EPA 600/5 75-003
March 1975
                      Socioeconomic Environmental Studies Series
  Land  Use  Forms and the Environment
         - An Executive Summary
                               Office of Research and Development
                               U.S. Environmental Protection Agency
                               Washington, D.C. 20460

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                          RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, Environmental
Protection Agency, have been grouped into five series.  These five broad
categories were established to facilitate further development and appli-
cation of environmental technology.  Elimination of traditional grouping
was consciously planned to foster technology transfer and a maximum inter-
face in related fields.  The five series are:

     1.  Environmental Health Effects Research
     2.  Environmental Protection Technology
     3.  Ecological Research
     4.  Environmental Monitoring
     5.  Socioeconomic Environmental Studies

This report has been assigned to the SOCIOECONOMIC ENVIRONMENTAL STUDIES
series.  This series includes research  on environmental management,
economic analysis, ecological impacts,  comprehensive planning and fore-
casting and analysis methodologies.  Included are tools for determining
varying impacts of alternative policies, analyses of environmental plan-
ning techniques at the regional, state  and local levels, and approaches
to measuring environmental quality perceptions, as well as analysis of
ecological and economic impacts of environmental protection measures.
Such topics as urban form, industrial mix, growth policies, control and
organizational structure are discussed  in terms of optimal environmental
performance.  These interdisciplinary studies and systems analyses are
presented in forms varying from quantitative relational analyses to manage-
ment and policy-oriented reports.
                               EPA REVIEW NOTICE
This report has been  reviewed  by  the  Office  of Research and Development,
EPA, and approved  for publication.  Approval does not  signify that the
contents necessarily  reflect the  views  and policies  of the Environmental
Protection Agency, nor  does mention of  trade names or  commercial products
constitute endorsement  or  recommendation  for use.

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                                               EPA-600/5-75-003
                                               March 1975
             Land Use Forms

           and the Environment


          An Executive Summary
                   by

            Brian J. L. Berry
            Grant No. 801419
         Program Element 1HA098
          Roap/Task 21 AKL 02
             Project Officer

         Dr. Philip D. Patterson
Washington Environmental Research Center
         Washington, D.C.  20460
              Prepared for
   OFFICE OF RESEARCH AND DEVELOPMENT
  U.S. ENVIRONMENTAL PROTECTION AGENCY
        WASHINGTON, D.C.  20460

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                           CONTENTS

                                                            Page

I      CONCLUSIONS                                             1

II.   BACKGROUND                                              2

III.  CONCEPTS                                                6

IV.   THE GROUPING OF METROPOLITAN AREAS                    11
      A.  The Sorting Table
      B.  Pollution Data Used in the Grouping
      C.  Factor Analysis of the Pollution Data
      D.  The City Characteristics

V.    INTER-METROPOLITAN ANALYSES                           20
      A.  Findings Related to Property Values
      B.  Findings Related to Land Use Relationships
      C.  Comparison with Intra-Metropolitan
             Property Value Studies

VI.   INTRA-METROPOLITAN ANALYSES                           33
      A.  Sample Density Relations

VII.  SUMMARY                                               35
                              ii

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                      ACKNOWLEDGMENTS
This executive summary of the final  report of Grant 8D1419, which
was sponsored by The Washington Environment Research Center,
Office of Research and Development,  U.  S.  Environmental  Protection
Agency, was completed by members of  the Department  of Geography
and Center for Urban Studies, University of Chicago.  The  project
director was Brian J. L. Berry and the  EPA project  officer was
Philip D. Patterson.
                               ill

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                        I.   CONCLUSIONS
     The relationships between the size and economic functions  of
metropolitan regions, the income levels of their residents,  and the
nature and intensity of environmental  pollution have been documented
and clarified in a number of recent studies.   The most important
finding of the study summarized here is that — in 1970,  metropolitan
regions of similar sizes, economic functions and income levels  had
different urban forms; that as urban form varied, so did  the urban
land use pattern; and that as land use varied, so did environmental
pollution.  In particular, it was concluded that high-density,  con-
centrated, core-oriented urban regions had superior air and  water
quality to sprawling, dispersed urban regions of similar  size and
economTc functions.

     This conclusion is important, because urban form is  itself
determined by the modal mix of transportation and the location  of
transport routes, employment complexes, airports and open spaces,
and each of these is to some extent controllable by land  use planning.
Thus, to the extent that variations in urban form produce variations
in environmental pollution, land use planning becomes a positive in-
strument for achieving environmental quality goats.

     A second conclusion points to the difficulties of this  task,
however.  Many economists agree that property values measure the net
benefits expected to flow over the useful life of an investment in
a particular land use, taking into account both the economies de-
rived from urban agglomerations and the environmental and social
costs of urban life.  Following this logic, the aggregate property
values of metropolitan regions, should therefore reflect  the total
stream of benefits expected to flow from the land uses within each
region.  The research summarized here concluded that aggregate  pro-
perty values, as expected, increase with city size and with  income
levels and decrease with the size of manufacturing concentrations.
But most importantly, the aggregate property values are greater in
more dispersed regions than they are in metropolitan areas with more
concentrated urban forms.  As measured by 1967 property values  and
1970 air pollution levels, there is therefore a conflict  between
the economically most desirable urban form (sprawl), and  the environ-
mentally most desirable form (concentration).  The urban  regions
that are emerging reflect market responses to the greater aggregate
net benefits in the more dispersed urban forms.  Decentralization
in our cities appears to be continuing apace, with the apparent con-
sequence of increasing metropolitan environmental quality problems.
Herein is the challenge to those who would formulate a national land
use policy.

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                       II.  BACKGROUND






     A few words of background are Important.  Under the provisions



of Project No. R-80H»19, "Land Use Forms and the Environment", under-



taken for the Washington Environmental Research Center, Office of



Research and Development, U.S. Environmental Protection Agency by a



research group at the University of Chicago, a voluminous final



report was submitted to EPA  in November, 1973.  This report was pub-



lished in April, 197** under  the title Land Use, Urban Form and Environ-



menta1 Qua 1?ty  (The University of Chicago:  Department of Geography



Research Paper No. 155, 1974, xxiv and 438 pages).  It was felt by



the Agency's staff that the  report was too long and too technical



for wide circulation, and so an "executive summary" was requested to



highlight the principal conclusions.  This Is that summary.



