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Xerox University Microfilms 300 North Zaab Road Ann Arbor, Michigan 4AI06 $ 75-3045 DAVIS. Richard Miles. 1940- DEVELOPMENT AND APPLICATION OF AN ECONOMIC-ENVIRONMENTAL TRADE-OFF MODEL FOR LAND USE PLANNING. The Ohio State University* Ph.D., 1974 Geography

Xerox University Microfilms , Ann Arbor, Michigan 48106 t

© 1974

RICHARD MILES DAVIS

ALL RIGHTS RESERVED

THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED. DEVELOPMENT AND APPLICATION OF AN ECONOMIC-

ENVIRONMENTAL TRADE-OFF MODEL FOR LAND USE PLANNING

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

By

Richard Miles Davis, B.A., M.A.

*****

The Ohio State University 1974

Reading Committee: Approved by

Henry L , Hunker

Howard 1 [i, Gauthier

Robert 1S. Roth Iviser Depart t of Geography DEDICATION

To Beverly, Sandy and Dick

11 ACKNOWLEDGMENTS

Several Individuals and organizations were instrumental in

assisting me to the successful completion of this research. I am

indebted to my adviser, Professor Henry L. Hunker, and the other

members of my reading committee, Professors Howard L. Gauthier and

Robert E. Roth, who so ably performed their duty of providing advice

and counsel throughout the program.

Valuable assistance was received from colleagues Mr. Frederick

K. Goodman who assisted in the programming of the model and Dr. Gary

S. Stacey who assisted in the initial formulation of the regional

analysis, and Mrs. Barbara Coles who aided and abetted In the entire

venture by assisting with data reduction and typing the draft manu­

script. 1 also acknowledge the institutional support received from

Battelle's Columbus Laboratories so I could direct my efforts toward

the completion of this work.

Most of all I acknowledge the constant patience and encourage-

ment received from the Family Committee chaired by Beverly Ann, my

wife, and staffed by Sandra Lynn and Richard Miles, Jr., my children,

who unquestionably have been as much affected by this educational

experience as I.

i i

ill VITA

May 25, 1940. . . Born - Cambridge, Massachusetts

1963...... B.A., Boston University, Boston, Massachusetts

1963-1969 . . . . Research Scientist, Travelers Research Corp­ oration, Hartford, Connecticut

1969...... M.A., Trinity College, Hartford, Connecticut

1969-1971 . . . . Research Economist, Battelle's Columbus Laboratories, Columbus, Ohio

1971-1974 . . . . Manager, Regional Centers Program, Battelle's Columbus Laboratories, Columbus, Ohio

PUBLICATIONS

"Measuring Impacts of Urban Water Development", Water Resources Bulletin, v. 7, No. 4, pp. 661-669, August 1971.

"Police Management Techniques for the Medlum-Slze Community", The Police Chief, v. 37, No. 7, pp. 44-50, July 1970.

"Development of an Economic-Environmental Trade-Off Model for Industrial Land Use Planning", The Review of Regional Studies, v. 4, No. 1, to be published, Spring 1975.

FIELDS OF STUDY

Major Field: Resource Management and Regional Development

Studies In Climatology. Dr. Robert Batchelder

Studies In Water Resources. Dr. Paul Bock

Studies in Public Administration. Dr. Clyde McKee

Studies in Resource Management. Drs. Henry L. Hunker and Robert E, Roth

Studies In Regional Development, Dr. Howard L. Gauthier

lv TABLE OF CONTENTS

Page

DEDICATION...... 11

ACKNOWLEDGMENTS...... Ill

VITA...... lv

LIST OF TABLES...... vil

LIST OF FIGURES...... lx

Chapter

I. INTRODUCTION...... 1

Problem Statement Dissertation Organization

II. REVIEW AND ANALYSIS OF RELEVANT LITERATURE...... 10

Organization • The Early Environmental/Conservation Movement

III. THE CONCEPTUAL MODEL...... 53

Restatement of Problem Overview of the Conceptual Model Regional County Model (Submodel 1) Site-Evaluation Model (Submodel 2)

IV. DESCRIPTION AND DATA PREPARATION FOR THE CASE STUDY AREA...... 73

Identification of Study Area Data Preparation for the Regional Analysis Submodel (Submodel 1) Data Preparation for the Site Analysis Submodel (Submodel 2) Environmental Overlays Economic Overlays

v Page

V. MODEL APPLICATION AND RESULTS OF ANALYSIS...... 139

Overview of Model Experimentation Experimentation with Submodels Model Experimentation and Results of Analyses . . . . 147

VI. SUMMARY AND CONCLUSIONS ...... 162

Review of Propositions Strengths of the Model Recommendations for Further Reseorch

APPENDIX

A. REVIEW OF SELECTED ENVIRONMENTAL ASSESSMENT METHODOLOGIES...... 170

B. LAND AREA REQUIREMENTS OF SELECTED INDUSTRY AND TEST OF LINEARITY OF LAND COEFFICIENTS...... 186

C. DEVELOPING A REGIONAL INPUT-OUTPUTMODEL ...... 194

D. MODEL SENSITIVITY TO FAMILY SIZE AND IN-MIGRATION RATES...... 202

E. RESULTS OF IMPACT ANALYSIS FOR 300 NEW EMPLOYEES BY SECTOR DERIVED FROM SUBMODEL 1...... 206

BIBLIOGRAPHY...... 230

vi LIST OF TABLES

Table Page

1. Land Disposal Summary...... 15

2. National Trends in Urbanization...... 18

3. State Air Quality Program Elements, 1970...... 26

4. State Water Quality Program Elements, 1970...... 27

5* Criteria Used to Evaluate Environmental Assessment Methodologies ...... 37

6, Environmental Assessment Methodologies Evaluated..... 39

7. Methodology Evaluation Summary Chart...... 43

6* Interrelationships Among Regions...... 49

9. Summary Organization of the Interregional Economic- Ecologlc Activity Analysis Framework...... 50

10* Criteria Used to Develop Industry Profiles...... 64

11. Candidate Suitability Criteria Considered for Submodel 2. 68

12. Growth of Charleston Region, 1960-1970...... 77

13. Employment Distribution In Percent for the United States and Coastal Plains Region, and in Percent and Numbers for the Charleston Region, 1970 ...... 78

14. Comparative Advantages of Charleston Region...... 81

15. Industry Classification of the 1967 Input-Output Tables . 89

16. Employment by Sector, Charleston Region, 1970 ...... 94

17. Adjusted Technical Coefficients, Charleston SMSA, 1970. . 97

18. Dollar Values of Interindustry Transactions, Charleston SMSA, 1970...... 100

19. Coverage of Industrial Land Use Survey...... 107

vii Table Page

20. Analysis of Impacts on Selected Natural Resource Inputs, Waste Emissions, and Employment, Charleston SMSA, 1970. . 109

21. Criteria for Evaluating Economic and Environmental Suitability of Sites...... 1161

22. Input Variables for Submodel 1...... 142

23. Output Indicators for Submodel 1...... 143

24. Input Variables for Submodel 2...... 145

25. Land Use Planning Model Experimentation ...... 148

26. Assessment of Impact of 300 New Employees in 23 Sectors in Charleston Region, 1970...... 150

27. Summary of Impacts from 300 New Employees in Each Sector on Key Economic and Environmental Indicators for the Charleston Region, 1970 ...... 152

28. Summary of Computation of Suitability Index for Five Select Sites...... 158

29. Allocation of Three Proposed Industries to Five Representative Industrial SiteB ...... 160

30. Land Area Requirements of Selected Industry Per Employee. 188

31. Location Quotient, Charleston SMSA, 1970...... 200

32. Results of Sensitivity Analysis for Variables: Average Size of In-Migrating Families (AVS) and Proportion of In-Migrants (PNI) ...... 204

33-55. Results of Impact Analysis for 300 New Employees by Sector Derived from Submodel 1 ...... 206

vlll LIST OF FIGURES

Figure Page

1. General Research Design...... 8

2. Simplified Structure of Land Use Planning Model...... 56

3. Conceptual Structure of Submodel 1 ...... 59

4. Expanded Economic-Environmental Matrix for Submodel1. . 63

5. Land forms...... • . • . 126

6. Forests . . 127

7. Wildlife Habitats...... 128

8. Air Resources...... 129

9. Watershed Resources...... 130

10. Sewer and Water Utilities...... 132

11. Transportation Access...... 133

12. Existing Land Use...... 134

13. Landforms...... 135

14. Topography/Slope ...... 136

15. Soil Type Associations...... 137

16. Geologic Formations...... 138

17. Five Representative Industrial Sites in the Charleston Region...... 156

18. Scattergram of Relationship Between Land Consumption Rates and Size of F i r m ...... 191

19. Overlay of Five Representative Industrial Sites in the Charleston Region...... 235

Map 1. Ihe Coastal Plains Region...... 74

Map 2. Charleston Study Area...... 76 ix CHAPTER I

INTRODUCTION

Problem Statement

The development and application of an economic-environmental trade-off model for land use planning is the subject of this disserta­ tion. Land use planning is rapidly becoming one of the key environment­ al issues of the 1970's.* Attention is being given to how land use and its spatial arrangement determines or affects the natural environment.

After years of following a course of action that allowed development to occur principally in response to market factors, planners, legislators, government officials, and the public are becoming increasingly concerned that development and environmental goals be pursued in harmony. Presi­ dent Nixon said in his February 19, 1973, report on the State of Our

Natural Resources,

As we steadily bring our pollution problems under control more effective and sensible use of our land is rapidly emerging as among the highest of our priorities.

Concern for the natural environment has stimulated passage of strong state and Federal legislation to control uses of the natural environment. The National Environmental Policy Act of 1969, the Federal

Water Pollution Control Act of 1972, and the Coastal Zone Management Act of 1972 represent major Federal legislation directed toward controlling

^Fred Bosselman and David Callles, The Quiet Revolution in Land Use Control (Washington, D.C.: Council on Environmental Quality, 1971), pp. 1-365. 2 the quality of the natural environment. Complementing this body of environmental lav is the land use legislation being considered by the

1974 Congress. Meanwhile, several state legislatures have taken the initiative in land use control. They are addressing the question of growth policy and are setting up the machinery for enforcing this policy.^

Recently proposed state legislation recognizes that the location of streets, highways, utilities, and shopping centers can significantly 3 influence the direction of growth in a region. Land use developments of this type.are known to significantly change the economic, social, and environmental character of the regions in which these developments occur.

The challenge faced by state and local public administrators and planning officials is to achieve a balance between environmental quality and economic growth. Economic growth provides the Job opportunities as well os the tax revenues required to provide quality education, health care, and other social services. Similarly, "Every state is currently involved in an environmental crises . . . to resolve the constant con­ flicts that arise between development processes and the needs for envi- L ronmental preservation and resource conservation."

2 For example, Hawaii, Wisconsin, Maine, Massachusetts, and Vermont have recently passed comprehensive or partial land use regula­ tions. 3 The concept of regulating developments of regional impact (DRl's) is incorporated in the National Land Use Policy Act pending in Congress as well as in several state laws regulating land use such as Florida's Land Conservation Act of 1972 (Chapter 259, Florida Statutes).

^Richard H. Slavin, "Toward a State Land Use Policy", State Government: The Journal of State Affairs, Vol. XLIV, No. 1 (Winter, 1971), pp. 2-11. The conflict may be best resolved through a carefully planned industrial development land use program. Land use planning forms a vital link between economic development and environmental quality.

Progressive industrial development programs generally recommend select­ ing those industries that maximize economic benefits while minimizing 5 environmental degradation in the region. The selection of industries for these programs requires careful consideration of the industries1 natural resource input requirements as well as the emission or waste characteristics of the industrial process* In addition to these input- output characteristics, spatial characteristics are also important. As pointed out by Stevens and Brackett, 11. . . it is important to keep in mind the assumption that.location decisions are generally two-step processes. The first step is the selection of the region of location; the second is the selection of a site within that region."^

While macro location factors such as markets, transportation, raw materials, labor supply, etc. are used to determine the "regional** feasibility of industry, micro location factors such as cocinunity serv­ ices, utilities, available land, etc. are used to determine "site" feasibility.^ Thus, the planning official designing a selective indus­ trial development program must decide (1) which industries to attract,

5 David C. Sweet, Appalachian Selective Development Program. Final Report (Columbus: State of Ohio, Department of Economic and Community Development, 1973), pp. 1-244.

6Benjamin H. Stevens and Carolyn A. Brackett, "New and Chang­ ing Factors in Industrial Location", AIDC Journal. Vol. Ill, No. 3 (1968), p. 26.

\ouis K. Loewenstein, "New Factors and Facets of Industrial Location", AIDC Journal. Vol. Ill, No. 3 (1968), p. 26. (2) what wLLl be the regional economic and environmental impact from locating theae industries, and (3) where should the industries be located spatially within the planning region to assure high economic gain and minimal environmental degradation.

Historically, the industrial location problem has most frequent­ ly been analyzed as a problem in optimization* For example, industrial 8 9 location models have ranged from Launhardt and Weber using "locational triangles" to more recent attempts by Casetti^ and Isard^ using linear programming or industrial complex analysis. Most of this work has focused on the identification of optimal locations for industries. How­ ever, an important departure from this approach was discussed by Simon who noted that in industrial development and plant location analysis most decision makers are concerned with evaluation and selection from a set of satisfactory alternative locations, and rarely is the decision focused on optimal alternatives. Simon developed the satisficer concept as a theoretical construct for this decision-making process. He as­ serted that the choice process requires "the replacement of the goal of maximizing with the goal of satisfying, of finding a course of action

0 Wilhelm Launhardt, Mathematische Gegrundung der Volkswlrt- schftslerhre (Leipzig, 1885). 9 A. Weber, Theory of the Location of Industries (Chicagot University of Chicago Press, 1958).

^Emilio Casettl, "Optimal Location of Steel Mills Serving the Quebec and Southern Ontario Steel Market", Canadian Geographer. Vol. X, No. 1 (1966).

^Walter Xsard and E. Schooler, "Industrial Complex Analysis Agglomeration Economics and Regional Development", Journal of Regional Science. Vol. I (Spring, 1959), pp. 19-33. -- 5 12 that is 'good enough.'" In the context of selective industrial devel­ opment it is entirely possible that an Industry might be equally attrac- * • tive to several different geographic regions and may have similar eco­ nomic and environmental impacts at several different sites.

The conflict between the optimizer and satisflcer concepts as they relate to locational decisions was discussed by Wolpert. He indi­ cated that the optimizer concept has been introduced into economic geo­ graphy "by the tacit assumption that men organize themselves, their pro­ duction and their consumption in space so as to maximize utility or 13 revenue." In his study of farming in Middle Sweden, Wolpert points out that "whereas the profit motive is present in every production deci­ sion in the sense that producers may be expected not to seek losses, 14 maximization may not be so universal." Wolpert's conclusion was that,

"the concept of the spatial satisflcer appears more descriptively accu­ rate of the behavioral pattern of the sample population than the norma­ tive concept of Economic Man."*'*

Research Objective and Propositions

The purpose of this dissertation is to develop and test a model which will help the decision maker evaluate specific industrial land use

12 Herbert A. Simon, Models of Man (New York: John Wiley & Sons, 1958), pp. 140-141. 13 Julian Wolpert, "The Decision Process in Spatial Context", Annals. Association of American Geographers, Vol. 54, No. 4, p. 544,

14Ibid., pp. 544-545.

