The South has been tagged as a "sacrifice zone" for the rest of America's toxic waste (Schueler, 1992; Bullard, 1990). More pointedly, the assertion is that racial minorities and the lower-income classes within this sacrifice zone bear a disproportionate burden of the region's environmental problems. A serious research effort has been undertaken to legitimize this claim, nationally and regionally, with results ranging from an unequivocal "yes" (United Church of Christ, 1987; Bullard, 1990; Mohai and Bryant, 1992; Pollock and Vittas, 1995) to several more recent studies suggesting "maybe" or "maybe not" (Yandle and Burton, 1996; Anderson et al., 1994; Been, 1994; Been and Gupta, 1997; Cutter et al., 1996; Cutter and Solecki, 1996). Past scholarly efforts, however, have focused on current outcomes with little regard to process--how the inequitable situation came into existence in the first place. Been (1994) notes that in some instances poor and minority residents living near locally unwanted land uses came to the area after the land-use siting decision had been made. Regardless of process or outcome mechanisms, blanket statements of environmental racism, certainly as applied to an entire region such as the South, demand critical review.
This article thus addresses the ambiguities in environmental justice research by examining the question of which came first: Did the residents come to the nuisance or was the nuisance imposed on them? In other words, were the sources of environmental threats (e.g., hazardous waste or Toxic Release Inventory sites) located in communities because they were poor, minority, or politically weak? Or were the facilities originally placed in communities with little reference to race or economic status, and, over time, did the composition of the area change due to migration, market dynamics, or some other factor? We present a systematic appraisal of process inequity in South Carolina and use this research as an illustration of some of the difficulties common to equity studies, such as geographic scale, population migration trends, economic development, and the uncertainties associated with data sources.
Determining Process Inequity
A longitudinal review of the circumstances that led to today's environmental picture requires the consideration of several factors. First and perhaps most troublesome is the scale of inquiry--that is, identifying the appropriate geographic unit of analysis (Cutter et al., 1996; Perlin et al., 1995). The United Church of Christ (UCC) study (1987) utilized zip-code areas, while others have used minor civil divisions (Zimmerman, 1993) or census tracts (Anderton et al., 1994; Been and Gupta, 1997; Burke, 1993). Inherent within all these studies is the assumption of a spatially uniform population distribution. In addition, the enumeration units inform us only about "night" conditions--where people sleep--but provide little insight into daytime risk. This is important in considering those who benefit from employment at a site but who may not carry the environmental burden because they reside elsewhere. (Still, census tracts remain attractive due to their relatively stable nature, availability, and comparability of population size [Been, 1995].) A third assumption is that tracts reflect the area around the facility, and that the area closest to the facility will therefore bear the worst impact. Although Pollock and Vittas (1995) discuss exposure as a function of distance, people living closest to a facility do not always face greater exposure than people further away. This assumption neglects the importance of toxicity and magnitude, method of pollutant dispersal, and the physical dispersal processes themselves, all of which contribute to the potential exposure (Glickman, 1994).
The utility of census tracts for longitudinal analysis is helpful only so far as 1980 for South Carolina (when the delineation first appeared statewide, not just in selected urban areas). This is a significant limitation. If we are to follow the premise established by Bullard (1994), that the present risk landscape, or riskscape, results from the past social and economic "backwardness" of the region, limiting our investigation to dates based on census-tract availability misses several opportunities. Environmental threats in the South did not just appear on the scene after 1960 with the rise of the "New South" and its accompanying rapid industrialization, but may have manifested themselves much earlier. To fully appreciate the injustice process, then, we must explore older established facilities, accepting that census-tract enumeration, while optimal as a spatial unit of analysis, should not be the limiting factor in our investigation. This research thus uses incorporated areas and counties as the spatial unit of analysis.
To conduct a statewide historical analysis, we selected Toxic Release Inventory (TRI) sites in South Carolina as our risk indicator. Although considerable controversy surrounds the reporting accuracy of industrial emissions in general (Air and Waste Management Association, 1997), and TRI releases specifically (Lynn and Kartez, 1994), TRI data are used widely in equity analyses (Perlin et al., 1995; Cohen, 1997). In using TRI data, we can compare results to existing studies and also replicate our methods for other places.
The TRI facilities included in this study met three criteria: 1) emissions were reported by the facility for each of the six years of the study (1987-1992); 2) facility emissions exceeded an average of 100,000 pounds for the six-year period; and 3) income and racial demographic data were available for the area in which the facility was located. Between 1987 and 1992 89 facilities in South Carolina reported more than 100,000 pounds of annual emissions; 17 of these reported more than 1,000,000 pounds of emissions. Census data were not available for the areas surrounding 7 facilities, so the total number of TRI facilities serving as point sources of environmental threats in this research is 82.