     It is important to realize what  is  summarized and what has been



excluded from the pages that follow.  When our research began  in the



summer of 1972 we searched in vain for sources—both within and out-



side EPA—to which we could  turn for  reasonably concise guides to



the nature and  sources of each type of environmental pollution, to



the measurement systems and  surveillance networks now  in use,  to the



data currently available, to the latest  information on effluent and



emission sources and amounts, to the  incidence of pollution,  to



assessments of quality  in terms of National and/or local standards,

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and to what is known about health and welfare effects of pollution,



the presumed bases of the standards.   As might have been expected,  the




search was difficult.  No agency has  the responsibility for drawing



together all that is known, although  EPA is now doing more than  most.



     Therefore, for each aspect of environmental quality we were



expected to address in our research—air, water, solid wastes,  noise,



pesticides and radiation—we culled the literature, badgered the rele-



vant organizations and agencies, and  pulled together our own summary



and assessment of current pollutant data sources and environmental



quality assessment systems.  Six chapters of the larger report,  one



for each pollutant, are devoted to these summaries.  The 250 pages



involved provide an identically-structured treatment of each pollutant,



looking in turn at measurement systems, generation information,  qua-



lity assessment, and health and welfare effects.  The person who needs



the kind of reference system and background knowledge that we found



to be lacking when we began our research should turn to the larger



report, because these background materials are not reviewed in  this



summary.



     Instead, this document focuses  on the original findings of the



research group, comprising faculty members and students in the  Depart-



ment of Geography and/or the Center for Urban Studies of the University



of Chicago.  The findings relate urban form and environmental pollution



(a) across the spectrum of U.S. metropolitan areas considered as enti-

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ties, and (b) on a more detailed basis within a sample of these

urban regions, at a point in time centering on the 1970 census year.

In both cases, the research involved painstaking data collection

and many experimental statistical analyses.  Again, the details of

this research will not be addressed in this summary; the full re-

port is the place for these.  Rather, we will highlight the results

that appear to hold most significance for public policies that affect

the  relationship between land use, urban form and environmental

quality.

     Because this is a summary, many of the bbvious caveats about

data quality, gaps in knowledge, and the like will remain unsaid.

Yet, lest there be any doubts about the matter, the research group's

findings concerning environmental data should be known at the outset:

          Collection of data on environmental quality
          is  in a developmental state at this time.
          Gaps and Inconsistencies abound.  The nation's
          environmental data banks either use the avail-
          able monitoring networks selectively and
          incompletely or assemble all available data,
          regardless of source, completeness or quality
          into an often poorly-functioning data bank.
          In other cases (e.g., solid wastes and noise)
          comparative nationwide Information is totally
          lacking, or is at a scale that does not per-
          mit detailed investigation of the effects of
          different urban forms on environmental quality
          (e.g., pesticides and radiation).

Much effort on the environmental information side will have to be

expended before research of the kind we report here can progress

beyond the exploratory and experimental stage.  That such effort

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might be well-spent Is, however, Indicated by our results:   we do



find, subject to all the qualifications above, that different urban



forms had significant effects on environmental quality in 1970.

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                         III.  CONCEPTS






     The finding that urban form affects environmental quality is



to be understood within  the framework of a conceptual scheme that



was used to structure the  research and a body of data that was used



to test the validity of  the concepts.



     In the first part of  the study, in which entire metropolitan



areas were used as units of analysis, the conceptual scheme was de-



rived from contemporary  urban economic theory.  For purposes of the



study, such city characteristics as population size, the nature of



the urban economic base  and the income levels of the area's resi-



dents were taken as "givens," determined by the role played by the



city within the national economy.  The question was one of exactly



how urban activities are translated Into land use and how land use



relates to environmental pollution.



     Urban form, as indicated by population density patterns, the



nature of the highway network, etc., was hypothesized to play an



important role In the translation of city characteristics into land



use.  The transport network, for example, helps determine the loca-



tion of economic activities and residences, and whether the urban



region has a radial structure from a dominant central business dis-



trict, or whether It is  sprawling and multi-centered.  Whether or



not the urban structure  Is highly concentrated or dispersed deter-

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mines the land supply and, at any given level of demand for land,


whether the land Is used Intensively or extensively.  Concentration


and dispersion, in turn, both result from and help determine the


transportation patterns of the metropolitan region and along with


the size and affluence of a community are reflected in the pattern


of urban densities.


     In turn, land use was hypothesized to determine land values.


Given well-functioning markets, it is a well-established principle


of urban economics that the price of land and the capital assets


located on it will equal the present value of the future stream of


net benefits expected to flow over the useful life of the assets —


increased, as several economists have recently pointed out, by the


positive externalities derived from others, as well as being re-

                                                 *
duced by such negative externalities as pollution imposed by others.


If this Is true for each individual property within a metropolitan


area, it should also be true of the sum total for all properties


within that region:  aggregate land values should include the agglo-


meration economies of large urban complexes, and should be reduced


by such disbenefits as the costs imposed by discharge of pollutants


into the urban environment.  Further, high property values should


contribute to the comparative advantage of the urban region in the


national economy, attracting investment, while low values resulting


from higher levels of environmental pollution and/or from other ef-


fects should detract from this comparative advantage.
* To the extent that buyers and sellers of property are aware of
the actual damages caused by pollution and other externalities.

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     The overall conceptual model is depicted in Figure 1.  In

keeping with what has just been said, It postulates that urban

characteristics are the determinants of land use, with an intervening

role played by urban form  (causal influences are indicated by arrows).

Land use is seen as determining land values, but the land use pat-

tern Is, in turn, also seen to be the source of the environmental

pollution that  reduces these values.