15Ibid.. pp. 558. development proposals. The model is designed to (1) evaluate the total economic and environmental impacts of proposed industrial location deci­ sions on a region (one or more counties) and (2) evaluate the accept­ ability of specific alternative parcels of land (sites) within the re­ gion. The model incorporates the perspective of the local development planner or administrator who is confronted with myriad industrial devel­ opment proposals and who must systematically evaluate these proposals in light of the economic and environmental needs of his planning jurisdic­ tion. The land use model developed will help the development planner trade off potential economic and environmental costs and benefits for his planning region.

Several propositions were established at the outset of this re­ search to assure continuity and direction throughout the program. Prop­ ositions are defined as theorems to be considered) discussed, proven, disprovcn, or unaffected by the results of a research program. The propositions developed for this dissertation include:

(1) The general systems approach can be used to develop

an economic-environmental trade-off model for indus­

trial land use planning.

(2) The land use planning model developed can simulate

' the industrial location decision process.

(3) The land use model developed can assess the relative "

impact of proposed industrial land use changes at

both regional and site specific levels. The impacts

can be measured by economic, environmental, and

social indicators. 7 (4) The land use planning model developed can serve as

the basis of a comprehensive planning tool.

(5) The land use planning model developed is generally

applicable and can be applied to regions and loca­

tions outside of the case study area.

Research Design

The research design used in this program is structured around a

scries of related tasks and research activities. Figure 1 outlines the generalized research design for the program including the major and minor steps in the program. The research method requires the following

sequential steps. i (1) Define the dissertation problem and objectives.

(2) Review and analyze relevant literature on the

conservation/environmental movement, planning and

development philosophy, and impact assessment

methodologies.

. (3) Formulate a model of the economic-environmental

trade-off process in industrial land use planning.

(4) Select and collect data on a case study area for

testing the model.

(5) Develop alltefualivo-itviua^ria!„J,pndus e proposa 1 s,

(6) Evaluate impact of industrial land use proposals.

(7) Develop summary and conclusions from research. CoOact D o ti on C m S tu d y A im fid u itt Impact of lodwitrwl L rid U m Piopoult D tttrib* Social, lew em it, and Eitvironmanbl C kJrw ltfhlki of At m

Om lop Bo m M i o f Study A rt*

Idanbfy AdvtnUyri and Limitation! of

Om lop itMtop Summary Allamalhrt InduttrM Mid C ondutioni land Um Ptopowli tiom RoMoich

FIGURE 1. GENERAL RESEARCH DESIGN Dissertation Organization

The second chapter of this thesis reviews the relevant litera­ ture related to (a) conservation and environmental movement and (b) regional development philosophy, and presents a critique of existing impact assessment methodologies. The third chapter draws upon the literature review and formulates a conceptual economic-environmental trade-off model for land use planning. The fourth chapter describes the selected case-study area and the collection, organization, and preparation of the data. The calibration, operation, and analyses per formed with the model are reported in the fifth chapter. Finally, in the sixth chapter, the land use model is evaluated in light of the pro gram propositions, and conclusions ore drawn on the general appllcabil ity of model to the problem of selective industrial land use planning. CHAPTER II REVIEW AND ANALYSIS OF RELEVANT LITERATURE

Organization

Three related bodies of literature are critiqued in Chapter 2:

(1) the conservation and environmental movement, (2) the planning and development movement, and (3) the methodological literature. The

chapter begins with a discussion of the historical evolution of the

Nation's land ethic. This discussion of attitudes toward land and.

land ownership Is reviewed as background for the subsequent developments

that occurred in the conservation and environmental movement. The

« chapter continues with a discussion of the planning and development

literature and its relationship to contemporary land use planning.

Next, the chapter presents a critique of recent attempts at methodology development designed to help the planner/developer analyze economic

and environmental programs. The research conducted in this dissertation

is directed at meeting a major research need identified by this litera­

ture review— the need to develop a land use planning model that incor­

porates both economic and environmental factors into the analysis. By

Incorporating both sets of factors into one model, the planner can

trade off economic and environmental costs and benefltB of proposed

industrial land use plans.

10 11 Evolution of a Land Ethic

A national land ethic In the United States has evolved slowly over the years. To understand present attitudes toward land and land use practices, it is necessary to review the evolution of this ethic.

The Indians were first to make their mark on the American land­ scape. Private ownership was not a concept in their society, "to the

Indian mind . . . land belonged collectively to the people who used it.

The nation of private ownership of land, of land as a commodity to be bought and sold, was alien to their thinking, and tribe after tribe re­ sisted the idea to the death."* The natural environment and the atti­ tude toward land changed little under Indian stewardship. They adhered to what Leopold colled the "Community Concept . . • that the individual 2 is a member of a community of interdependent parts." • The colonists from Europe had quite a different view. They had seen their society in Europe grow and transform with technological, political, and social changes. Their concept of land ownership included

"• . * fences and formal papers with wax seals attached were its emblems, 3 and it involved exclusive possession of parcels of land." Owning land was a measure of wealth and, to them, was an end in itself.

"The new world had a two-fold effect on the settlers. The for­ est and the wilderness represented a threatening force that had to be

*Stewart L. Udall, The Quiet Crisis (New York: Holt, Rinehardt and Winston, 1963), p. 8. 2 Aldo Leopold, Sand County Almanac (London: Oxford University Press, 1949), p. 203.

\dall, Quiet Crisis, p. 15. 12 conquered If they were to feel secure; It also represented the great 4 vastncss and abundances of resources that the new land possessed."

Even these common forces varied on a regional level. The settlement patterns of the New England colonies and the southern colonies give an insight into what was to come. In New England when a group of settlers wanted to establish a new town, they first obtained permission from the government and then surveyed and prepared titles for the land. They established a common grazing and meeting ground and built their houses around that area. They cleared the land collectively and divided it up evenly by family. Such settlements had little or no land speculation.

Agriculture was the concern of the entire town and was not the domain of a few large land owners.

The southern colonial establishment was quite different. Each man that settled in the colony received 50 acres (called a headrlght).

Those given headrights could select their location. Surveying and the issuing of land titles were ignored and thus land speculation became common practice. Headrights could be bought and sold. This led to the assembling of lands into the large plantations so evident in the south

later in the century.

The Revolution had a great effect on evolving settlement pat­

terns in the United States. The new government was faced with heavy

debts from the war and depreciated currency. When the Union was formedt

the colonies claiming vast quantities of land to the west, gave up their

claims to the Federal government. As Redding and Parry state, "It is

Martin J. Redding and B. Thomas Parry, "Land Use: A Vital Link to Environmental Quality", Land Use and the Environment (Environ­ mental Protection Agency, 1973), p. 7, 13 important to note that at the very basis of the new government was the firm belief in private property. The question at the time was not whether, but how, the government should dispose of its land to private 5 citizens • • . The first method of disposing of public lands was through cash sale of public lands as early as 1785. Land speculation

Increased in the early 1800's as speculators accumulated large tracts of land along the Atlantic coast where land values were highest. From

1640-1860 settlers were more interested in the government opening and selling land in the western areas as a large segment of the population migrated west in search of new opportunities. Settlers were given priorities in the Pre-emption Act of 1841 which allowed them to buy land on which they had already settled for $1.25 per acre.

A second method of disposing of public land was grants to states and public and private institutions. Grants were given to support pub­

lic education or to states for their administration. As Clawson noted,

Another type of land grant was for swamp and overflow lands, given to states for the purpose of land improvement. This was based on the assumption that the states would be better equipped to improve those lands than the Federal government, [howeverJ, the states were in fact much less well placed to undertake the large capital expenditures needed for extensive land reclama­ tion . . . .6

Meanwhile, transportation facility development was a major instrument

for opening up the West from 1800-1860. While grants for roads and

canals were relatively small, large land grants were made to railroad

transportation companies during the latter half of this period. The

5Ibid.

^Marion S, Clawson, The Land System of the United States (Lincoln: Hie University of Nebraska Press, 1963), p. 61. 14 government was more than generous with the railroads at this time simply because they felt it was the best way to insure settlement of the coun­ try.

Several important legislative acts highlighted the land disposal process in the mid 1800*s. In response to increasing pressure on the government for free land, the following acts were passed!

• General Purpose Grant of 1841 - Gave each state 500,000

acres for use in financing various internal improvements.

• Homestead Act of 1862 - Provided 160 acres of land free

of charge to settlers} settlers had to reside on the

land for 5 years before they acquired title to the land.

Many settlers claimed pre-emption rights after 6 months,

bought the land for $1.25 per acre, and then sold to

land speculators.

• Mineral Lands Act of 1872 - Provided for sale of lands

valuable for minerals and unfit for cultivation.

• Timber Culture Act of 1873 - Cave 160 acres of land to

an individual if he would plant trees on one-quarter

of the land.

• Desert Land Act of 1877 - Provided 640 acres to a

settler if he would irrigate one-eighth of his land.

• Timber and Stone Act of 1878 - Provided for the sale

of lands valuable for timber or stone and unfit for

cultivation. 15

Clawson has summarised the disposal of land claiming that well

over a billion acres of the public domain was disposed of to private

or state control from 1850-1890 (Table 1).

TABLE I

LAND DISPOSAL SUMMARY

Number of Acres (In Millions)

Total Land Area 1,904

Original Public Domain 1,442

Total Disposition, All Methods 1,031

Cash Soles, and Misc. Methods 300

Homesteads 285

Grants to States 225

Military Bounties and Private Claims 95

Railroad Grants 91

Timber Culture: Other Related Acts 35

Source: M. Clawson, The Land System of the United States (Lincoln: The University of Nebraska Press, 1963), p. 8.

In summary, growth was a major goal of the United States during the first half of the 19th Century. Most believed that this growth was good for the Nation and that private land ownership and disposal was an accepted form of wealth transfer. The attitude of the people and their leaders was that growth signified progress which became a major tenet of the growth ethic. Since land was plentiful and cheap, a "use it up, 16 throw it away" attitude was established. There was always more land, more trees, more water, and more minerals. Land speculation became a common (and basically accepted) practice in our early history.^ The practices and policies of resource exploitation began to take their toll on the Nation's resource base in the 1840's and 1850's.

The Early Environmental/Conservation Movement

Several factors stimulated a change in attitude toward the

Nation's resources beginning in the 1840's.

The popular attitude toward the public domain has varied as a result of five chief influences: (1) the growth of population} (2) the spread of the people made possible partly by improvements in transportation} (3) the con­ spicuous consequences of the exploitation of the land, especially deforestation, depletion of minerals and game animals, and, more recently, the striking effects of soil erosion} and (4) the growing realization that natural resources are limited and are being used up rapidly. (5) . . • the growing sense of responsibility concerning the .welfare of the populace.^

Stimulated by these factors national attitudes toward resource use began

to shift from those of resource exploitation to resource conservation.

The shift in attitudes marked the beginning of a new environmental ethic.

Several reknowned conservationists spearheaded the period such as George

P. Marsh, who pronounced his heralded statement for conservation on a

national scale in his book Man and Nature in 1863, Gifford Pinchot who

became Chief of the Forestry Division in 1898 and became a strong advo­

cate of modem forestry management, John Muir whose preservationist's

7 Redding and Parry, "Land Use," p. 8. O Guy-Harold Smith, Conservation of Natural Resources (New York: John Wiley & Sons, 1950), p. 18. attitudes stimulated the wilderness movement in the 1840's and culmi­ nated in President Theodore Roosevelt's first Conservation Conference in

1908. The Conference marked the first major initiative by the Federal

government to provide leadership in the national conservation effort.

Interest in the new ethic waned temporarily during World War I as the

Nation exploited resources for the war effort* Interest in the conser­ vation effort was rekindled during the depression years of the 1930's

and implemented through Franklin Roosevelt's public works programs.

During the decade 1930-1940 several pieces of landmark legislation ex­

emplified national concern with our natural resources and clearly estab­

lished the Federal government in a leadership role for protecting these

resources. The Works Progress Administration (1933) and the Civilian

Conservation Corps (1933) arc examples of Federal program initiates in

human resource conservation started during the depression to gainfully

employ a large unemployed labor force. The Tennessee Valley Authority

(1933) and the Soil Conservation Service (1935) were Federal program

initiates directed at natural resource conservation started to repair

past and prevent future environmental damage to the Nation's resources.

The contemporary environmental era can be traced to Aldo Leopold

and such works as his Sand County Almanac (1949) and Stewart Udall's

Quiet Crisis (1969). While the environmental movement continues strong

in the 1970's despite some backlash caused by concern over the energy

crisis, resource use and particularly land use are now recognized as a

vital link to controlling environmental quality. 18

The Contemporary Environmental/ Conservation Movement

The contemporary environmental/conservation movement has been attributed to such factora asi (1) increased population density, (2) decline in the quality of the natural environment! (3) increased know­ ledge of the impact of the natural environment on the physical and psy­ chological health of peoplet and (4) decline in known natural resource reserves. For example, urbanization has increased at an unprecedented rate in recent years, and there appears to be • . a strong correla­ tion between urban population growth and degradation in the quality of life,” according to the Council on Environmental Quality (CEQ). The trend toward urbanization is shown clearly in Table 2.

TABLE 2

NATIONAL TRENDS IN URBANIZATION

Percent U.S. Population 1900 1910 1920 1930 1940 1950 1960 1970

Urban 40 46 51 56 57 60 70 74

Non-Urban 60 54 49 44 43 40 30 26

Source: U.S. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States (1973). p. 18.

Density-associated environmental problems have spread according to the Council. Instead of being confined to urban areas alone as in the past, pollution began to affect entire metropolitan areas. Concern and public awareness over the quality of the natural environment also 19 grew as more systematic information became available on the quality of the environment. As reported in the First Annual Report of the Council on Environmental Quality in 1970*

Air Quality. In 1968, there were over 214 million tons of carbon dioxide, particulate matter, sulfur oxides, hydro­ carbons and nitrogen oxides released into the air, mostly in metropolitan areas, affecting health, vegetation, and property.

Water Quality. By 2000 it is projected that we will with­ draw 900 billion gallons of water from our rivers (80 per­ cent of their total flow). If our treatment facilities were totally effective, the problem would not be as severe, but they are not* today less than one-third of the nation is served by adequate treatment facilities, and one-third by no system at all* In some areas, industries continue to dump untreated wastes into streams and rivers) in other areas treatment systems arc not reducing the biological oxygen demand of the sewage to a point where water becomes more precious as time goes on.

Solid Waste. In 1969, Americans produced over 250 million tons of solid waste, most of which was disposed of in open dumps. Each American now produces 5.5 pounds of solid waste each day, and the rate of production is steadily rising.

Noise. The noise level of our metropolitan areas, especially the urban centers is almost deafening. City traffic noises are now as high as 90 decibels (a level which causes hearing damage over extended periods of time).

Social. In the last 10 years there has been a continued expansion of slum areas. Crime is still increasing by leaps and bounds while overcrowding and lack of space in metropolitan centers are creating both psychological and physiological problems.?

