as the waterway has suffered, so,

too, have many of the people living along the river’s shores. This study attempts

to highlight but one of the many burdens faced by these communities. While this

research is by no means comprehensive, it may, in some small way, help us to

understand the disproportionate burden that certain communities along the river

face in their daily lives. And if it is true, as has been proposed throughout the

ages, that the justice of society is measured by its treatment of the downtrodden

and disadvantaged (Rank, 2004), then it is our duty, as a just society, to rectify

those injustices that lay evident before us.

128

Appendix A: Combined Sewer Overflow (CSO) Survey Questions

Combined sewer overflows (CSOs) are the discharges from combined sewer

systems (CSSs), which were designed to carry sanitary wastewater (domestic

sewage from homes as well as industrial and commercial wastewater) and storm

water through a single pipe. During heavy precipitation events (e.g. rainfall or

snowmelt), the wastewater volume is often more than the sewer system or

treatment plant can handle and so the systems are designed to overflow when

collection system capacity is exceeded, resulting in a combined sewer overflow

(CSO) that discharges wastewater directly to surface waters such as rivers, lakes

and coastal areas. The wastewater the CSOs carry not only contains storm water

but also untreated human waste and industrial waste, toxic materials and floating

debris.

There are 26 active CSOs in the Mystic River Watershed. Within the Mystic

River Watershed, CSO permits have been issued for the following municipalities

and agencies: Boston Water and Sewer Commission (Chelsea Creek & Mystic

River), City of Cambridge (Alewife Brook), City of Chelsea (Chelsea Creek &

Mystic River), the Massachusetts Water Resources Authority (MWRA) (Mystic

River, Alewife Brook), and City of Somerville (Mystic River & Alewife Brook).

Questions

1. Are you aware of combined sewer discharges in areas of the river that are close

to people in your city or town?

2. Do you notice foul smells or see things floating in the river after large rain

events?

3. Do you notice any negative effects of these CSOs in your community?

If so, what effects?

129

130

4. In what ways do you think that these CSOs harm members of your city or

town?

5. Are you concerned by these CSOs in your community?

If so, how concerned are you with this issue: not concerned, somewhat

concerned, very concerned?

If you are somewhat or very concerned, what are your specific concerns?

6. If CSOs are a concern in your community, how do residents show their

concern?

7. Do you believe there to be any unfairness in terms of which areas of your city

or town have CSOs?

8. Have you or others in your community had discussions about CSOs with your

legislators or city officials?

If so, how did they respond?

9. What would you like done about CSOs in your community?

10. If the CSOs that affect your city or town were cleaned up or removed, in what

additional ways, if any, would you use the river?

11. For how many years have you noticed any of the impacts identified in your

responses?

12. Are there others with whom you think I should share this survey?

MEDFORD

WINCHESTER

WOBURN

ARLINGTON

BELMONT

MELROSE

STONEHAM

MALDEN

EVERETT

CHELSEASOMERVILLE

BOSTON

LEXINGTON

Median Household Income (US 1999 $)

0 - 35,000

35,000 - 50,000

50,000 - 70,000

70,000 - 100,000

100,000 - 200,000

Active CSO Outfalls

Appendix B:Median Household Income by 2000 Census

Block Group in Mystic River Watershed

ÜMA

NY

CT

NHVT

RI

NJ

ME

0 2.5 51.25Miles

MEDFORD

WINCHESTER

WOBURN

ARLINGTON

BELMONT

MELROSE

STONEHAM

MALDEN

EVERETT

CHELSEASOMERVILLE

BOSTON

LEXINGTON

0 2.5 51.25Miles

Percent Minority0 - 10

11 - 20

21 - 30

31 - 50

51 - 90

Active CSO Outfalls

Appendix C:Percent Minority by 2000 Census

Block Group in Mystic River Watershed

ÜMA

NY

CT

NHVT

RI

NJ

ME

MEDFORD

WINCHESTER

WOBURN

ARLINGTON

BELMONT

MELROSE

STONEHAM

MALDEN

EVERETT

CHELSEASOMERVILLE

BOSTON

LEXINGTON

MANY

CT

NHVT

RI

NJ

ME

Ü0 2.5 51.25Miles

Watershed Block Groups

Mass EOEEA EJ Populations

Active CSO Outfalls

Appendix D:Environmental Justice Populations

within Mystic River Watershed

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