     Consistent with this  conceptual model, the research strategy at

the metropolitan scale was to study the following:

          (i)  Environmental pollution as a function of
          land use, land use as a function of urban form
          and city characteristics, and environmental
          pollution as a function of urban form and city
          characteristics, to determine the ways in which
          urban form translates city characteristics into
          land use, and its role therefore in enhancing
          or reducing the  environmental pollution that
          results from urban size, economic base, and
          income levels.

          (ii)  Land values as a function of city charac-
          teristics, urban form and environmental pollu-
          tion, to measure the ways in which agglomeration
          economies and negative externalities  intertwine.

     At the  intra-metropolitan scale, because of serious data limita-

tions, the  research was more experimental, designed to open up  lines

of  research  inquiry.  Details of the urban land use pattern were  re-

lated  to details of the pollution map on a case-study basis following

the  logic outlined  in Figure 2,  in which the circular"relationships

between the urban  land use pattern and the pollution map are spelled
                                 8

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                                              Figure  1
                                     OVERALL CONCEPTUAL MODEL
NATIONAL
ECONOMY
  CITY  CHARACTERISTICS
                                      URBAN FORM
                                       TRANSPORT MESH
                                        LAND SUPPLY
                                      CORE ORIENTATION
                                        DISPERSION
      DEMOGRAPHIC STRUCTURE
                                       URBAN DENSITIES
                                           LEVEL
                                          PATTERN
                                                                  LAND USE
  MIX
PATTERN
INTENSITY
          LAND VALUES

            NET DISBENEFITS
          AGGREGATE BENEFITS
                                                                 ENVIRONMENTAL
                                                                    POLLUTION
                                                             TYPE
 INTENSITY
PATTERN

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      out.   Only  in  the case of  air pollution were comparisons of  several

      metropolitan areas possible on a detailed intra-metropolI tan basis.

                                      FIGURE  2

                    CONCEPTUAL  MODEL USED  IN THE FORMULATION
                           INTRA-METROPOLI TAN STUDIES
LAND  USE PATTERN
 IN URBAN REGION
  POLLUTION MAP
  OBTAINED FROM
  SURVEILLANCE
   RECEPTORS
                          RESIDUALS SOURCES
                                                    GENERATION FACTORS
RESIDUALS MEASURED
  AT RECEPTORS
  DIFFUSION.
  DISPERSION
OR TRANSPORT
                                          10

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      IV.  THE GROUPING  OF METROPOLITAN AREAS
A.   The Sorting Table

     In all, 76 metropolitan regions  were  studied.   The  Standard

Metropolitan Statistical  Area (SMSA), as defined  by  the  Office of

Management and Budget, was used as  the unit  of  analysis.  These

regions, whose locations  are shown  in Figure 3, are  as follows:
          Akron
          Albuquerque
          Al1 entown-Bethe 1 em-Easton
          Atlanta
          Baltimore
          Bi rmingham
          Boston
          Bridgeport
          Buffalo
          Canton
          Charleston, W.  Va.
          Chattanooga
          Chicago
          Cincinnati
          Cleveland
          Columbus, Ohio
          Da 11 as
          Dayton
          Denver
          Des Moines
          Detroit
          El Paso
          Flint
          Fort Worth
          Gary-Hammond-East Chicago
          Grand Rapids
          Hartford
          Honolulu
          Houston
          Indianapolis
          Jacksonv!1le
          Jersey City
          Johnstown
          Kansas City
          Los Angeles-Long Beach
          Louisville
          Memph i s
          Miami
MiIwaukee
Minneapolis-St. Paul
Nashvi1le-Davidson
New Haven
New Orleans
New York
Newa rk
Norfolk-Portsmouth
Oklahoma City
Omaha
Paterson-Cli fton-Passaic
Philadelphia
Phoenix
Pittsburgh
Portland, 0.
Provi dence-Pawtucket-Warwi ck
Reading
Richmond
Rochester, N.Y.
St. Louis
Salt Lake City
San Antonio
San Bernadino-Riverside-Ontario
San Diego
San Francisco-Oakland
San Jose
Seattle-Everett
Syracuse
Tampa-St. Petersburg
Toledo
Tulsa
Utica-Rome
Washington, D.C.
Wichita
Wi Imington
Worcester
York
Youngs town-Wa r ren
                                11

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ro
            LOS ANGELES
                    Representative metropo-
                    litan areas selected  for
                    use In intra-metropolltan
                    analysis
                                          0   100 200
                                            milts
FIGURE 3
                                 METROPOLITAN  AREAS USED IN THE INTER-METROPOLITAN ANALYSIS

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     The first task completed in the project was to group these



SMSA's Into subsets on the basis of their pollution characteristics,



so that the environmental dissimilarity among the subsets was  maximized



and the environmental dissimilarity among the SMSA's within each sub-



set was minimized.  The subsets then were used to prepare a "sorting



table" that showed how each SMSA fitted into the nationwide spectrum



of variations in urban environmental pollution.



     Table 1 summarizes thi's sorting table and Table 2 shows how the



groups of SMSA's differ in terms of several key urban indicators.



Some clear contrasts are evident between those groups of cities with



high levels of air pollution, for example, and those with poor water



quality.



     The classification of the SMSA's into relatively homogeneous



subsets on the basis of their pollution characteristics was undertaken



for several reasons.  One, as noted, was to learn more about nation-



wide variations in urban environmental quality.   Another was to faci-



litate acquisition of more detailed local data on a sampling basis,



with some guarantee that the sample of SMSA's selected would span



the universe of pollution types.  The SMSA's underlined in Tables  1



and 2 and shown by large dots in Figure 1, are those which were se-



lected as representative of these groups.  It was for these SMSA's



that detailed metropolitan land use data were derived to be used in




the later analysis.






                                 13

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                                                                             TABLE  1
                                                          THE  ENVIRONMENTAL  SORTING TABLE
                                                                             GROUP OF CITIES
                        Baltimore
                        Buffalo
                        Indianapolis
                        Lo« Angeles
                        M««mnaton D.
ENVIRONMENTAL QUALITY
  INDICATORS!