The Council went on to note that as environmental and social

problems continued to grow, there was a tendency for inhabitants to move

9 Environmental Quality* The First Annual Report of the Council on Environmental Quality (Washington, D.C.t Council on Environmental Quality, 1970), p. 65. 20 outward, away from the source of concern* While this trend reduces population concentration within the city, it can create urban sprawl and degrade the environment of the periphery. In recent years, some of

these trends have been reversed, particularly those regarding water pol­

lution and crime. However, as the Council states, these factors are still a dominant influence on urban and metropolitan life. The growing complexity and impact of environmental problems created a need for

strong Federal leadership in organizing and implementing programs de­

signed to protect and manage the natural environment.

Federal Initiatives in Environmental Control Programs

The evolution of the present Federal environmental control pro­

gram can be illustrated by (1) the history of enabling legislation which

authorized these programs, (2) the creation of institutions to execute

the provisions of this legislation, and (3) the process by which these

institutions created environmental control procedures. The nature of

the legislative, institutional and planning processes will, to a large

degree, determine the ease with which environmental protection agencies

can incorporate land use planning and control objectives into their • i present programs.

The development of environmental, protection programs in the

United States has been determined to a considerable extent by Federal

legislation. This has encompassed the whole range of environmental in­

sults from air pollutants to solid waste, but has, for the most part,

been formulated as an array of single-purpose legislative instruments, 21 each directed toward a specific pollution problem. The following cri­ tique of environmental protection legislation illustrates the initiative taken by the Federal government to mount a major effort to establish environmental protection programs since 1948.

Water Quality Legislation. The modem legislative approach to the problems of environment began with the Water Pollution Control Act of 1948. An enforcement procedure consisting of a conference hearing/ court action process was provided for water pollution abatement when the

Act was amended in 1956. Financial aid in the form of grants and loans were also provided under the Act. The Federal Water Pollution Control

Act of 1961 strengthened Federal enforcement procedures.

The Water Quality Act of 1965 required the states to establish and submit water quality standards for all interstate waters and a plan for the rapid achievement of the standards. These standards became the basis for most actions under the Federal Water Pollution Control Act, including planning activities, awarding of construction grants, and en­ forcement practices.

The 1966 Clean Water Restoration Act provided a grant system to support the establishment and maintenance of river basin planning by major river basin planning commissions based on water quality standards.

The Act also vastly increased expenditures for construction of municipal waste treatment works.

In late 1970, the President announced a new program to control water pollution through the permit authority of the Refuse Act of 1899.

The Refuse Act outlaws discharges and deposits into navigable waters 22 without a permit from the Secretary of the Army. The program makes a permit mandatory for ail industrial discharges into navigable waters of the United States. Violators of standards including standards imposed by the EVA when Federal-state or state standards do not apply or are clearly deficient are ineligible for permits and liable to enforcement proceedings. The Water Quality Improvement Act of 1970 further provides that any Federally regulated activity must have state certification that it will not violate water quality standards.

Air Quality Legislation. Federal legislation related to air pollution began in July, 1955, when Congress authorized a Federal pro­ gram of research on air pollution and technical assistance to state and local governments. The Clean Air Act of 1963 and the Motor Vehicle Act of 1965, augmented by the Air Quality Act of 1967, and culminating in i the Clean Air Act Amendments of 1970, represent the most significant

Federal legislation regarding air quality. The 1970 Amendments, as the strongest air pollution control legislation, authorize the regulation of both mobile and stationary sources of pollution. The most important sections of these programs deal with establishing National air quality standards, describing a framework for the states to meet these standards, i and improving procedures for Federal enforcement. The Environmental

Protection Agency (EPA) has thus far set National air-quality standards for particulate matter, sulfur oxides, carbon monoxide photochemical oxidants, hydrocarbons, and nitrogen dioxide. Federal Guidelines pub­ lished by the EPA require that states submit implementation plans for attaining and maintaining of these standards. 23

The 1970 Amendments also made Federal enforcement more effective

by providing EPA authority to issue compliance orders to any person in violation of implementation plans, and authorizing citizen suits to en­

force the provisions of the Glean Air Amendments.

The Clean Air Amendments indicate a recent shift in the burden

of proof in pollution control. When the EPA now specifies that an air

pollutant is a health hazard, industry must either comply with the emis­

sion standard or prove that the health hazard does not exist.

Solid Waste Disposal Legislation. The Solid Waste Disposal Act

of 1965, the first legislation aimed at solid waste management, is di­

rected primarily at the loss of natural resources which solid waste

represents. This Act authorized a research and development program with

respect to solid waste to promote the demonstration, construction, and

application of solid-waste management and resource-recovery systems. In

addition, the Act (1) provides financial and technical assistance to

states and local governments and interstate agencies in the planning and

development of resource recovery and solid-waste disposal programs, and

(2) promotes a national research and development program for improved

solid waste management programs.

The Resource Recovery Act of 1970 put a new emphasis on recycl­

ing and reusing waste materials by authorizing funds for demonstration

grants for recycling systems and for studies of methods to encourage

resource recovery. This Act also requires the EPA to publish guidelines

for construction and operation of solid waste disposal systems. 24

Environmental Protection Institutions^

The recent environmental protection legislation has necessitated organization or reorganization of environmental programs at the Federal, state, and local levels in order to cope with the Increased regulatory requirements of these legislative programs*

Federal Activities* The National Environmental Policy Act (NEPA) was passed by Congress in 1969. To implement this legislation, Reorgan­ ization Plan 3 was drafted and accepted, creating the Environmental Pro­ tection Agency (EPA) on December 2, 1970. EPA's mission is M. . • to define, achieve, and maintain environmental quality by abating and con­ trolling pollution from point sources by utilizing a wide range of in­ tervention strategies . . . The reorganization consolidated into one agency the Federal programs dealing with air pollution, water pollu­ tion, solid waste disposal, pesticide regulation, and environmental radiation. The EPA is a line agency with responsibility to administer, conduct, and enforce Federal pollution control programs.

The Act also created a Council on Environmental Quality (CEQ).

Although the Council on Environmental Quality and the EPA work closely together, their responsibilities differ significantly. The CEQ, as a staff agency in the Executive Office of the President, provides policy advice, and reviews and comments on the environmental impact control

^This section summarizes discussion contained in the Second Annual Report of the Council on Environmental Quality (Washington, D.C.t Council on Environmental Quality, 1971), Chapters 2 and 3.

^National Environmental Policy Act of 1969, Public Law 91-190, 42 U.S.C. 4321, paragraph 1. 25 activities of Federal agencies. The concern of CEQ is with the broad spectrum of environmental matters.

Local and State Environmental Protection Agencies. Recent Fed­ eral legislation has placed more and more responsibility for environ­ mental programs at the state level. In the past, environmental programs in most states were fragmented or scattered throughout many state agencies, boards, and commissions. Air- and water-pollution-control programs were frequently lodged in a state health department. Water- pollution-control programs were often incorporated into water resource management or public water-supply programs. Pesticide regulation was frequently under the health department or.the agriculture department; solid-waste management was frequently a responsibility of the health department. Some states have reorganized to cope with the broad scope of environmental Issues. Ohio, Massachusetts, New York, Washington,

Illinois, and other states have enacted legislation that consolidates pollution-control programs and streamlines pollution control authority.

The status of state air and water programs is shown in Tables

3 and 4. The elements listed refer to requirements of state implementa­ tion plans as specified in the Clean Air Amendments and the Water Qual­ ity Improvement Act. The numbers in the columns indicate the number of states and/or U.S. territories that have passed the necessary legisla­ tive authority to implement recommended elements of air and water qual­ ity control programs.

Solid waste management practices are also becoming increasingly regulated and less fragmented. As a result of the Solid Waste Disposal 26

TABLE 3

STATE AIR QUALITY PROGRAM ELEMENTS, 1970

States and Territories® Legislative Authority With Authority Without Authority

Adopt emission standards and promul­ gate other regulations 54 0

Require information on processes and potential emissions from sources of air pollution 39 15

Issue permits for construction of new sources of air pollution 38 16

Inspect facilities causing pollution 52 2

Require emission information from polluters and make it available to public 20 34

Require monitoring of emission by polluters 13 41

Issue and enforce compliance orders 51 3

Enjoin standards violators 52 2

Take special, prompt action in case of air pollution emergencies 44 10

Regulate land use and transportation to meet air quality standards 5 49

Inspect automotive pollution control r devices 16 38

54 territories include U.S. external territories of American Samoa, Guam, U.S. Trust Territories of the Pacific Islands, and the U.S. Virgin Islands.

Sourcet EPA, Office of Air Programs. 27

TABLE 4

STATE WATER QUALITY PROGRAM ELEMENTS, 1970

Number of Program Element States

Water-Quality Standards Interstate (full Federal approval with antidegradation) 46 Interstate (full Federal approval without antidcgradation) 1 Interstate (Federal approval with exceptions with antidcgradation) 4 Interstate (Federal approval with exceptions without antidegradation) 3

Planning (based on water-quality standards) 23

Permit Systema Municipal 46 Industrial 47

Statfe Matching Grantsa 34

Routine Treatment-Plant Inspection0 46

State Monitoring System 49

°The "Permit System" refers to the existence of enabling legis­ lation to grant permits for discharges. "State Matching" refers to the availability of state funds to assist municipalities in building sewage treatment facilities. "Treatment Plant Inspection" refers to surveil­ lance of the operation and maintenance of facilities at least once a year.

Sources EPA, Office of Water Programs. i Act, as amended, statewide and regionwide solid waste management plans must be prepared and include! (1) an inventory of waste disposal sys­ tems, (2) a survey of problems and practices which can be used as a data base for planning and, (3) wherever possible, provisions for recovery and recycling of solid waste. Lack of adequate Federal funding is cur­ rently limiting the solid waste planning programs.

Development of Land Use Planning

The second principal body of literature reviewed discusses the development of land use planning. According to Chapin, (urban) land use planning is a term used in at least three ways in contemporary planning literature: (1) to identify spatial distributions of city functions— its residential, industrial, comnercial areas; (2) to provide a frame­ work for visualizing urban areas in activity patterns or by physical facilities or improvements to the land in the urban settings; and (3) to

Identify the roles that people play as they regulate space using activ- 12 ities and the use patterns which emerge. The general planning litera­ ture has continued to expand in scope from 1930-1950. Originally, most city and regional planning focused on physical planning* Today, there is much discussion of the interrelationships between physical, social, and economic planning. Similarly land use planning has evolved into one of looking at comprehensive land use patterns and more and more consider­ ing the total impact of land use changes. Today, contemporary land use

12 F, Stuart Chapin, Urban Land Use Planningr 2nd ed. (Urbana: University of Illinois Press, 1965), p. 3. 29

planning involves consideration of the social and environmental-conse­

quences as veil as the economic effects from land use shifts and chang­

ing patterns.

Traditionally land use planning was undertaken to assure the highest and best use of all available land in a defined planning area.

The expression "highest and best land use" became a principle of plan­ ning activities during the 1940's, 50's, and 60's. With the emergence of the Environmental Policy Act of 1969 and companion legislation for

Coastal Zone Management in critical areas, it became clear that the public and its elected representatives no longer were concerned strictly with the "highest and best land use" concept. Rather, they were also concerned with the quality of life and the quality of the environment in which they lived. "Highest and best land use" was no longer expressed solely in the economic terms, but was also expressed in environmental and social terms* Administrative procedures and legal action at the national, state, and local levels have confirmed the belief that eco­ nomic factors alone are no longer the sole determinant of what is con­ sidered the "highest and best use" of land. The problem today is one of developing objective methods, techniques, and methodologies that will help the contemporary planner cope with this new interpretation of land use planning. Today the planner must be able to trade off environmental, social, and economic consequences which may result from recommended land use developments.

One key to the protection and enhancement of our future environ­ ment is more effective land use planning and control. The radical changes in land use planning in some cities, the "quiet revolution" in 30 land use controls taking place in many of our states, and the movement toward a national land use policy at the Federal level give evidence to this recognition* It is essential that actions and decisions related to land use at all levels place environmental values on a level comparable to those for social and economic issues. As stated by the Council on

Environmental Quality in its first annual report to Congress, "Misuse of the land is now one of the most serious and difficult challenges to 13 environmental quality * , . ." In its second report to Congress, CEQ states, "Land use decisions are an important determinant of environment­ al quality. Although planning and control of land use are largely the responsibility of local governments, the impacts of these activities 14 often reach statewide, regionwide, or nationwide." Clearly, contem­ porary planners recognize the need to include social and environmental factors as well as economic factors in their land use planning.

OriRin of Land Use Controls

Land use controls developed differently for nonurban and urban areas. Redding and Parry point out that land use controls were origi­ nally developed to control uses of land in congested cities. "As people moved to new areas in and around the city, they became concerned with the kinds of activities that would be located near their residences.

13 Environmental Quality; The First Annual Report of the Council on Environmental Quality (Washington, D.C.t Council on Environmental Quality, 1970), p. 165. 14 Environmental Quality: The Second Annual Report of the Coun­ cil on Environmental Quality (Washington, D.C.: Council on Environment­ al Quality, 197l), p. 19. 31 15 This led, in 1916, to the adoption of the first zoning laws." These

laws, however, were developed for reasons other than alleviating major

environmental problems, "The objectives of zoning were: (1) the protec­

tion of property values by requiring uniformity in each district, (2)

exclusion of dangerous and nuisance uses from residential districts,

(3) prevention of the over-exploitation of land and the reduction of 16 building density, and (4) fostering public service efficiency."

Instead of dealing with the major cause of environmental pollu­

tion (basically the industries), city dwellers were content to "deal with" the problem by moving away from the source. New zoning laws would

keep the industries in certain areas of the cities where the inhabitants

did not live. This, of course, postponed dealing with the issue of

emission-source pollution.

In the mid-1930's, subdivision regulations were introduced that

conceivably could have controlled the location and the rapidity of new

development. However, these regulations were used more for guiding

growth, as growth for its own sake, was considered proper and desirable.

America became firmly entrenched in "Watch America Grow" syndrome and

subdivisions ran rampant. "In Florida, enough land was subdivided to

house the population of the entire United States. In northern West­

chester County in New York State and along the New Jersey coast,

thousands of twenty-foot lots were distributed by newspapers as free

gifts to subscribers."^ America's land use controls were based solely

^Stephan Sussna, Land Use Controls (Washington, D.C: Urban Land Institute, 1970), p. 6.

*^John Delafons, Land Use Controls in the United States (Cambridge: MIT Press, 1969), p. 28. 32 on economic criteria and fostered the ethic that land was a commodity, and a cheap one at that.

After World War II, tremendous growth in highway building tech­ nology occurred. The Highway system expanded out from the city provid­ ing land developers and private individuals with profitable opportuni­ ties to develop land at major interchanges and key locations along the highway system. For the first time, large developments evolved that were, in a sense, independent of the city and its land use controls.

During this period, land use controls changed little. Master plans for urban and suburban growth began to develop but "most master plans mani­ fested a cursory treatment of the natural and man-made environments.

With plans based on projected growth and development objectives, the standard comprehensive planning process showed little, if any, sensitiv- 18 ity to the impact of development on the natural environment." Only within the post decade have state and local laws begun to require that environmental factors be considered in land use planning along with economic factors.