Establishing Accurate Locations and Facility Start Dates. Thirty of South Carolina's 46 counties (about 65%) host at least one of the 82 facilities used in this analysis. Our previous research found that almost half (48%) of the locations of South Carolina's TRI facilities were in the wrong block group, which required correction (Scott et al., 1997).
Facility establishment dates were confirmed using The South Carolina Industrial Directory (South Carolina Department of Commerce, 1941-1996). Entries in this directory include the following information: establishment dates, locations, employment totals, and product descriptions. The 1996 edition contains listings for more than 3,600 manufacturers with Standard Industrial Codes of 20 to 39. Determining plant start dates was a little more problematic than expected as several facilities changed corporate ownership or were renamed under another division; often the establishment dates on record reflected the time of that corporate change, not the date the plant was originally opened.
To maintain quality control over the establishment-date identification, we implemented a four-step date-confirmation procedure that included cross-checking earlier directories and local newspapers, consulting local economic development boards for host towns and counties, and contacting the companies directly. First, industrial directories were compared against each other to detect changes or inconsistencies in listings. Then local newspapers were researched for articles pertaining to plant openings. When establishment-date confirmation was unavailable using these sources, economic development boards were contacted for tax information that could point to a facility opening date. Direct firm contact was initiated as the last option if the other sources were unsuccessful. The industrial directory provided confirmation for 59 start dates, and 5 more were identified through researching newspaper articles and making calls to economic development boards. The remaining 18 facility start dates were confirmed via dire ct contact with the firms.
Demographic Characteristics. We collected data for incorporated areas and counties from the U.S. Census of Population and Housing in order to have a consistent geographic unit across all decades. The facility point locations and political boundaries were georeferenced and entered into a geographic information system (GIS). A one-mile buffer was constructed around each incorporated area (1990 boundary), so we could examine facilities located on the fringes of towns that might potentially affect those towns' populations. The incorporated areas were labeled as urban locations in our analysis. Suburban locations were defined by the one-mile buffer around the incorporated area, but did not include the urban core (i.e., the incorporated area). Rural locations were defined as everything beyond the one-mile buffer. Twenty-five sites were defined as urban, 28 as suburban, and 29 as rural. Data for incorporated areas were used for both the urban and suburban locales and county data were used for the rural places. The demographic data were collected for the period from the decade preceding the earliest establishment date of the facility through 1990. For example, if a facility start date was 1961, we collected socioeconomic data for that location starting with 1950.
The variable percentage Black is used in this analysis since the state populace has been overwhelmingly either African American or White. The 1990 census reflects this, as 98.8% of the state's population is either African American or White. In other words, to speak of this state's racial minorities in a historical sense is synonymous with discussing its African American population. Median family income was used as the economic variable because of its availability in the historic censuses.
Data Source Limitations. Creating a historical profile using census data posed several challenges. First, the variables reported in the census were not always uniform over time or geographic space. For example, the definition of certain variables changed, or they were reported differently from decade to decade--such as percentage Negro changing to percentage Black, changing to percentage Non-White--with subtle definitional changes. Also, we were unable to collect data for towns with populations smaller than 1,000 people for any decade. Finally, the geographic boundaries of incorporated areas changed over time. Facilities that were located in rural areas at start-up may now be located within a town boundary (e.g., in an urban area) because of population growth, annexation, or suburbanization. Unfortunately, most of the earlier incorporated boundaries are unavailable, a casualty of the large number of small towns in this investigation and the lack of historic geographic data about them. As such, the incorporate d areas described in this article refer to the 1990 boundaries.
Using the TRI as a measure of environmental threat also presents some limitations. First, the TRI represents only one of many potential environmental risks that communities face. Furthermore, it could be viewed as both an economic good (a source of jobs) and an environmental bad (a source of toxic releases). In addition, it is impossible to ascertain the quantity and toxicity of emissions prior to the implementation of the TRI reporting. Thus, we have made an assumption in our analysis that toxic chemicals were produced from the establishment date forward.
A final data concern is the establishment of a baseline with which to compare demographic changes in the TRI host communities over time. At least two possible solutions exist: paired community comparisons or comparisons to a larger standardized unit. Paired comparisons would allow changes to be followed between TRI and non-TRI host communities. This requires, however, a level of comparability between places that is difficult to achieve in South Carolina due to the varied spatial distribution of its population, economy, and industry. Instead, we have chosen to analyze demographic changes using the state means for each decade in which a facility has been operating.