1.  Water
     Dissolved oxygen
     Dissolved solids
     Nitrates
     Average WO. Index

2.  Air
     Average SOi
     Average TSP
     Average AQ Index
     Average EV Index

3.  Sol Id Wastes
     Generated by In-
       dividual mul-
       tipliers

k.  Noise
      Tr° travel Index
   ^_^                 Birmingham
Milwaukee    Allentown- Charleston
Minneapolis  Bethlehem  Chattanooga
Philadelphia Canton     Dayton
Pittsburgh   Rochester  Des Koines
Pprtland     Yonngatown Qary-
St. Louis    York       Hammond
                        Johnstown
                        Nashville
                        Omaha
                        Reeding
                        Otica-Rome
                        Worcester
Bridgeport
Cleveland
Hartford
New Haven
Newark
providence
Flint        Cjinoinnati    Atlanta
Grand Rapids Jersey City . Boston
SSSonvllle) Kansas City  Columbus
Lpuisville   San Bernadino Delias
Honolulu Albuquerque
HMphis  El.Paso
                                                                                                                                                    Denver
                                                                                                                                                    Salt L
                                                       Lake City
Norfolk
Patterson
Richmond
Toledo
Syracuse
Wilmington
7.2
865
3
5.1
34
115
3.2
9.7
5.897
170
8.0
211
5
1.2
49
117
3.4
8.4
6,737
228
5.3
820
16
2.8
38
106
2.7
5.9
1,440
194
7.8
353
3
1.6
25
119
3.2
10.6
999
36
7.1
95
4
2.1
51
84
2.7
4.2
2,482
99
7.9
407
3
2.2
20
82
2.1
2.2
1,434
34
7.0
4765
8
4.5
22
104
2.9
5.0
1,940
66
6
44'
]
3
2
3
4,5
1
Detroit
Fort Worth
Houston
Miami
New Orleans
New York
San Antonio
San Diego
San Francisco
San Jose

Taapa-8t. Petersburg
                                               19
         Phoenix
         Tulsa
         Nichita
                                               19
                                               85
                                              2.3
                                              3.5
                                              152
                                 16
                                 61
                                2.3
                                2.3
                                                      1,174


                                                        114
                                            4.9
                                          1,894
                                             16
                                            2.3
                                                           9
                                                          84
                                                         2.1
                                                         3.4
                                            984


                                             46
                                                                      445
                                                                       11
                                                                      1.3
                               1}
                               82
                              2.2
                              1.1
                                                                    1,564


                                                                      110

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                                                                                   TABLE  2
                                                                        KEY URBAN  INDICATORS
                                                                                  GROUP OF CITIES
URBAN  CHARACTER! VICSI

Population (In thousands)
Percent employed  In
  manufacturing.
Median fi»ml ly Income
  (In  thousands)
Urban  property values
  (billions)

URBAN  FORM INDICATORS:

Central density (sample
  city)
Density gradient  (sample
  city)
Radial highways
Circumferential highways
Open Space Percent
Baltimore
Buffalo
Indianapolis
Los Angeles
Washington D.C










Chicago
Milwaukee
Minneapolis
Philadelphia
Pittsburgh
Portland
St. Louia
Akron
Allen town -
Bethlehem
Canton
Rochester
Youngstown
York
Birmingham
Charleston
Chattanooga
Dayton
Dec Koine*
Gary-
Hammond
Johnstown
Nashville
Omaha
Reading
Otlca-Rome
Worcester
Bridgeport Flint
Cleveland Grand Raplda
Hartford Jacksonville
New Haven Louisville
Newark Norfolk
Providence Patterson
Richmond
Toledo
Cincinnati
Jersey City
Kansas City
San Bernadino
Syracuse
Wilmington
Atlanta
Boston
Columbus
Dallas
Detroit
Port Worth
Houston
Miami
New Orleans
New York
San Antonio
San Diego
San Francisco
San Jose
Seattle
Honolulu Albuquerque
Memphis El Paso
Oklahoma city
Phoenix
Tulsa
Hichita
Denver
Salt Lake City
Tampa-st. Petersburg
2,285
24.2
11.1
25.2
17,000
-.168
10.6
3.0
71.1
2,969
29.8
10.9
18.5
36,022
-.1281
10.9
2.7
70.7
557
43.9
10.6
3.4
10,931
-.3244
5.0
2.5
78.5
448
32.5
9.7
3.1
7,216
-.23*45
5.4
1.5
67.3
1,040
34.0
11.4
10.3
11,867
-.2687
7.5
1.6
81.6
705
29.4
10.3
4.7
.
_
6.6
1.7
82.1
921
30.3
10.2
8.5
10,558
-.1543
7.5
1.8
84.1
2,267
22.0
10.4
18.8
15,500
-.107
8.3
2.4
73.0
700 525
14.7 19.9
10.3 9.1
4.1 3.4
4,322
-.1714
5.5 4.0
2.0 3.0
84.6
893
16.4
10.4
6.6
10,198
-.1498
7.0
1.5
83.8

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B.   Pollution Data Used in the Grouping

     The environmental variables used to derive the groups of cities

shown in the sorting table were as follows:

     AIR POLLUTANTS  (data for 73 SMSA's)

        Sulfur Dioxide                  (a) Annual Mean Concentration
            (S02)                            (yg/m3)
                                        (b) Annual Maximum Concentration
                                            (yg/m3)
        Total Suspended Partlculates    (a) Annual Mean Concentration
            (TSP)                            (yg/m3)
                                        (b) Annual Maximum Concentration
                                            (yg/m3)

     DERIVED AIR QUALITY  INDEXES  (Source:  The Mitre  Corporation)

       Mitre Air Quality  Index  (data  for 6? SMSA's)

           (a) S02               index  numbers
           (b) TSP               index  numbers
           (c) N02               index  numbers
           (d) All Pollutants    index  numbers

