Our Project
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Introduction
We are using Census and EPA
TRI data to examine "environmental inequalities" in Santa Clara
County, CA, a County that contains both Silicon Valley and San Jose,
now the biggest city in Northern California. Our ultimate goal is
to explore the historical dimension, or the process that leads to
unequal outcomes.
There is, by now, a large body of research that suggests that poor
people and people of color are more likely to live in polluted areas
(neighborhoods with poorer air quality, communities in close proximity
to hazardous waste and solid waste dumps). Some recent studies have
failed to find such inequalities. Even where inequalities exist, the
processes that produce them have only just begun to be studied
systematically and are, thus, now yet well understood. Our work on
Santa Clara County is one of several efforts currently underway to
begin to examine the production of environmental inequality.
Work to date
The first step in this research
was to document the distribution of toxics and its relationship to the
distribution of relevant demographic characteristics as of 1990. This
phase of the research produced the outcomes that will subsequently
have to be explained through detailed analysis of the
geography/history of industrial siting and residential
development.
We have collected our data from
various sources. Some helpful resources are listed below:
Some Preliminary Observations.
Visual inspection of the maps suggests the following:
- Toxics emitting industries are concentrated in a band that
stretches from the northwest corner of the county to the southeast.
Within that band, the densest concentration is in the center, close
to the intersection of several major transportation corridors.
- GIS mapping of census data, and simple distributions of both
census and TRI data, suggest, furthermore, that neighborhoods closest
to this band of toxic emitters tend, generally, to be poorer and more
Latino than the rest of the county (see Percent Latino and Median
Income maps).
Table 1.
The Relationship Between Median
Income and Presence of TRI Emissions
in
Census Tracts in Santa Clara County, 1990
| Median Income | All Tracts |
Tracts with
TRI Emissions | Percent |
| 130 - 150,000 | 1 | 0 | 0 |
| 120 - 130,000 | 1 | 0 | 0 |
| 110 - 120,000 | 1 | 0 | 0 |
| 100 - 110,000 | 4 | 0 | 0 |
| 90 - 100,000 | 6 | 0 | 0 |
| 80 - 90,000 | 10 | 0 | 0 |
| 70 - 80,000 | 14 | 2* | .14* |
| 60 - 70,000 | 39 | 2 | .05 |
| 50 - 60,000 | 68 | 8 | .12 |
| 40 - 50,000 | 83 | 11 | .13 |
| 30 - 40,000 | 51 | 13 | .25 |
| 20 - 30,000 | 19 | 5 | .26 |
| 10 - 20,000 | 2 | 0 | 0 |
| 0 - 10,000 | 1 | 0 | 0 |
| Total | 300 | 41 | |
* One of these tracts reports 24 lbs. of emissions, a de minimis amount. Thus, .07 would be a more realistic percent in the $70-80,000 category.
Sources: 1990 EPA TRI data; 1990 US Census data.
Table 2
The Relationship Between Latino
Population and Presence of TRI Emissions in Census Tracts in Santa
Clara County, 1990.
| Percent Latino | All Tracts | Tracts with
TRI Emissions
(expected frequency) | Percent |
| 23.5 - 82.0 | 75 | 17
(10.25) | 0.23 |
| 13.2 - 23.5 | 75 | 12
(10.25) | 0.16 |
| 7.0 - 13.2 | 75 | 8
(10.25) | 0.11 |
| 0 - 7.0 | 75 | 4
(10.25) | 0.05 |
Sources: 1990 EPA TRI data; 1990 US Census data.
- The wealthiest communities are far from the toxic corridor and
upwind of it. But we note there are important exceptions to the
general pattern, notably Census Tract 5116.98, near Stanford
University, a tract high in emissions that borders two of the
wealthiest tracts in the county.
Background -- The Literature on Environmental
Inequality/Racism/Injustice
Environmental Inequality Bibliography
Throughout the 1970s,
there were scattered reports in the social
science literature that environmental hazards are unevenly
distributed, they disproportionately impact the poor and people of
color (Asch and Seneca, 1978; Burch, 1976; Freeman, 1972; Kruvant,
1975). A handful of landmark studies done in the mid-1980s focused
discussion on race, especially African-Americans (Bullard, 1983;
Commission for Racial Justice, United Church of Christ, 1987; U.S.
General Accounting Office, 1983). In 1992, Mohai and Bryant
published the first, and subsequently very influential, review
of the literature. They reviewed about fifteen studies.
Researchers, they said, found both race and class inequalities;
in studies of both kinds of inequality, race was generally found
to be the more important determinant of excess risk.
These studies helped spur the
formation of a new force in the environmental movement, the Movement
for Environmental Justice. The Movement's synthesis of civil rights
and environmentalist frameworks or rhetorics has brought new segments
of the public to environmental action and has, more generally,
infused environmentalism with new energy. Its claims and perspectives
have also been endorsed by formal political actors, notably the
Clinton Administration (see U.S. Environmental Protection Agency,
1992, 1995a, 1995b).
Some recent studies, however,
suggest a far more complex picture. In some instances, the class and
race claims of the Movement (and earlier studies) are supported;
in others, only social class indicators, such as income and
occupation, prove significant; in still others, no clear relationship
is found (Anderton, et al, 1994; Bowen, et al, 1995; Burke, 1993;
Glickman and Hersch, 1995; Napton and Day, 1993; Schlossberg, 1995;
Szasz, et al, 1993; U.S. General Accounting Office, 1995). Such
findings do not disconfirm a relationship between social class and
race and differential exposure to environmental risks; they do
suggest that the relationship is very complex and that more
research is needed.
Researchers agree, too,
that future studies of environmental inequality must be historical.
"Snapshot" studies that examine social and industrial geographies
at a single point in time tell us little about the processes that
generate unequal risks, even when they find a significant relationship
between race and/or class and proximity to toxic materials. Some
local, historical case studies have begun to appear (Hamilton, 1995;
Hersch, 1995; Hurley, 1995; Krieg, 1995. Interestingly, most of these
are of older industrial cities such as Boston (Krieg), Gary, Indiana
(Hurley), and Pittsburgh (Hersh).
Demonstration of the existence
of environmental inequalities in Santa Clara County is only the
starting point for our research. We are planning to study the
historical processes that generated, over several decades, the
inequalities that are observed today.
Santa Clara County is a
potentially interesting site for such a study. Unlike some of
the other cities that have been studied, industrialization in the
County is a recent phenomenon. Forty years ago, the place was
largely agricultural. San Jose was a small town. There were
orchards everywhere. Today, San Jose is the biggest city in
Northern California. Silicon Valley is the nationally-recognized
epicenter of the computer industry -- economically, the heart of
the "post-industrial" era; environmentally, reputed to be clean and
green in comparison to earlier forms of production.
[ Our Project |
Santa Clara County Maps |
E.I. Bibliography |
Annotated E.J. Bibliography ]