The census data and the information on the TRI facilities were input into a geographic information system (GIS) for management, analysis, and display purposes. We examined three relationships: 1) regional variations in facilities' locations and start-up dates; 2) racial and economic differences between the state and the facility host area at the time of the facility's establishment; and 3) racial and economic differences between the state and the facility host area in 1990.
Regional Variations. Most of South Carolina's largest emitters were established in the 1960s and 1970s, a period coinciding with the rapid industrialization of the state as well as the South in general. Notable exceptions include a number of facilities established in old mill towns at the turn of the century. The oldest facility in our study (a phosphate producer) was founded in 1880 in Charleston. In contrast, the three newest facilities were built in 1987.
The geographic distribution of TRI facilities closely follows the historical industrial development of South Carolina (Kovacik and Winberry, 1987). Facilities are concentrated in the upstate region around the cities of Spartanburg and Greenville, both along the Interstate 85 corridor. Smaller clusters exist in Columbia, which is the state capital, and Charleston (see Figure 1). The facilities established earliest are scattered throughout the state and are located primarily within incorporated or urban areas. Beginning in the 1950s and continuing through the 1960s, most facilities were located in the upstate region. Also during this period a transition occurred in the location of the facility relative to the town (see Table 1). Beginning in the 1950s, the location of greater numbers of facilities shifted to the periphery of incorporated areas. By 1960, many were being situated in rural areas. This trend continued into the 1980s. The average facility establishment date for each category--urban (1952), suburban (1962), and rural (1969)--further demonstrates this trend of locating facilities farther from incorporated areas over the last few decades.
Race and Income of Facility Host Area at Establishment. Generally, the host areas with facilities in the upstate region were predominantly White. In the coastal plain, however, the reverse was true. These communities tended to be above the state average for the black population. The Midlands region was mixed. These demographic patterns in racial composition parallel both the historic and contemporary social geography of the state.
The average minority-population percentage for each host area by establishment decade was compared to the state minority-population percentage for the same decade (see Table 2). For instance, ten facilities were established in rural host areas in the 1970s, with an average minority population of 35.9% compared to the state's average minority population of 30.7%. The differences between minority-population averages for host areas and the minority-population average for the state were analyzed through a t test. No significant differences were found to exist for urban or rural host-area minority populations at establishment date as compared to the overall state minority average. Only in the suburban host areas in the 1950s and 1960s do we find minority percentages that differ significantly from the state mean. In this instance, however, the relationship is negative, indicating that on average, the populations of host facility areas were significantly more White than the state average.
The average income level for each host area by establishment decade was also compared to the state average income level for the same decade (see Table 3). For example, ten facilities established in rural host areas in the 1970s had an average income level of $6,000, compared to a state average income level of $7,621. The differences between the average income levels of the host areas and the average income level for the state were also analyzed through a t test. The average income levels for urban host areas in the 1960s and for suburban host areas in the 1950s, 1960s, and 1970s were found to be significantly higher than the state averages at those times. Only for rural host areas in the 1960s and 1970s were the average income levels significantly lower than the state average. Both Tables 2 and 3 only portray those instances where significance testing was possible; the absence or small number of facilities in previous decades precluded their analysis. It appears that for South Carolina, TRI facilities were l ocated quite equitably so that low-income and minority populations bore no disproportionate burdens.
Race and Income of Facility Host Area in 1990. There were few significant differences in income levels or minority-population percentages between host areas and the state at the time the facilities were established. In all but two instances the differences that are significant point to the establishment of facilities in host areas that had higher income levels and a smaller minority-population percentage than the state.
In examining the same host areas in 1990, however, we see that demographic patterns have changed dramatically. By 1990, all urban and suburban host areas had minority-population percentages that were significantly higher than the statewide average (see Table 4). In contrast, minority-population percentages for rural host areas continued to show no significant differences when compared with the state average in 1990.
Regarding income levels, by 1990 suburban host areas had income levels significantly lower than the state average (see Table 4). These same host-area income levels either were not significantly different or were significantly higher than the state average at the time the facilities were established. Overall, rural host-area income levels remained significantly lower than the state average in 1990; urban host-area income levels showed no significant changes.
We began this article addressing the following question: Did the residents come to the nuisance or was the nuisance imposed on them? Our results seem to indicate the former. When these facilities were established, there was no significant differentiation in host communities by race or income. It would appear that these facilities were not located in communities because they were poor or minority but instead were situated with little reference to race or economic status. Yet over time the socioeconomic composition of the areas in which they were located changed. Admittedly, however, the scale used here is too coarse to determine whether facilities are situated within predominantly minority neighborhoods in the host areas.