Role of the State and Local Government in Land Use Control. In

Hawaii the legislature passed a land use law in 1961. The primary rea- son for enacting such a law was to preserve and protect the state's agricultural lands. The land use law created a State Land Use Commis­ sion which was directed to divide the State's land into four categoriesj conservation, agricultural, rural, and urban. The type and extent of

10 Promoting Environmental Quality Through Urban Planning and Controls (Chapel Hill: University of North Carolina, 1973), draft pre- pared by the Center for Urban and Regional Studies, p. 11-14. 33

development permitted in each category is based on the goals of the dis­

trict in which the land is located.

In Wisconsin a program to protect shorelines was authorized as part of the Water Resources Act of 1966. The Act authorized and re­

quired counties to follow specific regulations for the protection of

shorelines in unincorporated areas.

The Maine legislature passed a site location law in 1970 and

created a Department of Environmental Protection. The Department has

the authority (based on certain conditions) to approve or disapprove

large commercial and industrial developments and also residential sub­

divisions larger than 20 acres. A Maine Land Use Regulation Commission was created in the department to plan and regulate land in "unorganized

counties" which make up the northern half of the state.

There have also been regional approaches to land use planning.

The California legislature established a Conservation and Development

Commission to develop and implement a plan for the San Francisco Bay and

its immediate surroundings. In 1967f the Minnesota legislature created

the Metropolitan Council of the Twin Cities to plan, coordinate, and

implement all development In the metropolitan area surrounding Minneapo­

lis and St. Paul. A plan for Lake Tahoe has been created by the Tahoe

Regional Planning Agency. The basic purpose of the Agency is to plan development that is essential to accommodate the people within the re­

gion's area without destroying the environment.

In summary, the new approaches to state and local planning as well as the legislation pending in Congress define land use planning in

a much broader context. First, it is being viewed in a regional context. 34

Second, it Is being used to implement a broad range of social and envi­ ronmental policies. Third, it is being used to control economic growth: to define agricultural lands or allocate .land for open space uses. For land use planning to be effective as an instrument for this broad range of policies, it must be developed as a tool for articulating the impli­ cations of social, environmental, and economic growth policies. It is these policies that are affecting land use and that may be affected in turn by land use planning.

Review of Environmental Assessment Methodologies

The third body of literature reviewed dealt with developments in environmental assessment methodologies* The National Environmental

Policy Act of 1969 (NEPA) was one of the most significant pieces of envi­ ronmental legislation passed by Congress. The purposes of the Act were stated in Section 2 as follows: "To declare a national policy which will encourage productive and enjoyable harmony between man and his envi­ ronment} to promote efforts which will prevent or eliminate damage to the environment and biosphere and stimulate the health and welfare of man} to enrich the understanding of the ecological systems and natural resources constant to the Nation} and to establish a Council on Environ­ mental Quality."^

As a result of the National Environmental Policy Act (NEPA), planners of major construction projects financed in part or whole by

Federal funds are faced with a new requirement. This is the requirement

19 Public Law 91-190,- 91st Congress, S. 1075, paragraph 1. i I

35

that the proposal for the project be accompanied by an Environmental

Impact Statement (EIS) describing the ways the project would affect the

quality of the environment. The Act is intended to stimulate fore­

thought on actions that might have bearing on the quality of the envi­

ronment and to give decision makers the facts needed for rational judg­

ments. Since the Act has been passed, literally thousands upon thou­

sands of Environmental Impact Statements have been prepared and submit­

ted to the Federal government for approval. The machinery to review and

process these statements is cumbersome and frequently results in a long

delay being added to the project review cycle. Frequently the state­

ments receive only cursory review.

NEPA requires that five points be covered in the Environmental

I Impact Statement. A typical study aimed at developing information for a

an assessment considers:

• Direct environmental impacts of the proposed action.

• Any adverse environmental effects that cannot be

avoided should the proposed action be executed.

• Alternatives to the proposed action.

• Any irreversible or irretrievable commitments of

resources that would be involved should the proposed

action be implemented.

• The relationship between local short-term uses of the

environment and enhancement of long-term productivity.

The goal Is to insure that all environmental values including

those that have been ignored in the past are given appropriate considera­

tion. 36

The passage of NEPA has stimulated the development of a substan­

tial literature on impact assessment methodologies* Host present avail- 20 able methodologies are crudet and most have not been widely tested.

Nevertheless, to evaluate the merits of projects with modem concern for

the environment and the quality of life, requires evaluations that are practical, advanced, and comprehensive*

An extensive review of the state of the art in environmental

impact assessment methodologies was conducted. The National Environ­ mental Policy Act identified several criteria to be included in the im­

pact evaluation. The author reviewed the requirements of the Act and

the planning literature and identified ten criteria that were repeatedly mentioned as being most important in environmental assessment. These criteria are listed in Table 5. Next, 23-impact assessment methodol­ ogies were identified in the literature and evaluated according to the criteria identified. The impact assessment methodologies considered are

listed in Table 6 and discussed in detail in Appendix A.

The review of the literature on impact assessment methodologies

indicated three general types of approaches.

(1) Ad hoc committees

(2) Overlays

(3) Checklists.

The Ad hoc committee approach involves the assembly of a panel

of experts on a project-by-project basis to conduct assessments of proj­

ect impacts in their respective areas of expertise. This approach

20 The term methodology is used in the generic sense including both formal and informal approaches to evaluating environmental impacts. 37

TABLE 5

CRITERIA USED TO EVALUATE ENVIRONMENTAL ASSESSMENT METHODOLOGIES

1. Comprehensive

An environmental assessment methodology must be comprehensive because the environment is an intricate system of living and nonliving elements held together by complex processes, and because environmental concerns relating to large scale projects (such as highways) range wide­ ly from physical impacts on natural resources (air, land, water) to im­ pacts on living organisms (plants, animals, microorganisms) to a variety of impacts on people (aesthetic, cultural, and social values).

2. Flexible

The methodology must be flexible to permit its use in assessing impacts from both small- and large-scale projects, and it must require resources (people, time, and money) commensurate with the scale of the project.

3. Detect Project-Generated Impacts

The methodology must be able to measure changes in actual envi­ ronmental conditions that would result from the project as compared to any changes that would naturally occur if the project were not con­ structed, both short-term (e.g., construction phase) and long-term (e.g., operation and maintenance phases). The methodology must be structured to access differences in environmental conditions that would exist "with the project" as opposed to those that would exist "without the project."

4. Objective

The methodology must be objective, it must provide impersonal, unbiased, and constant yardsticks immune to outside tampering by politi­ cal and other external forces. To be effective as a decision-making planning tool, environmental impact assessments must be replicable by different analysts and must be able to withstand scrutinity by various interest groups. Moreover, provision must be made for periodic updating, refinement, and modification of the methodology to incorporate experi­ ence gained through practical application.

5. Insure Input of Required Expertise

A methodology must be designed to insure input of sound, exper­ ienced, professional judgment into the impact-assessment process since subjectivity is inherent in many aspects of environmental evaluation. Input of required expertise can be achieved both through the design of the methodology itself and through the specification of the rules 38

TABLE 5— Continued

governing its use. The methodology must be interdisciplinary since environmental concerns related to resources, living organisms, and peo­ ple require a broad range of talents and disciplines for analysis— in­ cluding the physical, biological, and social sciences.

6. Utilize the State of the Art

The methodology must use the state of the art, drawing upon the best available analytical techniques. It is important that techniques selected for use in an environmental assessment methodology have a well- founded theoretical basis, and if possible, demonstrated workability through empirical testing.

7. Employ Explicitly Defined Criteria

Evaluation criteria and values (for ranking, rating, etc.) should not be arbitrarily assigned. The methodology must provide expli­ citly defined criteria and procedures for using these criteria and also document the rationale upon which the criteria are based.

8. Assess Impact Magnitude

The methodology must provide a means for predicting specific levels of impact that will occur in key areas of environmental concerns for each alternative and not merely a way of identifying the alterna­ tives with least or greatest impact on relative basis only.

9. Assess Total Impact

The methodology must provide a means for aggregating multiple individual impacts to assess overall total environmental impact for each alternative under investigation.

10* Detect Environmentally Sensitive Areas

The methodology must provide a warning system of potential im­ pacts of great magnitude or intensity which might be confined to a nar­ rowly defined scope of the environment or to highly local geographic areas. For such areas the sheer Intensity or magnitude of impact may justify special attention in the planning process, regardless of how narrowly the impact might be felt. 39

TABLE 6

ENVIRONMENTAL ASSESSMENT METHODOLOGIES EVALUATED®

Key Methodology Identification and Reference

1 R. T. Eckcrirodo, "Weighting M ultiple C riteria," Management Science. Vol. X II, No. 3 (1965).

2 R. A. Lamanna, "Value Consensus Among Urban Residents," Journal of the American Institute of Planners, Vol. XXX, No. 4 (1964).

3 C. E. B. McKcnny, ct al., "Interstate-75) Evaluation of Corri­ dors Proposed for South Florida," University of Miami Center for Urban Studies for Florida Department of Transportation (1971).

4 R. W. Baker and J. D. Crucndlcr, "A Case Study of the Milwaukee- Crccn Bay Interstate Corridor Location" (paper presented at Highway Research Board Sumner Meeting, 1972).

5 D. S. Lacato, "The Role of Resource Inventories in the Highway Route Selection Process" (ithAca, N.Y.i Department of Conser­ vation, Cornell University, 1970).

6 lan McHarg, "A Comprehensive Highway Route Selection Method," Highway Research Record 246 (196B).

7 A. K. Turner and I. Hausmsnls, "Computer-Aided Transportation Corridor Selection in the Cuclph-Dundas Area, Ontario, Canada" (paper presented at High Research Board Summer Meeting, 1972).

6 L. B. Leopold, et a l., "A Procedure for Evaluating Environmental Intact," U.S. Geological Survey Circular 620 (L969).

9 M. L. Manhelm, et a l., "Community Values in Highway Location and Designi A Procedural Guide" (Cambridget Urban Systems Labora­ tory, MIT, fo r Highway Research Board, September, 1971).

10 Jens C. Sorensen, "A Framework for Identification and Control of Resource Degradation and C onflict in the M ultiple Use of the Coastal Zone" (unpublished M.S. thesis, Department of Landscape Architecture, University of California, Berkeley, 1971).

11 A* D* L ittle , Inc., "Transportation and Environment, Synthesis fo r Actiont Impact of NEPA on the U.S. Departmentof Transpor­ tation" (1971).

12 V. G. Atkins and D. Burke, "Social, Economic, and Environmental Factors in High Decision-Making" (Texas Transportation Institute fo r Texas Highway Department, October, 1971).

n A detailed discussion of each methodology shown in Table 6 la presented in Appendix A. 40

Methodology Identification and Reference

13 Highway Research Section, Engineering Research D ivision, Wash­ ington State University, "A Study of the Social, Economic and Environmental Impact of Highway Transportation F acilities on Urban Communities,*' fo r Washington State Department o f Highways (1 9 6 8 ).

14 M. H ill, "A Method for Evaluating Alternative Planst The Coals- Achicvement M atrix Applied to Transportation Plans" (unpublished Ph.D. dissertation, University of Pennsylvania, 1966).

15 C. E. Klein, "Evaluation of New Transportation Systems," Defin­ ing Transportation Requirements—Papers and Discussions (Ameri­ can Society of Mechanical Engineers, 1969).

16 C. H. Oglesby, C. Bishop, and C. W illeke, "Socio-Economic and Community Factors in Planning Urban Freeways," Stanford Univer­ sity research project for C alifornia Transportation Agency (October, 1969),

17 Southeastern Wisconsin Regional Planning Conmlssion, "Land Use Transportation Study—Forecast and Alternative Plans 1990," Plan Report No. 7. Vol. II (June, 1966).

16 J. A. Dearlnger, "Esthetic and Recreational Potential of Small N aturalistic Streams Near Urban Areas" (Water Resources In s ti­ tute, University of Kentucky, A pril, 1968).

19 Norbert Dee, "Environmental Evaluation System fo r Water Resource Planning" (Battelle - Columbus Laboratories for the Bureau of Reclamation, U.S. Department of the Interior, January, 1972), i 20 Institute of Ecology, University of Ceorgia, "Optimum Pathway M atrix Analysis Approach to the Environmental Decision-Making Process" (1971).

21 G. T. Orlob, et a l., "Wild Rlverst Methods for Evaluation" (Water Resources Engineers, Inc. for the U.S. Department of the Interior, October, 1970).

22 L. E* Walton and J* E. Lewis, "A Manual for Conducting Envlron- mental Impact Studies" (V irginia Highway Research Council, June, 1 97 1).

23 P. H. Lewis, Upper M ississippi River Comprehensive Basin Study (Washington, D.C,t U.S. Department of the Interior, 1969). 41 presents several problems* First, there is no assurance that a compre­ hensive set of all relevant impacts will be considered. Second, consist­ ency is a problem, in that different groups may elect different criteria.

Third, the approach is inefficient because of the effort involved in identifying and assembling an appropriate panel for each impact assess­ ment.

The overlay approach involves development and use of a series of maps indicating different types of environmental concerns important in different geographic areas. It is useful mainly as a screening tool for identifying impacts that are not highly site specific.

The checklist approach can be described in three closely related versions:

• The first version is simply a checklist of environmental

parameters that must be considered for possible impacts,

without any systematic guideline as to how parameter data

are used, and without any explicitly stated criteria for

determining what constitutes an impact of a given magni­

tude and what its relative importance is. The basic

value of such a checklist is therefore in identifying

potential Impact areas. For future reference, this ver- '

sion is designated as Checklist Type A.

• The second version of the checklist "methodology" is a

Type A checklist plus an overall systematic framework

regarding how the parameter data will be used in an eva­

luation, but without any explicit criteria for determin­

ing what constitutes an impact of a given magnitude or 42

what Its relative importance is. For future reference

this version is designated as Checklist Type B.

• The third version of the checklist is a Type B check­

list plus explicitly stated criteria for determining

what constitutes an impact of a given magnitude and

what its relative importance is. This general type

of methodology has the advantage of providing within

one framework a means for identifying impacts, a means

for measuring magnitude individual Impacts, and a means

for evaluating overall project Impact by aggregating

individual Lmpacts in proportion to their relative impor­

tance. This version is designated as Checklist Type C,

The advantages and disadvantages of the various methodologies were evaluated by the author using the ten desirability criteria pre­ sented earlier. The results of the evaluation are shown In Table 7, the

Methodology Summary C tart. The chart summarizes the extent to which each methodology meet t the ten basic requirements specified in Table 5.

A summary and evaluation of 23 methodologies Identified according to ten assessment "desirability" criteria was principally based on the subjec­ tive judgment of the juthor and on the judgment of selected experts work­ ing in the field of environmental assessment. More checklist methodolo­ gies were evaluated than any other type. Considerable diversity can be seen in the extent to which each methodology met the desirability criteria listed in Table 5. A review of the methodology evaluations indicates that the Battelle methodology (No. 19) and the Lewis methodology (No, 23) ranked relatively high with respect to the evaluation criteria. The 43

TABLE 7

METHODOLOGY EVALUATION SUMMARY CHART8

Methodologies Identified in Evaluation Criteria Identified in Table 5 Table 6 1 2 3 4 5 6 7 8 9 10

1 S S S N N NNN N N 2 SSS N N N N N N N 3 LLL SS N N L L S 4 L L N L L LLN N S 5 S SM N S N S N N S 6 L LN L L LL N N S 7 L L N L LL LN N S 8 S S S N N S N S NN 9 NLS NN S S S S S 10 S L L S N N N N N S 11 S SN N NN N N N N 12 s SS N N S N S L N 13 s S S NN S S S L S 14 s L N NN s SN S N 15 s S S L S L LLSN 16 s S N NN S S N NN 17 s SN NN S NN N N 18 s SS L S L LLSN 19 L S L L L LLL L L 20 L S L SS LSL LN 21 SSN L S L L N N N 22 NN S LS N NS N N 23 L SL LL LLL L L

Key: N = Little or no fulfillment. S ■ Requirement fulfilled to some extent. L « Requirement fulfilled to a large extent.