       Extreme Value  Index  (data for  59 SMSA's)

           (a) S0£               index  numbers
           (b) TSP               Index  numbers
           (c) All Pollutants    index  numbers

     WATER QUALITY PARAMETERS  (data for M  SMSA's)

           Temperature                 Degrees Fahrenheit
           Color                       Platinum-Cobalt Units
           Turbidity                   Jackson Turbidity Units
           pH                          p" values
           Fecal Coliform  Bacteria     MPN/100 ml.
           Total Dissolved Solid       ppm  (residue at 180° C.)
           Suspended  Solids            Parts per million
           Total Nitrogen              Parts per million
           Alkalinity                  Parts per million  (as  CaC)
           Hardness                    Parts per million  (Ca, Mg)
           Chlorides                   Parts per million
           Total Iron and Manganese    Parts per million
           Sulfate                     Parts per million
           Dissolved Oxygen            Parts per million
                                     16

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     DERIVED WATER QUALITY INDEXES (data for 44 SMSA's)

         Water Quality Index, Drinking Use              index numbers
         Water Quality Index, Recreation Use            index numbers
         Water Quality Index, Industrial Use            index numbers
         Mean Water Quality Index (averages of above 3)  index numbers

     SOLID WASTE ESTIMATES (data for 76 SMSA's)

         Total Calculated from Simple
            Generation Rate                            1,000's tons/year

         Total Calculated from Separate
            Source Unit Estimators                     1,000's tons/year

         Same as second above, omitting manufacturing  1,000's tons/year

     NOISE—SURROGATE INDICATORS (data for 76 SMSA's)

         Automobile Traffic Volume     Number of workers
                                          using private  automobiles
                                          to commuted to work, SMSA
         Air Traffic Volume            Number of scheduled aircraft
                                          arrivals and departures, SMSA

C.   Factor Analysis of the Pollution Data

     As noted, the above data were subjected to a factor analysis,

the purpose of which was to group the 76 SMSA's into subsets in such

a manner that the dissimilarity among the subsets is maximized and

the dissimilarity among SMSA's within the subsets is minimized.

     Factor analysis is a complex mathematical procedure that cannot

be undertaken without a large computer.  In the application here it

was used to explore the similarities and differences among the SMSA's,

simultaneously considering the 34 pollution variables listed above.

The result of the analysis was to determine that the 76  SMSA's should

be classified into the eleven groups shown in the sorting table.
                                 17

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D.   The Urban Characteristics

     In addition to the pollution data, a set of ci^y characteristics

also was assembled to be used in the subsequent investigation, viz:

                 CITY CHARACTERISTICS  (76 SMSA's)

     1970     Central City Population       1000's
              SMSA Population               1000's
              Central City Density          Pop./square mile
              SMSA Density                  Pop./square mile
     1960-70  Population Change, CITY       percent
              Population Change, SMSA       percent
     1970     Median Age of Population,
                 City                       years of age
              Median Age of Population,
                 SMSA                       years of age
              Median Family Income          $
              Percent of Labor Force
                 Employed in Manufacturing  percent
              Land Area, City               square miles
     1967     Total Value of Real Estate,
                 SMSA                       $l,000,000's

                 URBAN FORM INDICATORS  (76 SMSA's)

     Degrees of Arc of SMSA around CBD      0° to 360°
     Density Ratio                           (SMSA density/city density)
     Transportation Radials, SMSA           number
     Transportation Circumferentials,  SMSA  number

Finally, after the factor analysis had  provided a pollution-sensitive

classification of the SMSA's, a sample  of 13 cases was selected, with one

from each of the groups, both to enable preparation of metropolitan land-

use estimates and to limit the scope of the subsequent Intra-metro-

politan analysis.  The land use variables collected were as follows:
                                  18

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        SMSA LAND USE (13 representative SMSA's)

Residential                       Percentage of total area
Commercial                        Percentage of total area
Industrial                        Percentage of total area
Extractive                        Percentage of total area
Public and Semi pub He             Percentage of total area
Transportation, Communications,
   Utilities (TCU)                Percentage of total area
Open Space                        Percentage of total area
                            19

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             V.  INTER-METROPOLITAN ANALYSIS






A.   Findings Related to Property Values



     One stage In the analysis Involved an examination  of  the  relation-



ships between the total value of property In each of the 76  metropo-



litan areas, the size and other characteristics of the  SMSA's,  the



agglomeration economies accompanying concentration of activity  in these



urban areas, and the negative externalities of growth,  including



environmental pollution.



     It is pointed out in the existing literature of urban economics



that the net benefits of urban life should, first of all,  vary  directly



with the size of the metropolis.  The larger the city,  the greater



the size of market that can be reached, the greater the access  to



information about new products and processes, the better the access



to a wide range of specialized suppliers, and the easier it  is  to



recruit and  retain a specialized workforce.  In industries marked by



uncertain and fluctuating demands, there are advantages in being



located in a city where specialized inputs can be obtained quickly.



For households, there are advantages of a larger range  of  potential



employment opportunities, varied and specialized sources of  consumer



goods and services, and access to those cultural activities  that are



available only in the  larger cities.  Such benefits should become



manifest through improved productivity* and a resulting stream of net



benefits that therefore increases directly with city size.
                                 20

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     Another well-established principle in economics is that,  given



well-functioning markets, the price of any capital  asset will  equal



the present value of the anticipated future stream of net benefits



over the useful life of the asset.  Thus,  summing over the properties



within any metropolitan area, aggregate property values should pro-



vide a first approximation of the stream of net benefits expected to



accrue to land users within that area, and a means of estimating the



effects of economics of agglomeration on those benefits.  In other



words, the market for land and property within urban areas should



capture and express the net benefits of urban growth and size.