Several broad processes help to explain these changes. First, the percentage of the overall population that is Black has decreased substantially over time. Additionally, while Black populations in urban and suburban areas are growing, the reverse is taking place in rural areas. Lastly, the economics associated with the siting of industrial facilities influenced a shift of facility locations from urban areas to more rural locales.
While utilizing the local level as the scale of analysis is important for examining environmental equity, each area has unique characteristics that may create ambiguities in the analysis, thus making environmental equity claims more difficult. For example, contextual factors like statewide and regional migration and economic factors add to our understanding of the racial composition of areas around environmental threats. Simply relying on a time-series census analysis overlooks these important factors.
South Carolina's Racial Migration Trend. The shifts in the demographic composition of incorporated areas from White to Black likely has more to do with statewide migration trends than the actual siting of TRI facilities. South Carolina experienced a steady decline in its Black population relative to the total population as a consequence of a mass exodus of Blacks during the 1960s (see Table 5). This decline slowed beginning in the 1980s. The initial Black migrants were from the rural farm areas, with most leaving South Carolina for perceived better employment and social equality in northern cities. Apparent dissatisfaction with the North and a changing political and economic climate in South Carolina caused a reversal of the migration trend. Blacks were not returning to rural areas, however, but rather turning toward urban centers for work. The shift of more Blacks into metropolitan areas (such as Charleston) and the rapid suburbanization of Whites (as in Berkeley and Dorchester Counties, adjacent to Charlest on) dramatically altered the demographic profiles of host areas. Thus, the racial composition of TRI host areas with large Black populations may have been caused by state and regional migration trends, not necessarily by environmental injustices.
Inequity or Economic Development? Although TRI represents facilities releasing toxic chemicals into the environment, arguably benefits exist as well. Depressed local economies can be uplifted by employment generated by the plants and strengthened by an increase in corporate tax dollars. Lobbying by local areas for these plants can be intense even when it is known that hazardous by-products are part of the deal (Bourke, 1994). Indeed, the promise of financial benefits arising from the establishment of new facilities may have led to siting facilities closer to White communities in order to provide jobs. The pattern of facility siting in the predominantly White upstate region during the 1950s and 1960s potentially reflects this goal. The subsequent siting of post-1960 facilities in rural areas--those areas with an average income level significantly lower than the rest of the state--attempted to reverse this trend by bringing economic development to impoverished areas; this effort was a response to changing raci al and social attitudes within South Carolina.
Familiarity with the Local Context. Broad-based state, regional, or national studies of empirically based indicators designed to uncover inequity patterns make attractive, neat packages to hand policymakers, but they neglect several issues related to the local context. One example of the importance of understanding local factors is the Baxter Healthcare facility in Kingstree, South Carolina, which was established in 1961 and closed in 1996. Census data for 1990 shows Kingstree's population to be 64% Black with an income level only 60% of the state average. On the surface, the site of the Baxter Healthcare facility appears to be a strong candidate for an equity investigation. The facility, however, is actually removed from the town and its residents and instead is situated among vast acreages of farmland; the company only uses an Kingstree address. Thus Kingstree residents may not be at risk when compared to another community downwind from the facility. Further, the composition of the plant's workforce and th e location of workers' residences would determine whether those who live near the facility actually benefit from employment by its location. Only through this type of individual, local investigation can we truly understand the context and processes that produce inequities.
This research examined the issue of which came first: Were toxic facilities initially located in areas irrespective of racial or economic factors, and over time did community demographics change so that inequities appear to exist in 1990? Or were the facilities located in communities that were initially poor or minority and remained so during the intervening years? Our results suggest that the former mechanism was true for the state of South Carolina, The outcome of inequity that we see manifested in 1990 reflects sociodemographic processes of population change and not inequitable siting practices, at least at this scale of analysis. It appears that larger economic and social processes such as land cost and migration are more likely determinants of the current outcomes visible today than when the industrial facilities were initially sited.
While this study cannot provide indisputable answers to the question of environmental equity, it does point to the necessity of undertaking process-equity analyses in order to substantiate current claims of environmental inequity. It suggests three directions for future research. First, it would be useful to develop paired comparisons of communities with and without facilities to test for differences in sociodemographic changes. A second line of inquiry should detail the siting process as much as possible, including minutes from public hearings, tax records, government incentives, and a review of property values and changes over time. Finally, a third important research area involves differentiating between emission types, toxicity, magnitude, and disposal methods. An example of the utility of such research is provided by the following case: a particular social group resides near few facilities, and yet those facilities adjacent to it have the highest emission rate of toxic releases. It should be understood, however, that since the present research only examined one type of environmental threat, these conclusions therefore address only one part of the equity debate.