Relative rankings were performed subjectively by the author and environmental experts from the Environmental and Land Use Planning Section and the Regional Centers Program, Battelle Memorial Institute. 44 high rank is to be expected since these methodologies were developed recently after passage of NEPA in 1969 and also have the advantage of incorporating many of the better elements of the earlier assessment methodologies reviewed. Elements from both the overlay approach and the checklist approach are used in the industrial land use planning model presented later in this dissertation.

Linkages Among Economlc- Environmental Models

The study of economic development and its relationship to envi­ ronmental quality has most often been approached by analyzing environ­ mental considerations separately from economic considerations. Individ­ ual environmental factors such as air, water, and solid waste have also been treated separate from one another. In many studies partial equi­ librium analyses have been used. As Ayres and Kneese state "the partial equilibrium approach is both theoretically and empirically convenient, but ignores the possibility of important trade offs between the various 21 forms in which materials may be charged back to the environment."

Recent attempts at model development have recognized the limited value of this partial perspective and have suggested the use of input-output 22 techniques for coupling environmental factors into economic analysis.

21 Robert V. Ayres and Allen V. Kneese, "Production, Consumption, and Externalities", American Economic Review. 59:3 (1970), pp. 284-285.

alter Isard, Ecologlc-Economic Analysis for Regional Develop­ ment (New York: The Free Press, 1972). Harry W. Richardson, Input-Outnut and Regional Economics (New York: John Wiley & Sons, 1972), Wassily Leontlef, "Environmental Repercussions and the Economic Structure: An Input-Output Approach", A Challenge to Social Scientists (Tokyo: Asahi, 1970), pp. 114-134. AS Description of the Input-Output Methodology. Input-output is a method of analyzing the transfer of goods and services between various sectors of an economy. Basicallyt the input-output table is a matrix of rows and columns, each headed by a specific classification or sector.

The sectors are classified as agriculture, mining, manufacturing, etc. and are listed as column headings and as row designations in the two dimensional matrix. Each intersection of a row and column has an entry which indicates the amount of input the row headed "sector" must provide in order to produce the column headed "sector output." Reading down the columns, the entries indicate the amount of inputs the row headed

"sector" requires from the specific row headed "sector." These direct requirements arc called the transactions matrix. In developing techni­ cal coefficients, the direct requirements are divided by the total out­ put of the column headed "sector" under which they fall. The coeffi­ cients indicate the percentage of a column headed "sector's unit" provided os inputs by the corresponding row headed "sector."

If a given sector increases its output, it must then increase all its inputs proportionately. However, each sector which expands its own output to satisfy another sector's input demands generates its own demand for additional inputs. The effects of the changes in demand re­ verberate throughout the whole system until finally another equilibrium point is achieved. The total change in the economy is the sum of these direct effects plus all the indirect effects. To estimate these changes it is necessary to Invert the technical coefficient matrix by matrix algebra and to sum the column elements to develop a local multiplier associated with a unit change in the column headed sector's output. 46

Mathematically the relationships in the input-output table may be repre­

sented as follows:

X^ ** total output of sector i

Xjj “ output provided by sector i tosector j

alj “ percentage of sector i total output provided to sector j;

a ij

Y^ “ exogenous demand for output of sector i.

In matrix formt the output of sector 1 is equal to:

Xl “ X 11 + X12 + * * * + Xln + Y1

X - X , + X - + . . . + X + Y n nl nz nn n

Substituting a ^ for —XiJ and transposing terms we get:

Y1 “ X1 " aU Xl " * * * alnXn or

Y 1 " (1 “ all) (X1J " * ’ * " alnXn

In matrix notation the above is written as: — — 1 - a • ft • Y1 11 'In xi • • • . • • ■ • • -a . . . 1 - a X Yn nl nn n - - • a . 0 • or Y « (I - A) X, where I 1 • the matrix of • called the technical • • . 1 coefficient matrix. 47 Extension of Input-Output Analysis, Several recent attempts have been made to extend the input-output methodology beyond economic relationships to account for environmental relationships within an eco­ nomic framework. For example, John Cumberland adds "rows and columns to the traditional input-output table to identify environmental benefits and costs associated with economic activity and to distribute these by 23 sector." Benefits are entered in rows added to the inter-industry matrix, and costs are added as columns to the right of the inter­ industry matrix. The costs and benefits are represented by as many rows and columns as necessary to include all the environmental factors find resource units under consideration. The Cumberland model attempts to translate environmental effects, such as air pollution, water turbidity, etc., into monetary costs. The translation requires a subjective evalua­ tion and assignment of monetary costs to qualitative changes which have not been priced by the market mechanism.

Walter Isard has developed a comprehensive formulation of eco­ nomic and ecological systems with both the intro- and inter-system rela­ tionships. The Isard model is composed of four matrices grouped in two rows, two matrices per row. Richardson described the model as • . a general input-output flows matrix which includes both economic activ­ ities and environmental processes. The aggregate matrix is partitioned into four submatrices . . • The diagonal matrices contain the coeffi­ cients representing the internal structures of the economy and the

JO Harry W. Richardson, Input-Output and Regional Economics (New York: John Wiley & Sons, 1972), pp. 215-218. environmental system, whereas the off-diagonal matrices illustrate the 24 flows from the environment to the economy and vice versa."

Constructing an interrelations table for planning purposes,

Isard develops a sectoring of the ecological processes and commodities.

Geographic areas are subdivided into regions of similar environmental conditions. Each region is characterized by definite ecological proc­ esses and physical flows which are mutually dependent and operate to maintain life and regenerate vital nutrients. Thus, he identifies such major regions as Land and Marine.

Next, Isard identifies the ecological relationships between the regions. The study of "food chain" relationships can provide an under­ standing of energy flows not only between organisms but also between regions. So also can the study of "biogeochemical cycles" trace the flow of abiotic substances essential for organic growth through more or less circular paths between organisms and the several regions of the environment. Table 8 illustrates* how interrelationships between regions can be displayed in a manner helpful for the description and analysis.

The table postulates three main regions based upon gross simi­ larities of environmental conditions: land, marine, and air. The three regions may be further subdivided into zones, each having a high degree of identity in terms of geographical location and ecological processes.

For example, the marine region might be subdivided into two subregions: open water and intertidal. In turn, each of these subregions may be further subdivided into zones of similar environmental conditions,

^Walter Isard, Ecologic-Econoroic Analysis for Regional Develop­ ment (New York: The Free Press, 1972), p. 59. 49 depending on the requirements of the particular problem being investi­ gated. Similarly, the zones may be subdivided into ecologic and economic sectors.

TABLE 8

INTERRELATIONSHIPS AMONG REGIONS

Land Marine Air (i zones) (j zones) (k zones)

Land Effect of Effect of Effect of (i zones) land processes marine processes air processes on land processes on land processes on land processes

Marine Effect of Effect of Effect of (j zones) land processes marine processes air processes on marine processes on marine processes on marine processes

Air Effect of Effect of Effect of (k zones) land processes marine processes air processes on air processes on air processes on air processes

Source: Walter Isard, Ecologlc-Economlc Analysis for Regional Develop­ ment (New York: The Free Press, 1972), p. 59.

Isard summarizes the organization of the interregional economic- ecologic activity as shown in Table 9.

Two problems of the Isard model discussed by Richardson are (1) data availability for the ecological system and (2) the validity of fixed coefficients in the ecological system and in the economic- 25 ecological interactions. Data problems arise when one considers the less than perfect understanding of the ecological system and its inter­ nal relationships. Fixed coefficients, an assumption of the economic

25 Richardson, Input-Output, p. 220. 50

TABLE 9

SUMMARY ORGANIZATION OF THE INTERREGIONAL ECONOMIC- ECOLOGIC ACTIVITY ANALYSIS FRAMEWORK

_1.iind Marine Zone A ••• Zone U Zone A 1 Economic Ecoloik Economic | Etologic 1 1 t 1* l it l i l l e i h l l l b.ZSE* Jll5 l u v Atricviiurc : | | MtnufKtutini { Scnkti * “ Gotttnmtni ! i Clinuit i < 1. GtoJoir t ■fc fh|’l*o*«phr 1 Zone A Zone £ llrdralaor • •5 M U PUnU i • Animiti • • * i i v Ajnnilturt | i * * | Mtnur*clunni I * i B Scntoi j w Oovttnmtni | V Climiu | 1 _! ' Gcoto|)r j u ftifMOtriphr j 1 Zone Zone J llrdioiogr 1 4 * 5 M i j | FUflll | I Animiit 4 i i u A|rKUtiuii i 4 i i I Mtnuliciunni i | Vrrvkri i ! 1 1 w Gotrrtftmenl I i J_l ■ u A c ChmiM Godtatjr 1 v hniiotriphr i 1 Zone £ Hrtftnlo*! l . «S M l j rwiu i , 1 Aim milt I

Source: Walter Isard, Ecologic-Economlc Analvata for Reelonal Development (New York: The Free Press, 1972), p. 60. system, may not ba valid for the ecological system as many of the rela­ tionships within that system and between that system and the economic system are nonlinear and cannot be incorporated into the input-output scheme.

Leontief has extended the input-output formulation in attempting to reconcile the incompatibility between environmental and economic var-

96 iables. In the Leontief model sectors of the economy are listed across the top of the table and inputs and pollution output are listed down the side of the table. The columns in this table cannot be summed vertically because all elements of the table except pollution output are in dollar terms while pollution output is in physical terms. Richardson points out another distinction of the Leontief model is the pollution abatement industry's "output is recorded in physical terms (i.e., amount of pollutants eliminated “ negative output of pollutants) and in mone­ tary values (i.e., in terms of the cost of inputs from other industries and value added). This double valuation enables the monetary cost of 27 eliminating each unit of pollutant to be estimated directly."

A modification of the Leontief approach was developed by Laurent and Hite. This model is composed of an Interindustry matrix, a local use matrix, an export matrix, and an ecological matrix. Essentially the model shows the physical change in the environment per dollar change in output of a given sector of the economy. Laurent and Hite derive the inverse of the interindustry matrix (I - A)"* and then postmultiply the 52 environmental matrix by that inverse. The environmental matrix is one in which industries are listed across the top of the table and natural resource inputs and waste emissions are listed down the side of the table. The coefficients in this matrix are inputs/outputs per dollar of gross product. The multiplication results in a matrix of environ­ mental impacts including both direct and indirect changes, associated with changes in the industrial sectors. This matrix of environmental impacts is then divided by the local income multiplier corresponding to each sector of the economy. The results are "estimates of the envi­ ronmental repercussions of one dollar's change in the local pecuniary 28 income arising from each sector."

The model developed is one approach to meeting an important re­ search need identified in the literature review— the need to incorporate environmental as well as economic factors into one planning model. The model developed and applied in this dissertation extends the input- output methodology to incorporate (1) natural resource input require­ ments and (2) waste emission characteristics of industrial processes.

By incorporating these factors into one framework, the model can be applied to the industrial land use planning process to evaluate the economic and environmental impacts and trade offs resulting from indus­ trial land use planning decisions*

28 Eugene A. Laurent and James C. Hite, Economic-Ecologlc Analysis in the Charleston Metropolitan Region; An Input-Output Study. Water Resource Research Institute (South Carolina: Clemson University, 1971), pp. 71-72. CHAPTER III

THE CONCEPTUAL MODEL

Restatement of Problem

The development planner who designs and implements industrial development programs must decide (1) which Industries to attractf (2) what will be the regional economic and environmental impact from locat­

ing these industriest and (3) where should the Industries be located

spatially within the planning region to assure high economic gain and minimal environmental degradation. These decisions will have specific economic and environmental effects both at the county (regional) level and at the site (local) level*

Ayres, Kneese, Richardson, and others have Identified the need

to develop and operationalize a planning methodology for analyzing the economic and environmental trade offs from industrial land use planning decisions. The methodology developed in this dissertation is one ap­ proach for conducting the trade off analysis between economic gain and

environmental degradation within a land use planning framework* The methodology is designed to simulate the impact of the three-step indus­

trial location process discussed above. The model assumes that one or more industrial location proposals have been made, and the development

planner must evaluate and respond to these proposals. The development

53 54 proposal contains a specified type of industrial activity as well as a proposed location or site for the activity. The planner must eval­ uate the merits of the proposal in terms of its economic and environ­ mental impact on the county (region) as well as its specific impacts at alternative sites (locations) within the planning space. Based on these analyses, the planner must decide to recommend acceptance or denial of the development proposal. The model suggested in this chap­ ter is designed to help the development planner evaluate the impact of such planned industrial land use changes.

Overview of the Conceptual Model

Many researchers have approached the subject of economic development and its relationship to environmental quality by analyzing environmental considerations separately from economic considerations.

The work of Cumberland, Isard, Leontief, and others, reported in

Chapter II, indicates a growing trend to using general equilibrium models for representing the relationships between environmental and economic factors in a planning region. Preliminary attempts have been made by these authors at incorporating selected environmental parameters into an input-output analysis. The land use planning model suggested here combines the economic and environmental factors into one model and represents one approach to broadening the traditional land use planning model. 55

The work done by Leontief* and later modified by Laurent and 2 Hite has four characteristics that limit its usefulness for land use planning. The approach (1) is economic and not spatial, (2) develops aggregate pollution loads from the total economy and does not disaggre­ gate the pollution streams associated with Intersector trading, (3) does not Incorporate site-related locational factors important for land use planning, and (4) the models require primary data.

The model developed in this research has four improvements over the work completed by Leontief, and Laurent and Hite reported above.

Each Improvement is important in land use planning. First, the model incorporates natural resources input variables important to land use planning, such as total land area, building site area, water Intake re­ quirements, etc. Second, the model Incorporates pollutlon-emission variables for each sector and simulates the intersector pollution ef­ fects by tracing the forward or backward linkages between sectors. Both of these improvements are part of a regional analysis. Third, the model incorporates a suitability index to help guide the spatial siting of

Industries selected from the regional analysis. The land use suitabil­ ity index is developed and applied to evaluate the suitability of alter­ native development sites for the proposed Industrial land use. Fourth, the model requires secondary data and is generally applicable.

Hfasslly Leontief, "Environmental Repercussions and the Economic Structure: An Input-Output Approach", A Challenge to Social Scientists (Tokyo: Shifeto Tsuru, Ed. Asahi, 1970), pp. 114-134. 2 Eugene A. Laurent and James C. Hite, Economic-EcoloBic Analysis in the Charleston Metropolitan Region: An Innut-Output Study. Water Resource Research Institute (South Carolina: Clemson University, 1971), pp. 71-72, 56

The land use planning model comprises two submodels as shown in

Figure 2. Submodel 1 is a Regional County Model that analyzes the eco- nomic and environmental effects on the county(s) of proposed industrial land use changes* Submodel 2 is a Site Evaluation Model that evaluates the suitability of alternative industrial sites for acconmodating pro­ posed industrial land use changes within the county(s). A detailed description of each submodel follows.