     If this is so, then one question that arises is whether,  if



urban form affects land use, the stream of net benefits varies with



differences in urban form.  Urban planners frequently argue, for



example, that disorderly urban sprawl destroys property values.  A



second question is whether these benefits are reduced by environmental



pollution.  Both economies and diseconomies of agglomeration will



come into play with increasing metropolitan size.  New activities pro-



vide additional opportunities for specialization or integration of



activities or improved quality of information.  These can be either



pecuniary or physical external economies in production or consumption.



If there are scale economies in provision of public services,  addi-




tional population gives rise to decreasing average costs of services,



which will result in a higher quality of services per tax dollar.
                                 21

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At the same time, diseconomies of agglomeration will result from con-

gestion and pollution, or from decreasing returns to scale In the

public service sector.

     A series of empirically-testable propositions arise from the

foregoing:

     (1)  Aggregate property values and total population
          should move systematically together, In the
          absence of net economies or diseconomies of
          agglomeration, in a linear fashion.

     (2)  If there are net economies of agglomeration
          over some size range, property values should
          Increase more than proportionally with popu-
          lation.

     (3)  With net diseconomies, property values should
          increase less than proportionally with popu-
          lation, and if diseconomies become suffici-
          ently severe, property values should actually
          decline as population increases.

     (4)  If there are increasing returns to city size,
          followed by decreasing returns, aggregate
          property values should Increase In an S-shaped
          logistic pattern with respect to population,
          and it should then be possible to identify
          that point at which average land value per
          person Is maximized, the population size which
          Is optimal in an economic sense for all cities
          In the system In the long run, as well as
          that point (the lower inflection point) at which
          the marginal increment In land value from an
          incremental change in population Is maximized.
          This latter point Is that size at which the
          marginal contribution of population to land
          values is largest In the short run.

     (5)  To the extent that manufacturing concentrations
          increase environmental pollution and environ-
          mental quality Is better in higher-Income com-
          munities, these variables should account for a
          significant portion of the variance from  (1).
                                 22

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     (6)  If the dispersed ctty, holding constant city
          characteristics, produces a land use mix deliv-
          ering lower environmental quality, this should
          be reflected in appropriate statistically-sig-
          nificant partial relationships of urban form
          and aggregate land values.

     In testing these propositions, the dependent variable, total

property values, was derived from assessment data In the 196?

Census of Governments, with adjustments made to the market value

using the assessment ratios in that publication.  The independent

variables that were used are those listed in the previous section.

Figure k plots the observed property values against metropolitan

population.  Our interest centered, first, on the shape of this

relationship, and-then on the sources of variability including the

possible contributions of urban form and environmental pollution to

the variance.
                              23

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                        FIGURE k
             AGGREGATE PROPERTY VALUES RELATED
                   TO SMSA POPULATION
 100
  50
  10
               0.5
1                       5

LOG POPULATION (IN MILLIONS)
10
Source of  Data:   1967 Census  of Government  and
                    1970 Census -of Population
                           24

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     After completing many multiple regression analyses  the following

findings emerged:  aggregate property values and metropolitan size

increase in a highly correlated manner (elasticity* in the range 0.85

to 0.89), but are depressed by manufacturing concentrations (elasti-

city -0.37 to -0.45) and assume much higher levels  in higher-income

cities (elasticity 2.14 to 2.33).   Some economists  believe that to

the extent that median incomes reflect real-wage differentials, they

are the necessary "bribes" that must be-paid to attract  and retain
                                                                  »

the urban labor force in congested, polluted, inadequately serviced,

dangerous, and impersonal large cities.  However, our results belie

this supposition; environmental quality was found to be  much better

in higher-income cities than In lower-Income cities.

     There were some negative conclusions, too.  In particular, none

of the variables used to index levels of environmental pollution was

statistically significant in any of the regression  models.  Apparently,

once the effects of population size, manufacturing  concentrations and

income levels had been taken into account, the main sources of varia-

tion in overall levels of environmental pollution also had been ac-

counted for I

     Separate studies were made of different size-classes of cities,

and even within size classes, city size remained an important deter-
  Elasticity is the percent change in the dependent variable resulting
from a 1 percent change in the Independent variable.  For example^ in
this case, an elasticity of .85 means that aggregate property values
go up .85 percent for every one percent Increase in metropo11 tan\popu-
lation.                                                          \
                                  25

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mlnant of property values, and manufacturing concentrations continued



to depress them.  The most complex analyses explored whether the



relationship between property values and city size was straight-line



or S-shaped.  The latter was found to be the case.  Net agglomeration



economies were found to be present In urban regions up to a size of



2.5 millions, with maximum property values per capita In urban regions



of around 1 million people.  However, progressively greater net dis-



economies of size were found to take their toll In metropolitan



regions between 2.5 millions and 6.0 millions In size.  But Increasing



returns were found thereafter in the largest urban regions.  Reiter-



ating earlier conclusions, variables representing levels of environ-



mental pollution added no explanation to this most complex model not



already provided by size, economic base and income levels.  This means



that the effects of pollution, congestion and crime on the quality of



urban life show up (a) in the fact that the elasticity of property



values with respect to population size is less than one (property



values increase less rapidly than population; (b) in the fact that



the coefficient attached to manufacturing concentrations Is negative



(more manufacturing activity depresses property values), and (c) that



there is a self-selectivity reflected in the positive large relation-



ship of property values to Income levels.



     There were, though, some significant relationships of property



values to the urban form variables.  In particular, aggregate property
                                 26

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values were found to be greater In lower-density (dispersed) urban



regions than in high-density (concentrated) urban centers.  The rapid




continuing decentralization of American urban regions is consistent



with adjustments to urban form in response to these net benefits of



dispersion, thus confirming the thrust of the statistical conclusions.



B.   Findings Related to Land Use Relationships



     Regression models also were formulated and tested, using the



smaller sample set of 13 SMSA's, to determine, firstly, the relation-



ships between land use, city characteristics and urban form, and



secondly the relationships between environmental pollution and land use.



