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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:

  1. 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.
  2. 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 IncomeAll Tracts Tracts with
    TRI Emissions
    Percent
    130 - 150,000100
    120 - 130,000100
    110 - 120,000100
    100 - 110,000400
    90 - 100,000600
    80 - 90,0001000
    70 - 80,000142*.14*
    60 - 70,000392.05
    50 - 60,000688.12
    40 - 50,0008311.13
    30 - 40,0005113.25
    20 - 30,000195.26
    10 - 20,000200
    0 - 10,000100
    Total30041

    * 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 LatinoAll TractsTracts with
    TRI Emissions
    (expected frequency)
    Percent
    23.5 - 82.07517
    (10.25)
    0.23
    13.2 - 23.57512
    (10.25)
    0.16
    7.0 - 13.2758
    (10.25)
    0.11
    0 - 7.0754
    (10.25)
    0.05

    Sources: 1990 EPA TRI data; 1990 US Census data.

  3. 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.


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Copyright 1996-1998 Michael R. Meuser and Andrew Szasz


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