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Whereas proximity studies will shed light on the issue of disparate impact, they may not be able to address discriminatory intent. Future studies will be needed to answer the ancient question of which came first -- did policy makers choose to locate public housing projects in areas close to existing or abandoned hazardous waste generators, or did new waste generators move into areas with existing public housing, causing residents of the public housing or surrounding areas who place a high value on the environment to leave the community, leaving behind the residents who lack the resources to purchase a high level of environmental amenities (Hamilton, 1995)? Researchers in St. Louis, Missouri (Lambert and Boerner, 1995) looked at the demographics of communities prior to siting of waste facilities and determined that facilities were more likely to be sited in non-minority neighborhoods. They conclude that instead of polluting facilities following the poor and minorities, the poor and minorities followed the low-cost housing created by the siting of waste generators while higher-income people and non-minorities tended to leave the area.
1. Convert data from CERCLIS and HUD tapes to Arc/Info
a. Write and run SAS programs to
1. read data in CERCLIS tape and in HUD's 951-file
2. define items by a descriptive name; specify starting
point and length of character field for each item
3. eliminate records with missing latitude or longitude
coordinates, or with coordinates outside the
lat/long grid range (e.g. latitude greater
than 90 degrees)
4. convert lat/long coordinates from degree-minute-second
format to decimal degrees, and make longitude
negative (for western hemisphere)
5. assign a consecutive number to each record; item
is called "id"
6. output data to two files:
a. ascii file containing only the consecutive
number, longitude (x-coordinate) and
latitude (y coord)
b. database file containing consecutive number
and all attribute data of interest
(e.g. EPA (or HUD)-ID, name, street,
city, county, state, smsa, zip, site
category, NPL status, etc.)
7. confirm accuracy of file generation and validity of
data - look at sas.log and data contained in
both output files.
b. Generate point coverage in ARC from ascii files, and build
point topology. Confirm creation of point
attribute tables (.pat)
(ARC commands GENERATE, BUILD, ITEMS, LIST)
c. Convert the database file to an INFO attribute table and
confirm creation.
(ARC commands DBASEINFO, ITEMS, LIST)
2. Define the projection and confirm
(ARC commands PROJECTDEFINE, DESCRIBE)
3. Add an item to the .pat for each coverage with the same characterics
as item "id" in the info tables, and assign the same value as
in cover-id. Join the INFO tables to the .pat for each coverage
using the common value "id".
(ARC commands ADDITEM, CALCULATE, JOINITEM
4. Locate base maps and project the coverages to the base map projection.
(ARC command PROJECT)
5. Write AML's to display CERCLIS and PUBLIC HOUSING PROJECT point
coverages on basemaps for the USA, Texas, and D/FW CMSA.
6. Calculate distance from each public housing site to toxic waste sites
within 1 mi. Will get an infofile with distances in units of the
projection. Add an item to distance called "id" for the public
housing consecutive number.
(ARC command POINTDISTANCE, ADDITEM)
7. Select public housing sites within specific distances. Since the
distance infofile contains distances to all toxic waste sites
within 1 mile there is a one-to-many relationship. A traditional
relate cannot handle one-to-many relationships; need to treat the
distance infofile as a keyfile
(ARCPLOT command RESELECT keyfile INFO {logical expression})
where the logical expression is a distance criteria (distance<= 402),
(ARCPLOT: RES KEYFILE
Clear the selection, and repeat for successive distances.
8. Write AML's to display public housing projects within specified distances
to toxic waste sites, calculate the number of sites and percentage
at each distance and place information in the legend key.
9. Convert the family data database file into an INFO table and create a
second abbreviated infofile containing the racial composition data.
(ARC commands DBASEINFO, RESELECT, INFOFILE).
10. Create a relate from the infofile to public housing project point
attribute table.
(ARCPLOT commands RELATE ADD, RELATE SAVE)
11. Determine percent minority composition of housing projects within 1
mile of toxic waste sites and outside that distance. Start by
adding an item to public.pat which contains a 1 for within 1 mi
of a toxic facility or 0 if outside that 1 mile radius.
(ARC command ADDITEM, ARCPLOT commands RESELECT, CALCULATE)
Then restore the family data relate to the public.pat, and reselect
the public housing points where the distance equals 1 and meeting
minority occupation standards, e.g.
(ARCPLOT: res pubalb point mitotoxic eq 1 and famdata//min < 25)
12. Write AML's to display public housing projects within 1 mi of
toxic waste sites, showing the racial composition of those sites.
Place site number and percentage information in the legend key.
13. Repeat steps 11 and 12 above, except showing the racial composition of
public housing sites outside a 1 mile radius of toxic waste sites,
(ARCPLOT: res pubalb point mitotoxic ne 1 and famdata//min < 25)
14. Create eps output files from all AML's
15. Convert .eps files to .gif
(Unix programs: pstopnm and ppmtogif)
16. Move .gifs to public_html directory, change permissions
(Unix commands cp, chmod 755 *.*)
17. Write project description in html on web; include gifs.
Within 1 Mile Radius Outside 1 Mile Radius Less than 25% minority: 27.4% 30.9% 25 to 50% minority: 8.9 9.8 50 to 75% minority: 10.7 10.2 Greater than 75% minority: 53.0 49.1The data reflect only a slight national tendency for public housing projects with a high minority population to be located within 1 mile of toxic waste sites. The difference (3-4%) is not significant.
Within 1 Mile Radius Outside 1 Mile Radius Less than 25% minority: 8.3% 19.0% 25 to 50% minority: 2.0 10.8 50 to 75% minority: 17.1 13.4 Greater than 75% minority: 72.6 56.8The data reflect a tendency for public housing projects with high minority populations to be located within 1 mile of toxic waste sites compared to public housing outside that radius for the state of Texas.
The analyses completed for this project are just a taste of what can be done within Arc/Info with the toxic waste site, public housing project, family data for public housing, and census data. Data for the entire USA was examined, as well as for Texas and 9 counties comprising the Dallas/Fort Worth CMSA. Any city, state, smsa, EPA region, congressional district, etc. can be looked at individually and compared to any other sector. In addition, family data such as average gross income could be examined.
Glickman, T.S., 1994, Measuring Environmental Equity with Geographical Information Systems. Resources for the Future, No. 116, p. 2-6. Hamilton, J.T., 1995, Testing for Environmental Racism: Prejudice, Profits, Political Power? Journal of Policy Analysis and Management, v. 14, p. 107-132. Lambert, T. and Boerner, C., 1995, Environmental Inequity: Economic Causes, Economic Solutions. Center for the Study of American Business, Washington University, policy study no. 125, pp 38.
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