Submodel 1 Submodel 2 Regional County Model Site Evaluation Model

Regional Economic/ Detailed Land Use Environmental Impact Impact Analysis for Analysis for County(s) Specific Site(s)

Screened and Selected Screened and Selected Industries Site(s)

Match Industries With Sites

FIGURE 2. SIMPLIFIED STRUCTURE OF LAND USE PLANNING MODEL i

Regional County Model (Submodel 1)

« The Regional County Model (Submodel 1) is based on an expanded input-output methodology that incorporates both economic and environ­ mental factors in the input-output framework. The factors incorporated in the submodel represent (1) natural resource input variables 57

(requirements) as well as (2) pollution emission variables (effluents)

for each industrial classification included in the input-output table.

The basic justification for this approach is that many environ­

mental goods are not bought and sold in markets and thus, these goods 3 are not priced and easily traded off with economic factors. Ayres,

Kneese, Boulding, and Isard have recognized the need for a general equi­

librium model. A general equilibrium approach conceives of materials moving from the environment into the processing sector of the economy,

changing forms, and being deposited back into the environment. The eco-

logic system consists of a large number of interdependent activities in­ volving os inputs and outputs many commodities none of which are uti­

lized by the economic system. As suggested by Isard, et al., these com­ modities serve as inputs into the economic system and exports from the ecologic system.^ In other words, the material flow can be seen as a special type of import-export activity or intersystem trading between the economy and the environment. The approach is expanded into a gener­ al model of economic-ecologic linkages by conceiving of natural re­ sources Inputs and pollution emission exports as additional elements within the Leontief general production framework.

As in the Leontief approach, the model developed in this disser­

tation divides the economy into exogenous (external) and endogenous

(internal) activities. The economy is further broken into a processing

3 Laurent and Hite, Economic-Ecologic, p. 11.

^Walter Isard, et al,, "On the Linkages of Socioeconomic and Eco­ logic Systems", Regional Science Association Paper. Vol. XXI (1967), pp. 79-83. 58

sector (endogenous), and final demand and primary input sectors (both exogenous)* Goods are being purchased for final consumption (e.g., goods going to final demand) or for intermediate use in producing other products within the processing sector. The decision as to what is classified as exogenous is somewhat arbitrary and depends on the purpose of the study. For example, the model can be structured as a completely closed system, or it can be very open with extensive interaction between the local economy and the surrounding economy. In a closed Leontief model, all elements are endogenous— that is, there are no imports or exports. it the table is open, exports, imports, and factors such as households and government activities will be excluded from the process­ ing sector. Submodel 1 has three components, (1) an interindustry matrix (A), (2) a natural resource input matrix (G), and (3) a pollution emission output matrix (E), os shown in Figure 3.

A standard interindustry input-output matrix, called the A matrix, contains a row and column for each industrial sector in the economy. Each cell contains the amount (measured in dollar values) of the output of the row industries required to produce one dollar's worth of gross output by the industry heading the column. The a is the flA amount of output of A required to produce one dollar of gross output by

A, a ^ is the amount of output of A required to produce one dollar of gross output of B, and so on.

The G matrix shows the amount (in physical units) of various types of natural resource inputs required to produce one dollar's worth of gross output by the industrial sectors in the A matrix. If G^ is A B C ... N

A • • • a aaa aab an

B aba Interindustry • Coefficients A “ • Matrix

•

N ana

# * • Gi 8la elb 8ln

G2 82a Natural Resource Input •• • • Matrix

«

Gm ®ma

• • • E1 h *k

• • • eal ea2 eak

eb2 Pollution • Emission E ■ • Matrix •

enl

FIGURE 3. CONCEPTUAL STRUCTURE OF SUBMODEL 1 60 land, then g^a is the amount of land service required to produce one dollar of gross output by A, and so on*

The E matrix is analogous to the G matrix, except it shows the pollution emissions or exports to the environment from the various indus­ tries in the A matrix. The E matrix is read in muchthe same way asthe other two matrices. If E^ is sulfur dioxide, then eQ^ is the amount of sulfur dioxide associated with one dollar of gross output by sector A, and so on.

The operational advantages of the modified model relate to the size of the G and E matrices. One may have n number of industrial sec­ tors in the A matrix, n number of natural resource imports in the G matrix, and K number of pollution emission exports in the E matrix.

These numbers are not constrained (or expanded) by an ecologic inter­ process matrix as proposed by Isard.'’ Hence, one can specify the economic-ecologic linkages at any level of aggregation desired.

The model suggested still assumes linear processes (constant coefficients), but the approach makes the assumption easier to deal with since the environmental parameters included in the model are limited to physical parameters. The relationship between environmental pollution and ecologic productivity is not well understood; however, many ecolo­ gists believe that this relationship is not linear.^ Rather, it is be­ lieved that ecologic species have "threshold levels" above or below

5 Walter Isard, Ecologlc-Economlc Analysis for Regional Develop­ ment (New Yorkt The Free Press, 1972).

^Personal interviews with ecologists at The Ohio State Univer­ sity and the Battelle Memorial Institute. 61 vhlch the Linearity assumption does not apply. Empirical data is notice­ ably absent in this area. The linearity assumption is more reasonably applied to physical parameters than to ecologic parameters. For example, it is more reasonable to assume that physical parameters such as water use or BOD output will vary proportionately with industrial output, than it is to assume that ecologic parameters such as aquatic life will vary proportionately with BOD output. A discussion of the linearity assump­ tion for the physical parameters used in this model is presented in

Chapter IV and in Appendix B.

An expanded economic-environmental matrix for Submodel 1 is shown in Figure 4. With reference to this figure,

Ajj “ q ^* (i, J*l,2, • • ., n) where

A^j is any element of the A matrix,

Yjj are elements of matrix Y in Figure 4, and

Oj is the total output of the sector groups in Figure 4.

In other words, in order to produce a dollar of output, industry group j needs to purchase A^j of input from industry group i, and employ

Pj/Oj of primary economic inputs, E^/O^ of natural resource imports, and import M^/Oj of economic inputs from outside.

For estimating the total effect, which includes not only the direct effect resulting from succeeding rounds of buying and selling activities between the different industry groups in the region, but also indirect effects, the following reasoning is usedt 62 Using the notation of Figure 4,

AU Oj and, Oj » + Cj + Ej + Xj , but A^j . 0^ " Y^jj therefore

(AtJ . 0j> + Cj + Ej + Xj - 0j ,

Cj + Ej + Xj - (L - A£j) Oj , and

(Cj + Ej +Xj) (L - A y )"1 = Oj , vhere 1 is a unit matrix with the same rank as A.

Thus, one first calculates (1 - A)~\ which is known as the

Leontief inverse matrix. The total effect of local users on the sector groups may be obtained by the following computations.

CJ *l * AiJ* The total effect of the outside region is

XJ (1 ’ Alj) l The total effect of pollution emission exports

Ej (1 - A y ) ' 1 .

Conceptually, it Is useful to conceive of Submodel 1 in this form fitting within the Leontief system. Submodel I was programmed for automatic data processing on a CDC 6400 computer. The basic Leontief inverse routine was incorporated into the program package and was coupled with a program for simulating the addition of an industrial plant to the core study area. Total Other Resource Economii Inputs Imports Imports Inputs neidsr arx s Eprs xot Output Exports Exports Use Interindustry Matrix IUE4 EXPANDED ECONOMIC-ENVIRONMENTALFIGURE 4. P1 i M Ei Ni MATRIX FOR SUBMODEL1 oa Eiso Other Emission Local CJ Pollution Ej • J°j XJ . 1 63 The output from Submodel 1 is used to develop a regional assess­ ment of the economic and environmental consequences of locating a speci­ fied industry or series of industries in a given planning region. By conducting a comparative analysis of the impacts from alternative indus­ tries, the development planner can select the industry(s) that provides the best economic consequences and least environmental damage to his region* Submodel 1 develops this type of comparative analysis. The information is used to develop environmental and economic profiles for each class of industry in the input-output table according to the cri­ teria shown in Table 10* 4

TABLE 10

CRITERIA USED TO DEVELOP INDUSTRY PROFILES

Environmental Profile Economic Profile

Air pollution potential Job generation potential in the sector Water pollution potential Job generation potential Solid waste potential^ outside the sector

Water demand potential Value added potential

Land consumption potential

The environmental profile is developed by classifying each indus­ trial group in the table according to a scale of high, medium, and low pollution potential on each of the above criteria. Similarly, the eco­ nomic profile is developed by classifying each industrial group in the table according to a scale of high, medium, and low economic potential on each of the criteria listed. The profiles provide a comparative 65 basis for evaluating the regional impact of proposed industry and pro* vides input to Submodel 2, the Site Evaluation Model*

Slte-Evaluatlon Model (Submodel 2)

The Site-Evaluation Model (Submodel 2) is an empirical model that evaluates the environmental and economic suitability of alternative industrial sites for accommodating proposed industrial uses. The evalua­ tion is conducted by constructing a series of descriptive map overlays and an associated suitability index.

The construction of assessment indices has been suggested by several researchers whose work is reviewed in Appendix A. The Appendix includes recent attempts to develop and apply environmental assessment methodologies many of which feature environmental indices. Orlob, _et alt proposed the use of a cost/benefit ratio for evaluating monetary and nonmonetary aspects of Wild River preservation and development. The work is based on the premise that all evaluations must ultimately be reduced to a benefit/cost ratio because this indicator has become so Q ingrained in our decision-making processes. Leopoldf et al., proposed a matrix system for use in assessing environmental impacts; however, the system is more an inventory or cataloging system than an overall evalua­ tion system. The system is based on a two-dimensional matrix containing

8,800 cells defining potential environmental impacts. Several other

^Gerald T, Orlob, et al,, Wild Rivers Methods for Evaluation (Sacramento, California: Water Resources Engineers, Inc., October, 1970). O Luna B, Leopold, Frank E. Clarke, Burce B. Hanshaw, and James R. Balsley, A Procedure for Evaluating Environmental Impact. Geological Survey Circular 645, U.S. Geological Survey, Washington, D.C. (1971). 66 impact assessment methodologies are discussed in Appendix A. These methodologies were reviewed to identify environmental assessment cri­ teria that were used to evaluate suitability in Submodel 2. The cri­ teria identified are suggested as a means for evaluating a particular site's suitability for proposed industrial land uses changes.

Candidate Criteria for Developing Suitability Overlays and a Suitability Index

Suitability is defined as the degree to which the natural and man-made qualities of a location are economically and environmentally suited for a proposed industrial land use. Economic suitability ad­ dresses the features of the land that make it expensive or inexpensive to develop. Theoretically, a developer can overcome any resource prob­ lem. However, the incentives would have to be high for a firm to locate and build on a site with low industrial suitability. Environmental suitability addresses the effect that a land use has on environmental quality. In the evaluation, consideration is given to the physical features of land, water, and air, and also to the ecological and aes­ thetic features.

The literature reported on in Appendix A was analyzed to lden- tify several candidate criteria to be used in Submodel 2 to evaluate the economic and environmental suitability of potential industrial develop­ ment sites. While the studies discussed in the Appendix identify well over 100 economic and environmental criteria, the candidate criteria identified for use in this research were limited to those that (1) had particular relevance to the case study area and (2) were criteria for 67

which secondary data were readily available in order to minimize the

requirements for primary data collection* The criteria selected for

consideration in this research are presented in Table 11. Each of the

principal criteria listed have been subdivided into several specific

critera. The specific criteria were evaluated subjectively to assess

their (1) economic suitability and (2) environmental sensitivity to

industrial development. The reciprocal of environmental sensitivity was

judged to be environmental suitability for industrial development.

The criteria identified are used to (1) describe the economic

and environmental characteristics of the study area and (2) to display

the characteristics of the study area on a series of map overlays that

are used in the Site-Evaluatlon Model.

The overlay approach has been suggested by researchers in trans­

portation and natural resource planning. A qualitative overlay approach was developed and used by McHarg to identify transportation corridors 9 suitable for highway development. McHarg attempted to identify com­

ponents of social valuef natural resources, and scenic quality and to

locate these components geographically using a series of map overlays

in order to identify highway corridors of minimum social cost and mini­

mum physiographic obstruction. The sum of least social cost and highest

benefit alignment were identified as the preferred corridors for future

highway development.

A second overlay approach that is more quantitative in nature was developed by Lewis and applied to his landscape inventory work in the

9 lan McHarg, "A Comprehensive Highway Route Selection Method," Highway Research Record 246 (Washington, D.C.: U.S. Department of Trans­ portation, 1968). TABLE 11

CANDIDATE SUITABILITY CRITERIA CONSIDERED FOR SUBMODEL 2

Economic Criteria Significance of Criteria to Site Development

1. Existing Land Use Affects land prices and limits type of development since planning goals generally stress compatibility between ad­ joining land uses. Also if existing uses include struc­ tures that must be removed demolition may be required that would increase site preparation costs.

2. Utilities Affects site preparation costs since basic utility serv­ ices are required for development.

3. Transportation Facilities Affects access to labor pool and resource imports; af­ fects distribution of produced goods and services to markets.

4. Landforms Affects site preparation cost to improve drainage, level land, or stabilize site.

5. Topography/Slope Affects site preparation cost since excessive relief may cause erosion and/or require excavation; too little re­ lief causes flooding and poor drainage.

6. Soil Type Limits load bearing capacity for structure; limits ground water availability and effectiveness of sewerage disposal systems; affects value of land for farming.

7. Zoning Affects type of land use since zoning stresses compati­ bility between neighboring land uses. TABLE 11— -Continued

Environmental Criteria Significance of Criteria to Site Development

8. Geology Affects soil types and flora; affects ground water re­ charge; affects ability to support man-made structures.

9. Landforms Provides habitats for fauna and flora; affects aesthetic quality of visual environment.

10. Forests Provides habitats; affects soil erosion and runoff char­ acteristics.

11. Wildlife Habitats Provides food and shelter for wildlife.

12. Air Quality Affects human and nonhuman ecology; affects aesthetics of region.

13. Watershed Water Resources Affects water availability and quality important to human and nonhuman ecology; affects aesthetics of region. 70

Upper Mississippi River basin.^ The Lewis approach utilizes a resource value point system to associate quantitative rankings to landscape fea­ tures subjectively judged to have importance for recreation planning.

Lewis applied his overlay technique to the Wisconsin landscape in order to identify "environmental corridors" that have high natural resource potential for recreational development.

The overlay approach was selected for use in Submodel 2 because it facilitates the presentation of a large mass of diverse data in a simple visual display. By overlaying these displays, the researcher can illustrate the geographic relationship between the various data sets which is not as easily accomplished using numerical or descriptive analysis procedures.

