Record Display for the EPA National Library Catalog

RECORD NUMBER: 15 OF 21

OLS Field Name OLS Field Data
Main Title Secondary Effects of Public Investments in Highways and Sewers.
CORP Author Environmental Impact Center, Inc., Newton, Mass.;Environmental Protection Agency, Washington, D.C. Office of Research and Development.;Department of Housing and Urban Development, Washington, D.C. Policy Development and Research.;Council on Environmental Quality, Washington, D.C.
Year Published 1975
Report Number EQC-317; EQC-3172deff1;
Stock Number PB-240 332
Additional Subjects Urban planning ; Highway planning ; Land use ; Site surveys ; Sewers ; Impacts ; Land development ; Environmental impacts ; Economic impacts ; Regression analysis ; Forecasting ; Minnesota ; Colorado ; Massachusetts ; District of Columbia ; Sewage treatment plants ; Social impacts ; Boston(Massachusetts) ; Denver(Colorado) ; Minneapolis(Minnesota) ; Saint Paul(Minnesota) ; Washington Metropolitan Area
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB-240 332 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. 06/23/1988
Collation 150p
Abstract
Statistical correlations between the amount and form of land use changes and the location of new highways and wastewater facilities were established for four major metropolitan areas individually and in combination. The statistical findings were supplemented with results from a dynamic simulation model of land use in metropolitan Washington. The analyses identified factors which seemed to explain much of the variation in location and type of development in all four regions: availability of sewer service, proximity of an area to major highways, amount of vacant land, and residential vacancy rate. However, the relative importance of each factor varied from one region to another so that although results from pooled data were acceptable in terms of their aggregate statistical significance, the set of regression equations developed from pooled data cannot be expected to produce accurate predictions in all regions.