     In the first case, each land use type was initially regressed



on such city characteristics as size, manufacturing concentrations,



etc., and then on these variables plus the urban form indicators.  In



all cases except two, the amount of variation in the land use variable



explained by the equation more than doubled when the urban form indi-



cators were included in the equations, indicating that urban form



plays a significant role in translating city characteristics Into



land use.  The exceptions are industrial  land use and transport-com-




munication-utilities (TCU).  In economic models, it is commonly assumed



that industrial location is determined by the role played by a city



in the national economy, and that TCU represents a key instrument



variable that may be used to shape land use, and the results of the



analyses certainly seemed to confirm this supposition that industry
                                27

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and transportation are determinants of urban structure rather than

being determined by It.

     As for the other land uses, the Important Intervening role of

urban form In determining the urban land use mix was clear.  For

example, the percentage of land used for residential purposes was

found to vary in the following ways:  directly with SMSA population,

with a  1.0 percent change in population producing an 0.6 percent

change  in the residential percentage; inversely with income levels;

and positively with manufacturing employment.  The less-than-proporr-

tionate rate of increase of residential land use with city size is

commensurate with the fact that city area also increases at a slower

rate than urban population, producing increased residential densities,

and was borne out by an  inverse relationship found to exist between

the residential percentage and the density  ratio:  the percentage of

residential land increases as the density ratio falls.  Because the

density ratio falls when central city densities are high relative to

SMSA densities  (i.e., a situation in which  the population density

gradient* is  relatively steep and the population of the urban area is

core-oriented), higher central city densities produce more intensive

land use and  a  relatively lower residential percentage.
*  The density  gradient  charts  the  rate of  decline of densities with
increasing  distance  from the  city center.   A  steep gradient  indicates
that densities  drop  very quickly; a shallow gradient  indicates a much
more uniform  population  density pattern.
                                   28

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     The greatest elasticity of residential land use was found to be



with respect to median incomes; a 1.0 percent increase in incomes was



associated with a 2.1 percentage point decrease in residential land



use.  The compensating factor apparently was open space:  another



equation showed that the greater the median income of a community,



the greater the open space, commensurate with national attitudes



regarding the quality of life.



     The intervening role of the three urban form variables revealed



the specific mechanics by which city characteristics are translated



into land use.  A positive relationship was found between the residen-



tial percentage and the "degrees of arc" covered by a city.  The



higher the degrees of arc, (i.e., the greater the approximation of



the city to a full circle around its center), the more area is avail-



able for residential development, and the more extensive is land use.



On the other hand, residential land use varies inversely with the



number of radial highways.  Planners have advocated the use of a



radial urban design to cut down on urban sprawl.  By concentrating



development along the radials or "fingers," and restricting the uses



of the "wedges" between these fingers, according to the argument, land



development might be confined to the easily accessible areas, occurring



at higher density and leaving more open space.  The inverse relation-



ship shown here supports this argument, as does the positive relation-



ship between the residential percentage and the number of circumferential



highways.  An Increased number of circumferentials promotes residen-



tial sprawl.
                                 29

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     What, then, are the mechanics of these urban form relationships



that have been suggested?  What is indicated is that the demand for



urban land is determined by the role that the city plays in the



national economy.  From such relationships arise the industry mix,



growth rate, size, and income levels of the urban region.  Urban form



controls the supply of land of each access type available for develop-



ment.  The greatest supply of land is delivered by a circular urban



region with many circumferential highway rings; such supply conditions



produce residential sprawl.  On the other hand a radially-structured



urban region on a  restricted site has higher residential densities, a



steeper density gradient, a lower residential land use percentage,



and more open space.



     Similar relationships exist for the other land uses.  The com-



mercial and extractive percentages increase with city size, are lower



where the density  gradient is steep, decrease with community income



levels, and increase in manufacturing cities.  They Increase as the



urban form approaches circularity, decrease in a radial structure and



increase with the  number of circumferentials.



     Conversely, open space decreases with city size, manufacturing



concentrations, and circumferential structure, increases with income



levels, where the  density gradient Is steep, and with the number of



radials, and — the only surprise — decreases as the degrees of arc



Increase.  But a moment's reflection eliminates even that surprise.
                                30

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Departures from circularity are usually environmentally-determined by

lakes and seashore, rivers and mountains, and where such environmental

amenities exist, there has been effort to preserve them as open space.

     The final step in this phase of the analysis was to relate environ-

mental pollution to land use.  Each of the air and water quality vari-

ables was regressed directly on the city characteristics and indicators

of urban form, with very mixed results.  When, however, these same

variables were related to the land use variables instead, highly signi-

ficant results emerged, thus confirming the general logic of the con-

ceptual sequence diagrammed in Figure 1.  Apparently, urban forms are

expressed in environmental pollution through the intervening role of

land use, just as urban form, in turn, translates city characteristics

into land use.  Basically, size, manufacturing concentrations and low

incomes, combined with urban configurations that permit extensive

sprawl, produce land use mixes that have associated with them the

greatest environmental pollution.

C.   Comparison with Intra-Metropolltan
     Property Value Studies

     One question about the foregoing macro-scale conclusions (i.e.

findings related to metropolitan regions as a whole) is how they

relate to micro-scale conclusions about the effects of environmental

pollution on property values.  For samples of individual properties

within particular cities, many recent investigators have found that
                                31

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property values decline as environmental pollution increases.  Why



should this fact not be reflected at the macro-scale of the foregoing



inquiry?  The answer is that the individual effects are present in



all cities, varying in the magnitude of their incidence with city size,



with the scale of manufacturing concentrations, and with income levels.