Each overlay developed in this research displays the spatial distribution of one economic or environmental characteristic of the study area. The display of this information is useful in and of itself; however, the real power of the approach used in Submodel 2 is realized by superimposing series of overlays over a base map of the region. This approach develops an integrative display of the study region that iden­ tifies those sites that have the highest economic and environmental suitability for industrial development*

A numerical scale was devised in order to quantitatively evalu­ ate the suitability of sites according to the criteria used in the analysis. A three-point scale was used to evaluate suitability.

l0Phliip H. Lewis, Upper Mississippi River Comprehensive Basin Study (Washington, D.C.s U.S. Department of the Interior, 1969), 71 Criterion Scale Interpretation of Scale

1 Low Suitability

2 Moderate Suitability

3 High Suitability

The scale was used to develop a series of map overlays describ­ ing the economic and environmental suitability of, alternative sites for industrial development. The scale used in the overlays was converted to a quantitative index. Conceptually, the suitability index can be ex­ pressed in two parts, which represent environmental suitability and economic suitability. For example, the environmental suitability index would be computed as follows:

EVS = EVR. + EVR- + . + EVR 1 2 n where

EVS b Total environment suitability

n a Number of environmental criteria used in evaluation

EVR b Suitability rank of each environmental criteria used in

evaluation where rank b low, moderate, or high.

Similarly, the economic suitability index would be computed as follows:

ECS = ECR. + ECR- + . . . + ECR„ 1 2 m • where

ECS 0 Total economic suitability

m b Number of economic criteria used in evaluation

ECR b Suitability rank of each economic criteria used in

evaluation.

Each suitability rank can be weighted by inserting a constant (K). 72

The composite environmental-economic suitability score (SI) for any given site in the analysis would be expressed asi

n m si «= I k . e v s , + I k , e c s , 1 1 1 1 J J

The use of the suitability overlays and index provides the planner with a tool for evaluating the comparative suitability of alter­ native development sites within the study area. The overlays provide a comprehensive visual display of the data. Theindex expressesquantita­ tively the large amount of diverse data displayed on the map overlays*

In Chapter IV a detailed case study is presented to test the usefulness of the land use planning model concept described in this chapter. CHAPTER IV

DESCRIPTION AND DATA PREPARATION FOR THE CASE STUDY AREA

Identification of Study Area

The study area selected for application of the economic- environmental trade-off model is the Charleston, South Carolina, metro­ politan area consisting of the three counties of Charleston, Dorchester, and Berkeley. A detailed description of the economic and environmental characteristics of the study region are presented in this chapter while the detailed maps of these characteristics are presented in Chapter V.

The study region contains three contiguous counties that are closely allied economically, socially, and politically with the Port of

Charleston providing the primary urban influence. The close ties among the three counties are evidenced by the fact that the counties have a central planning agency and a single chamber of commerce.

Charleston is a peninsula city bounded by the Ashley and Cooper Rivers.

However, the urban area has spread across both rivers as well as inland along the major transportation routes. The two rivers converge to form

Charleston harbor. * • The Charleston region is part of the larger Coastal Plains Re­ gion (Map 1). This larger area has been the subject of considerable research over the last ten years. The Coastal Plains Regional Commis­ sion was officially chartered in July, 1967, to Implement the intent of

73 GEORGIA

Charleston Study Area

MAP 1. THE COASTAL PLAINS REGION the Public Works and Economic Development Act of 1965.* These regions were designated because of the chronic economic distress and need for social economic development within their boundaries. As discussed by

Leven, this new concept in solving regional economic problems had its roots in the Tennessee Valley experiment of the 1930 period.

Socio»Economlc Description of the Charleston Region

The Charleston study area covers 2,614 square miles in three counties atid had a 1970 population of 336,215 (Map 2). Approximately

40 percent of the area was classified rural. As shown in Table 12',

247,000 people, or 74 percent of the population in the region, resided in Charleston County in 1970. The region’s population grew 20.5 percent between 1960 and 1970, with the highest percentage growth occurring in relatively rural Berkeley and Dorchester Counties.

The Charleston region contained 99,969 jobs in 1970, according to the Bureau of Census. The 1970 employment distribution for the re­ gion is compared with the United States and with the Coastal Plains

Region in Table 13. The Charleston region has relatively little employ­ ment in agriculture, trade, and textiles, compared to the Coastal Plains

r Region. Transportation equipment, particularly ship building, is high

*The Public Works and Economic 'Development Act of 1965 estab­ lished multistate regional commissions: Four Comers, Coastal Plains, Ozarks, Upper Great Lakes, and New England. The Appalachian Regional Commission was established under separate legislation. The Appalachian Regional Development Act of 1965. 2 Charles L. Leven, "The Big Regions," Journal of the American Institute of Planners. Vol. XXXIV, No. 2 (1968), pp. 66-80. T ake > MARK)!

ALT CD"

CD

ALT

CD

MAP 2. CHARLESTON STUDY AREA TABLE 12

GROWTH OF CHARLESTON REGION, 1960-1970

Population Percent Region 1960 1970 Change

Total 278,961 336,125 20.5

Berkeley 38,196 56,199 47.1

Charleston 216,362 247,650 14.5

Dorchester 24,383 32,276 32.4

Sourcet Department of Commerce, Bureau of the Census, Census of Population, United States, North Carolina, South Carolina, Georgia, 1970. 78

TABLE 13

EMPLOYMENT DISTRIBUTION IN PERCENT FOR THE UNITED STATES AND COASTAL PLAINS REGION, AND IN PERCENT AND NUMBERS FOR THE CHARLESTON REGION, 1970

United Coastal States Plains Charleston Region Area of Employment Percent Percent Percent Numbers

Total Employment 100.0 100.0 100.0 99,969 Agriculture 3.7 8.0 2.2 2,188 Mining 0.8 0.4 0.1 50 Construction 6.0 7.3 7.8 7,830 Manufacturing 25.9 24.7 24.3 24,334 Durables 15.3 8.5 15.9 15,909 Furniture & Lumber 1.2 2.5 1.6 1,555 Metals 3.5 1.0 1.0 1,013 Nonelectrical Machinery 2.6 0.9 0.6 598 Electrical Machinery 2.5 1.0 0.6 571 Transportation Equipment 2.8 1.5 10.3 10,259 Other Durables 2.7 1.7 1.9 1,913 Nondurables 10.6 16.2 6.4 8,425 Food & Related 1.8 1.9 0.7 717 Textile & Apparel 2.9 8.7 3.1 3,425 Printing & Publishing 1.6 0.6 0.6 624 Chemicals 1.3 1.4 0.8 754 Other Nondurables 3.1 3.5 3.3 3,268 Transportation 3.7 2.7 3.5 3,483 Communications & Public Utilities 3.1 2.8 3.3 3,346 Trade 20.1 18.9 16.4 16,375 Finance, Insurance, & Real Estate 5.0 3.7 4.1 4,053 Services 20.6 19.1 22.2 22,193 Government 11.1 12.6 16.1 16,117

Source: Department of Commerce, Bureau of the Census, Census of Population, United States, North Carolina, South Carolina, Georgia, 1970. 79 in the Charleston area as is government employment, particularly due to the presence of an U.S. Navy Base and an U.S. Air Force Base in the re­ gion. Trade and textiles are also relatively low compared to the

Coastal Plains area while year round shoreline resorts provide rela­ tively higher service employment.

The comparative economic advantages of the Charleston Region were identified in a recent report completed by Battelle in 1973. The general description of the study area (Charleston, Berkeley, and Dor­ chester Counties) as included in the Battelle report follows.

The location of this subregion (Subregion 15) is advan­ tageous in serving the industrial markets of the Northeast and Midwest. The metropolitan Charleston area also represents a considerable consumer market. Transportation via highway, rail, air, and water arc excellent except for poor coastal highways.

The subregion's labor force is very highly skilled in Charleston, but poorly skilled and educated in the outlaying parts of the subregion. The presence of the Charleston Navy Yard and other ship-building facilities account for the many skilled jobs in the subregion. Recent emphasis on developing a more balanced employment structure was necessary to offset the heavy concentration of government Jobs in Charleston which historically cause severe employment fluctuations. A strong base of support resources combined with a recently diversified economy improve Charleston's opportunities for linkage to new industries.

Two outstanding natural advantages of the subregion are its coastline and its large deep-water port* The opportunity for development in the area is enhanced by the presence of many industrial sites, especially those fronting on navigable waterways. Government planning is coordinated for the sub- region, but conflict along city-suburb lines has hampered the implementation of planning efforts.

Living conditions are very good. Shopping, recreation, and entertainment are excellent, but concentrated in metro­ politan Charleston. Medical and educational facilities in the subregion are very good. The overall environmental con­ ditions are very good, although some air and water pollution exists. 80

The ability o£ the area to attract industry is very good based on locational advantages, a very good transportation system, and excellent living conditions. The major problem hindering economic development is leadership and cooperation among governmental jurisdictions.^

The Battelle report goes on to summarize the comparative advan­ tages identified for the Charleston region (Subregion 15). The proce­ dure used to evaluate economic development potential was to develop and administer a questionnaire in a structured interview with regional planners, government officials, and industrial developers to gather their professional views of the subregion's development potential. The comparative advantages of the region were evaluated according to twelve criteria identified as being important to development. These criteria are presented in Table 14 together with their ranking for the Charleston region. The respondent evaluated the subregion on each of the criteria on the basis of "fair," "good," "very good," and "excellent." The re­ sponses from the questionnaire were averaged to develop an assessment of how industry would view the factor in each subregion if it were consider­ ing the location of a new plant in the subregion. The evaluation is subjective and is based on what industry views as the comparative advan­ tages of the subregion according to agreed upon criteria. Table 14 illustrates the relative ranking of the region's advantages according to twelve evaluation criteria selected and applied by the project team.

The region has very good comparative advantages for economic growth and has exhibited strong growth over the last 20 years. The

3 Battelle Memorial Institute, A Plan for Achieving Income Parity in the Coastal Plains Region by 1980 (Washington, D.C.: The Coastal Plains Regional Commission, 1973)7 pp. B-29-30. 81

TABLE 14

COMPARATIVE ADVANTAGES OF CHARLESTON REGION

Very Criteria Fair Good Good Excellent

Markets X Transportation X Labor X Industrial Linkages X Support Resources X Natural Resources X Industrial Sites X Development Plans X Government X Livability X Environmental Quality X Ability of Area to Attract Industry X

Source: Battelle Memorial Institute, A Plan for Achieving Income Parity in the Coastal Plains Region by 1980 (WashingtonT D.C.: The Coastal Plains Regional Commission, 1973), p. B-29. 82 diversity of the social and economic composition of the region make it an excellent area for testing the land use planning methodology devel­ oped.

Environmental Description of the Charleston Region

Environmentallyt the Charleston Region is part of the lower coastal plains region. The region has a long indented coastline which dominates the entire three-county area and is important to both the ecologic and economic vitality of the region. Cllmatologically the region is a warm temperate to subtropical zone with a 260 to 280 day growing season with an average annual precipitation of 50 inches. The three-county region is dralred by the Santee, Ashley, Cooper, Wando, and

Edisto Rivers. Surface and ground water supplies are plentiful. Total dally water use, excluding power generation and small water system use, equals 102.7 million gallons per day (mgd). A high water table is found throughout the region and potable wells average 150-200 feet in depth.

Daily demand for ground water is about 40 percent of sustained yield in the basins. The Santee, Ashley, Cooper, and Edisto Rivers form four important estuaries that indent the coastline and provide the fresh

. i water flow needed to maintain the delicate saline balance in the coastal waters zone. The fresh water flow also serves as a barrier to salt water intrusion into the ground water systems along the coastline.

Geologically, the region rises from a sea level elevation along the coast to 175 feet above MSL in the northern reaches of Berkeley and

Dorchester Counties a distance 85 miles inland. This represents an 83 average slope of 2.05 feet per mile. The area Is underlain with calcium carbonate formations including the Peedee, the Cooper Marlt the Duplin, and the Waccamaw Formations. The carbonate content of these formations

is normally less than 50 percent but some currently mined areas have contained 85-90 percent calcium carbonate.

Seismic activity is dominated by the great Charleston earthquake of August 31, 1686. Some 438 earthquakes have been recorded in South

Carolina between 1754-1971; 402 have been in the Charleston-Summervilie area particularly since the 1886 occurrence. In recent years, the

Charleston region has continued to experience numerous minor shocks which are common in the southern Appalachian region.

Soil characteristics vary widely among the three counties.

Poorly drained to moderately well drained fine tcxtured level soils characterize one-third of Charleston County while wet peats, mucks, and

loams flooded by tide water comprise a second third of the area. The

principal physiographic characteristic in the County is its nearly level

character with frequent depressions! formations along the coastline. In

Berkeley County approximately half of the soils are characterized os moderately well drained to poorly drained, slightly undulating to level

soils, with sandy clay loam to sandy clay subsoils. Much of the remain­

ing area is characterized as well drained to poorly drained loamy sand

soils with sandy clay loam to clay subsoils on narrow, nearly level

ridges and flats. In Dorchester County, some 45 percent of the area is

characterized as moderately well drained to somewhat poorly drained

soils on broad flats. Another 17 percent of the area is in moderately

well drained to poorly drained soils with sandy clay loam to clay 84 subsoils while some 11 percent is in very poorly drained soils on nearly level stream flood plains* These soil characteristics have two features important to development. The poorly drained depressions! areas are not capable of supporting ground septic systems and the nearly level topo­ graphy requires frequent pumping stations to maintain adequate pressure in municipal water and sewer distribution and collection systems.

Secondly) poorly drained areas have low load bearing capacity to support structures or related man-made facilities. Consequently! large areas in the three-county region are not suitable for intensive development.

The air resources of the region are dominated by the marine sea breeze effect and the air flow in the three principal river systems.

Air quality is generally good across the region with the most serious pollution loading occurring in the Charleston peninsula and in the North

Charleston area. Particulates and sulfur dioxide are prevalent in these two areas although the state's 1972 air pollution control plan has devel­ oped strategics for eliminating this pollution. Much of the air pollu­ tion problem is caused by the unique micro climatology of the coastal environment. On-shore sea breezes tend to blow pollutants from coast­ line industries inland or northemly up the major river valleys, which act like channels for air currents as well as water currents.

The case study area has a diversity of land resources that are important as recreation attractions as well as wildlife habitats for the region. Some of the most prominent land resources include the beaches, coastal and riverine wetlands, and extensive forests. The beaches are wide, gently sloping, and backed by parallel ridges of sand dunes.

Northeast of the Santee River, a densely forested area is a major 85 recreational resource, while southwest o£ the Santee the numerous bar­ rier beaches provide a shorebird habitat and sea turtle nesting area*

Extensive salt marshes are prevalent which are important to waterfowl.

Farther inland the fresh water marshes and associated open fresh waters have similar or higher importance to waterfowl. The riverine swamps and bottomland hardwood forests contain outstanding forest species such as the bald cypress and tupelo gum; they are major habitats for small fur bearers, resident gamebirds, m o d ducks, and alligators*

The wetlands are particularly sensitive to changes in the depth and frequency of flooding and to pollution by Industrial waste, sewage, and siltation. Losses of wetlands to date have resulted principally from agriculture drainage enterprises and flood control activities.

Construction of canals and connecting waterways has allowed saltwater penetration into freshwater lagoons and marshes; it has also produced abnormally low water tables at low tide, which is damaging during drought. Ditching for mosquito control and saltmarsh hay production has tended to reduce open water areas, thereby reducing the invertebrate population essential to waterfowl, shorebirds, and fish. Road construc­ tion has induced drainage and filling operations as well as expanded development in the general area.