[FIGURE 1 OMITTED]
TABLE 1 Average Establishment Dates of TRI Facilities, by Type of Area Average Est. Date No. of facilities Urban Suburban (within incorporated (within one mile of Decade Est. area) incorporated area) Rural 1880s 1880 (1) * * 1890s * 1899(1) * 1900s 1904 (1) * * 1910s * * * 1920s 1920 (1) * 1928 (1) 1930s 1936 (4) 1937 (2) * 1940s 1944 (3) 1948 (2) * 1950s 1953 (3) 1954 (5) 1959 (1) 1960s 1963 (5) 1964 (6) 1964 (12) 1970s 1975 (5) 1974 (8) 1975 (10) 1980s 1986 (2) 1983 (4) 1982 (5) N = 82 1952 (25) 1962 (28) 1969 (29) * No facilities established. TABLE 2 Minority Population at Facility Establishment Date, by Host Area and State Average Average Host Decade No. of Host-Area State Area Est. Facilities % Minority % Minority t test Urban (n = 22) 1930 4 44.7% 45.7% -1.60 1940 2 30.9 42.9 -1.03 1950 3 44.5 38.9 1.52 1960 5 25.5 34.9 -2.19 1970 5 39.5 30.7 1.28 1980 2 41.7 31.2 1.25 Suburban (n = 25) 1930 2 51.3 45.7 0.89 1940 2 28.9 42.9 -1.84 1950 4 32.5 38.9 -3.67 * 1960 5 19.3 34.9 -4.55 * 1970 8 25.9 30.7 -0.83 1980 4 41.6 31.2 3.12 Rural ** (n = 27) 1960 12 40.0 34.9 1.01 1970 10 35.9 30.7 1.14 1980 5 38.3 31.2 1.57 * significant at p < .05; ** county data. TABLE 3 Income Level at Facility Establishment Date, by Host Area and State Average Average Host-Area State Host Decade Number of Income Income Area Est. Facilities Level Level t test Urban (n = 15) 1950 3 $1,664 $1,647 0.12 1960 5 4,740 3,821 3.41 * 1970 5 7,927 7,621 0.93 1980 2 16,500 16,978 -1.34 Suburban (n = 17) 1950 4 2,121 1,647 8.38 * 1960 2 4,774 3,821 45.38 * 1970 7 8,399 7,621 4.51 * 1980 4 15,443 16,978 -2.41 Rural ** (n = 27) 1960 12 2,858 3,821 -3.77 * 1970 10 6,000 7,621 -5.83 * 1980 5 17,053 16,978 0.089 * significant at p < .05; ** county data. TABLE 4 Minority Population Percentage and Average Income Level in 1990 for Host Area and State No. of Mean Host-Area Mean State Minority Facilities % Minority % Minority t test Urban 25 40.3% 30.9% 4.01 * Suburban 28 39.6 30.9 3.31 * Rural ** 29 36.5 30.9 1.97 Mean Host-Area Mean State Income Income Income t test Urban $29,122 $30,797 -1.73 Suburban 28,342 30,797 -3.40 * Rural ** 25,221 30,797 -7.04 * * significant at p < .05; ** county data. TABLE 5 South Carolina Black Population Change Census Year Black Population Total Population % Black 1880 604,472 995,577 60.7% 1890 689,141 1,151,149 59.8 1900 782,509 1,340,316 58.3 1910 836,239 1,515,400 55.1 1920 865,186 1,683,724 51.3 1930 794,725 1,738,765 45.7 1940 815,496 1,899,804 42.9 1950 823,622 2,117,027 38.9 1960 831,572 2,382,594 34.9 1970 796,086 2,590,516 30.7 1980 974,596 3,121,820 31.2 1990 1,079,729 3,486,703 30.9
* Direct correspondence to Susan L. Cutter, Department of Geography, University of South Carolina, Columbia, SC 29208. Upon request, the authors are happy to provide all data used in this study for replication purposes. The authors would like to thank Michael Scott, Charles Kovacik, and the anonymous reviewers for their constructive critiques. This research was funded by the South Carolina Universities Research and Education Foundation (Project #9562). Editor's note: Reviewers were Douglas L. Anderton, Steven Brechin, Christopher Jan Carman, Philip H. Pollack, and James L. Sadd.
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Thomson Gale Document Number:A89871951