They are thus accounted for by these latter variables in the macro-



scale equations, which say that when the size-, manufacturing- and



income-related compoaents of overall environmental pollution have been



accounted  for, there are no additional  relationships between environ-



mental  pollution and property values that'are discernible.  The dif-



ference in conclusions  Is one arising  from differences  in the scale



of analysis,  and  in no way  implies  that one set of conclusions con-



tradicts the  others.
                                   32

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            VI.   INTRA-METROPOLITAN  ANALYSES




     A variety of exploratory and experimental  studies of  land  use-

environmental pollution relationships  also  were undertaken within

metropolitan regions after first providing  a  detailed  review, for
                              »
each pollutant,  of patterns of pollutant  sources within metropolitan

regions, generation factors, diffusion, dispersion  and transport

mechanisms, etc., consistent with the  flow  of causation diagrammed

in Figure 2.  No attempt was made to achieve  comprehensiveness  or

completeness, because of the limitations  inherent  in the data sources,

Rather, the intent was to investigate  potentially  fruitful lines of

inquiry.  Two of these lines will be noted  here, because of  their

different links  to urban form:  (a)  relationships of air pollution

to urban densities; and (b) patterns of water quality  in a complex

hydrologic situation.

A.   Sample Density Relations

     It is known that population densities  within  urban regions drop

off with distance from the city  center in a negative exponential

manner  (dx = D e~^x) where dx is population density at distance x

from the city center, DC is density  at the  city center, and  B is the

density gradient, the rate at which  densities fall  with  increasing

distance.
                                 33

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     Such density gradients were fitted to data obtained for each of



the 13 sample regions for the censuses of 1950, I960, and 1970.   It



was found that in each census year, larger cities have higher central



densities and flatter density gradients, whereas in all cities in the



20-year period, central densities have been declining in absolute terms



and density gradients have been becoming flatter as urban dencentral-



ization has progressed.



     The question that then was posed was whether air pollution showed



similar gradient patterns and changes.  In several cases, it was found



that a similar equation descrf-bes the spatial pattern of air pollution,



but comparable data were unavailable to relate unfolding urban decen-



tralization to changes in the pattern of air pollution.



     Some experimentation also  took place with both  solid wastes and



noise data, and  it was found that these, too, were density-related,



suggesting that  they might be profitably subjected to density-gradient



analysis as better data become  available in the future.
                                  34

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                         VII.   SUMMARY



     To summarize, the following are some of the main principal  conclusions

of the statistical analyses presented in Land Use,  Urban Form and Environ-

mental duality:

              FINDINGS FROM MULTIPLE REGRESSION ANALYSIS
                     WITH PROPERTY VALUES AS
                      THE DEPENDENT VARIABLE

          1.  Property Values:

              a.  Increase with metropolitan size
              b.  Decrease with manufacturing concentration
              c.  Increase with high-income population

          2.  Environmental quality is better in high-income
              cities than in low-income cities.

          3.  When population size, manufacturing concentration,
              and income level  are taken into account, differ-
              ential environmental pollution levels have no effect
              on property values.

          4.  When cities were grouped by population size,  popu-
              lation size still affected property values in a
              positive fashion and manufacturing affected property
              values in a negative fashion for cities within a
              group.

          5.  The relationship between property values and  city
              size follows an S-shaped curve, which means that
              for small and large city sizes, a change in city size
              produces a larger Increase in property values than is
              true of medium city sizes.

          6.  Total property values are greater in low-density dis-
              persed urban regions than in high-density concentra-
              ted regions, when population size, manufacturing
              concentrations and income levels are taken into
              account.
                                   35

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    FINDINGS FROM MULTIPLE REGRESSION ANALYSES
     WITH LAND USE AS THE DEPENDENT VARIABLE
1.  Urban form plays a significant role in translating
    city characteristics into land use.

2.  Land use plays a significant role in expressing the
    effects of urban.form on environmental pollution.

3.  Residential land use:

    a.  Increases with metropolitan size
    b.  Decreases with Income levels
    c.  Increases with manufacturing employment
    d.  Decreases in high-density core-oriented cities
    e.  Increases as the city area increases and as
           the number of circumferential highways in-
           creases i.e. as urban sprawl increases in
           dispersed urban regions

4.  Other  land uses:

    a.  Commercial and extractive land use
            -  increases with city size
            -  decreases when the density gradient Is steeper
            -  decreases with Income levels
            -  increases with manufacturing concentrations
    b.  Open space
            -  decreases with city size
            -  decreases with manufacturing concentrations
            -  increases with income levels
            -  increases when the density gradient is steeper
                         36

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SELECTED WATER
RESOURCES ABSTRACTS

INPUT TRANSACTION FORM
                             Repo > No.
                                                w
 4. Title

   Land Use Forms and the Environment - An Executive Summary
           .1  I
                    >*yy
  Department  of Geography and Center for Urban Studies
  University  of Chicago
  Chicago,  Illinois
                                                                     5. Report Date
                                                                     8. Perfo.. >ing Or£
                                                                        P. -port Nc
                                                                        1HA098
 12.  Sponsoring Organiutioa

 15.  Snpplcmenur> Not->
Eaviromental Protection Agency

Environmental Protection Agency
Report No.  EPA-600/5-75-003, March 1975
                            801419
                            Type of Report and
                            Penod Le
                            Final
 16  Abstract

       This executive summary contains highlights of the  full study which focused  on
  the relationship between land use forms and environmental quality.  It investigated
  the influence of the spatial distribution of land rises on the pollutants generated
  and the resulting environmental quality.  The investigation was assisted by the
  preparation of a "sorting table" in which the "rows" are the various urban forms and
  land use patterns and the "columns" are the several classes, types and elements  of
  environmental pollution.

       A comparative analysis of  the materials assembled  for the table determined  trends
  across the urban forms and land use types, focusing particularly on the identification
  of those land use forms that naturally generate the least pollution.  Also, parallel
  Investigation of national trends in population distribution and land use was performed,
  so that some expectations could be developed as to the  likely impacts on pollution of
  current patterns of regional growth and change.
 la  I)ec..riptOK
 17b.  Idenlilicrs
 17c.  COWS R. Held &. Group
 18. Volatility
     ,9. Security dan.
        (Report)

     20. Security Class.
21. No. of
   Pages

27. Puce
Send To:

WATER RESOURCES SCICMTtmC INFORMATION COTTER
U.S. OKMRTMCNT OP THC INTERIOR
WASHINGTON. OJG. Mt4O
 Au-tracti-i
WRSIC 102 (REV. JUNE 1971)

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