The Charleston region is well suited as a case study area for this research because the area is reasonably representative economically, socially, and environmentally of a large number of "medium.size" regions along the eastern coastline. Though the area is medium size, it still presents a diversified industrial base, contains a number of extractive industries, includes a wide variety of Federal government activities, 86 and has a large potential for recreational development. Most important* ly, the area is beginning to experience strong conflicts between the various activities utilizing the coastal zone. Due to the large number of activities using the area, many of the conflicts arising are repre­ sentative of environmental problems in general and especially those occurring along the Atlantic and Gulf Coast. Because the region has been the site of historic and current conflict, several background studies have been completed on the area. These studies were collected and analyzed during the data preparation phase of the research. The following section will discuss the data collection and preparation activities required to develop the data used in Submodel 1 and Submodel 2 .

Data Preparation for the Regional Analysis Submodel (Submodel 1)

The data required to develop and utilize Submodel 1 is readily available in secondary sources. The Regional Analysis Submodel is based on an expanded regional input-output analysis. There are two basic ap­ proaches to the construction of regional input/output models: (1 ) de­ tailed surveys of Industry within the region to determine the inter-

T industry distribution of their sales and purchases, as well as their sales and purchases outside the region and (2 ) development of a regional input/output model from a basic detailed national input/output matrix and important key published data at the regional level. The latter approach was used to develop the regional table in this research. 87

The principal justification for this approach was discussed by

Boater and Martin, who compared two published input-output models, one which was a large-scale endeavor using mostly primary data sources and

the other using secondary sources (national coefficients) exclusively.

They concluded that although there are great differences in the costs

of the two approaches, there is no clear evidence that either approach

gives superior results. In fact, the results for the two studies com­

pared were not significantly different for the two methods. They

concluded:

If, as Is usually the case In regional Interindustry analysis, one is Interested in the overall structural view of the economy and the Interindependent relationships result­ ing therefrom, rather than individual lnput-output coefficients, a model developed from secondary data sources Is quite adequate and vastly less expensive than a model developed from primary data.^

Burford and Hargrave have also conducted a comparative analysis

of these two basic approaches to developing a regional lnput-output

table and have concluded:

On balance the evidence seems to Indicate that national coefficients, properly used, can serve the basis for an excellent regional I/O model. Only those local Industries which generate a significant proportion of the total re­ gional product and which are known a priori to be unique need to be surveyed individually.5

. • r Miemyk, another exponent of nonsurvey techniques, haB developed

an approach for tailoring national lnput-output tables to a regional

A Ronald S. Boster and William E. Martin, "The Value of Primary Versus Secondary Data in Interindustry Analysis: A Study In the Eco­ nomics of Economic Models", Annals of Regional Science (December, 1972), p. 44.

Roger L. Burford and Carolyn H. Hargrave, "Input/Output Models: Data and Methodology", (paper presented to the Southern Regional Science Meeting, Washington, D.C., April, 1974), p. 11. 88 scale by adjusting the national coefficients to reflect local economic relationships,** This method will be discussed in more detail in the next section.

The principal source of structural economic data currently avail­ able to researchers Is the national lnput-output table published by the

U.S. Bureau of Census for the year 1963,^ This table contains 367 sec­ tors and is the most detailed reliable source of secondary data avail­ able on the national economy. The table has been updated to the year

1967, based on procedures developed and applied by the Bureau of the

g Census. The updated table contains 83 sectors as shown in Table 15 and is the most current estimation of a national input-output table available.

Regional Input-Output Table

A regional lnput-output table was developed for the Charleston metropolitan region from the 83-sector national table. The Charleston region as defined In the table Included the counties of Charleston,

Berkeley, and Dorchester. The national table was collapsed Into a 23- sector table along the lines of the economic activities found in the

Charleston region. The collapsing process had the added advantages of

(1) eliminating many cells with zero entries caused by the absence of

^William K. Mlernyk, "Long Range Forecasting with a Regional Input-Output Model", Western Economic Journal. Vol. VI, No. 3 (June, 1968).

^U.S, Bureau of the Census, Input-Output Structure of the U.S. Economyi 1963. Vol. II (Washington, D.C.: 1969).

g For a discussion of these procedures, the reader should refer to: The Survey of Current Business (February, 1974), pp. 24-56, TABLE 15

INDUSTRY CLASSIFICATION OF THE 1967 INPUT-OUTPUT TABLES

M m < i__ W alirM atarM lI •1C Anln HHf AMIMI

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TABLE 15— Continued

TIMaUl <____ U tit ■tC ( I H f I U lia IIC IIMf rdiUoa)

1LH Howfefekyhei, am II KOI raM diH intih prawiwu, u i. J irn-i. I It 01 m t m I t U b W u 4 t f k m r fi II. M htba Matarw aal Hu b ..... mi. KOI Lau»j r*J*ra aal lma*M nmlrtt- am. ILM Atebalt Mia aal tiaUnca...... IUI to n . If Rabat* aal ulaatOtataat fuaaba l a M l b aal plaMai aittb, mm l tan. a m a«« &S(Ql 01 HotOnoO llninilM ul (aortal, T l ! t KOI TkM aal laatr tab**...... Hit MMtUI oraOMt ta ra llb , M l. . . , a«». KM Hvbbf foaavtat MU. ML01 am, KM Hartal nal mbbar aal ailaaallli liu Mil, I VmmtmO al/Mol..... am. rabbtr fnlacta, a**. S 3 fMiMMN noI ilndt a«u, KM UlMaOaaaawa *laaUn prtlart*.,... MTO. am. •I taaiba* uaaltf aal Maurttl hala Waal poOwUt a**., a«M oaalaaU MM Ualbar laaaUf aal lalaaUW 1111, IIIL H Vata aOO»w balba* oaalacu. ILK WoaMa aaauiam..., IM. M TU w a aal aibar Inlb o aralatu K M . . I IQ HOI aalaaattalamb...... UIL Bm ^B^^P^WW^BBI fu ln a i r u r k mbfcar...... KOI W aal I n h MM fira ltara...... till,ISIO. Chbt* laalbat anlataa...... J I^ IIL IIT . KM Uabobum bounball laraltan. m i l KM Maul Iw aiM I liolMia..... ail i. ilalaaa KM llllll M H am. KOI i aal gat TULKKKIL ana. ■ Otbn MOaw «M lauraa KM i aaalalai_____ •BL WaaO aAco OailLwa.Hiti* **..»■ tin, M OUaa aal tUr oaalaau sM>. & ¥9 S lal aloa finalUr*...... utt KOI Oauaat, hr ItaolM.,..... KM M M MMlai finnan.,...... aut. KM M t l aal tuwianl tiar ub..... KM a m , MM Caiali n il aal Oaga tala...... KM ■Opartltlaai aal litana...... a nt MM CUr Mranaoaa...... KM MaUI parti Uaaa aal Oitaraa...... M il, MM Oinnaral da* anaam, au . HOT Vmtlaa MUOa ul tbaln..... U 00. MM VHiaaaa plaaiMaf latana UIO Vbnttara oa4 liia m , u i ...... MOT 7«b0 KIBMIIBi ^liUfyaoaoooioiooii Otaa aaatfi a MM I tWrtiml W^flllloiotooor feaaaa JBBObCBBo 144* loooooooaoi laiimjaa a Mtaaa*l*a M l , 1 Mltk 4M Mi l l a*. «H*t OalUlai pa**. Mil. MS? i l Ii***a*taara»i Maaa afaOaaw tMT. M i a QnWtt ^MMlat . WaUgapr aal M M ai MH.MII. Mil C«( llMM 4*4 ItlH yrsOertl.a.eb, MU iiooooooiooaani HOT ton MIT Aabaataa oaalocu...... aa«M aaauuan aal baau. iB&F* Mil Q u b U aal laaalallaaa...... MIO Mlaaaal^irpal ar ma u l ..... M h a a lt a l a ia l alaua a a l baaaa KM h fo la rt aaaulaan aM boaaa., SS Naadar MM HaaurtalHa Maaaal Qw laau. aa«. M II M a n baa aal ataal uaaafttatrtaa KOI IBMBBInaaaM — *-J ^U l M^Mmm I mbk^a^B^ UL W O . 4 w KM I m MW bIBW fWlMNo*i*iiio*ii IK •TO I, KM ImiMiMtMOaw . UIL mi.ma. KM ntavr m u l y^ M O i u m boaiaaaa ianaa, blaal- mi, mi. aa* al ia ■■aalat* buba. a>< bu m . HOT Om O t f aaH raMukiaf...... mi. M O l ’ *a*aar...... *■*.*,...... MIL IMumaiibibfanhia.... m i n K i n . MM lauty Hal...... i...,. MM laiarr aM M CtiUblaialal»rtilaiiulil|aal. MM I atair alaMwaH...... M M . M M MM laair aaaltnaaa ualaK t a b . . . UK KOI " S o - * - , Inipaalt aaO atpali M l (aaaL M IK I MM ■■■■alarr aaad nau autaT IML MOT OafaurlbBiaallfael**...... Ull. S’.M.M fanUlMia...... MTI. MM AluiaUaai talllaa aal liaaia*,.... UK ’.01,M aartaallaral rtuauiaM, SOTO. N a a h m a raUai aal l r a * U | , '.M tMI.MO. MM .M Mlialliaaai cbaaUaal ail. M HaaMia aal a ra M i am r tli MIO Haalarr UIT. IbIIba KOI flauMa auirflaM aaO mlaa...... Mil. tt II Ihialaau taallaal aaaaaaaaaaa*# *+| IUI. HiatbrtM tuLbff .. ... M i l b u . bfaaw, aal up u i lauJaoi.. MM CWabula niam W Ma n ..... Stl M i l Maalm iau niUaal, aaa,...... KM OifaaM Obara, awarllvMt.. Mil. MU JIMlMfttH lB|ll^4ita**ifib(ai*t UK M Bm k *eala| aaO UOM oNoaaaOaea MaUI wa lihai KOI linaa.*...... m . M O l Mrul caaa.. MIL Cbaalai fwrparat m ...... •Hitact MM ) MM Iltul banrts Imaw, aal * a m . . . . MIL 00SI Tailat on*anU

I AL 1—Continued XABLE 15— mm i e ??????? n%* ns ss: 8 3888838 S8SS 888 88888 88: TABLE l5--Conttnued

MOUik Rfta—4__ fM*M 1__ etc *™Ra IIM f l*te>i im m iiai RIC cnl- (IMT tAUd) tOtUMl)

MM HntaM wunhtMm . Mil. eeancce n o * Atitmmitc (rm pm iitf m in li. . , n n . il>04 tetr,ft*I ta4 M tral M niwM i.., j»ti. tl lOOt mA I*0f1* | n o t *Vftnj4n>U.MT**n4nmiLn..., Ml Ram. |**u*0 fin 2»l*l fm«HM*t .*4 wppiM ...... JjOwtOr-rrter*. «u 0400 WMM**4tfiMOit*.»....,.t.i mi. M * M I* M RUIN— hr w t n n Mho *«it*M i« f m nw i...... im. •4 4*4 teO—ulte o*ri*n*l*e 4*4 04to jt n oi** int!...... ,... MM. u i O-- ■ ■ I I n n ' J ftp * n o * 3 - t4im*, M l Tf M m * ukm n I I Ml***Ba*t* 4* w f a witr**. u i . moil TIM M imMIi wytM w4 urnw**.*, n T§ 4m h b m || TPAWOtytTATTOM. COMMlWtATtOX, f e l l M*U— Rtr4an* Ill****ltl4l»»lh4l n KLKCniC. C4>. AND U M W I ItR T IC tl n n A— — 4 440 *—r| *—...... 7L I f M M M . *0— te»«l H*tte*4, 440 „ „ n Th i i i WOIi i M l n i t m l i i — — — — — — MA *4— a U a — i u a 0401 poumtO* oat Kl*ia4 *arvtn*.... 40,414 n n Itetel. MbwOM u 4 taimntaa 41. TT.OI Im w i u I 4—i—u ...... 10 L in e n , epnr iMiop iiuoM* n.n N-puk ...... *0*1. ’ T l.n Otter t ilo r t 440 *—ll> **n1*—„ o m , eer, too. n n Ifm prtUloi **4 41,474 (***L Rt. MM) f4 * < VMHuaHprteltea ...... 44 TT.04 I A*** 11*4*14*f 4(4*414. n o * iut* 4*0 i**4i *i«t<44 4iiuu**...... n o t Otter MU* * 4* latal pi*r»*M4l BUtuteoUlU** ...... iii,R4*n 5W OOlteaaaaaaaaaaaaaaaaaaaaa. 4HH.W. IMPOITO «M*f *10 MlOUfT —tete.aa,..., M 0*«4* lte 44*t44>eu l***l**w 4m n 41 tNmUl ttt—*l *4 iMRtet* .. v a o u a u s and e rr a il t ia d k I^ M iklMllMl lM^MIt4*l»i4«l4*tl*t n wt*i***ii >*e H«*e on* DFMMY IN D m tm n e t MtmLteUte __ II e**t*»-«r»rte. ateartalM.M **40

»4...... TfflSKo 0004 Ft* ottoi n n 04w*—rm — ...... T1NANCR, IH4l»ANC« AND RIAL EATATI I I * —*4. *—4 4a l 4— 44**4 4—4* n n 4p*L 4— 0 4*0 **—44*1*14—0*.. ft *i!! ...... m an iiaminuu 5» p**»r«te ...... it. ft. _ 14 C—r*—*t 1*1—*t, 5 9 RttteHr u * —u —telly bmA***... ii. n n o*>»—■—t i404»ur...... JAM I— »-amm ...... 14 M ■**• i f 1*4 OteM l 4lHW n n Im n tM m—U t*0 W iktn . 44. n n N*M*4ite**rtoi*oii*or. n B—i WO* u 4 natal „ H It— tell l*l***r JjiJI OtmmtelauWte.. n n HM-teMteOwvr.... 41•Ml), (nd. g.l The titles In bold face represent the groupings of industries used for the aunraary version of the 1967 tables and were also used in the 1958 and 1963 input-output tables prepared by the Bureau of Economic Analysis.

Source: U.S. Department of Commerce, Bureau of Economic Analysis The Survey of Current Business. February 1974, pp. 24-56 93 comparable types of economic activity on the regional level, (2) pro­ viding economic data on an aggregated basis similar to that available for environmental data, and (3) simplifying the mathematical matrix inversion operation. The survey of industries and employment levels by sector in the Charleston region was compiled from data available from the U.S. Department of Commerce and from the South Carolina State Devel- 9 opment Board, The collapsed 23 regional sectors are comprehensive and cover all possible sectors of the regional economy. The sectors and the 1970 employment for each sector are shown in Table 16.

The next step in developing the Charleston regional table was to test whether the technical coefficients in the national table accurately reflected the lntcrsector relationships for Industry in the Charleston region. As pointed out earlier by Boater and Martin, and Burford and

Hargrave, one recommended approach is to develop a table of regional coefficients based on notional coefficients, thus minimizing the need for primary data collection. A test was devised to determine the simi­ larity between the national economic structure and the Charleston economic structure. If the two economies have similar structures, then it could be readily assumed that the national technical coefficients adequately represent the local transactions in the Charleston region since the same basic relationship exists between Industry transactions both at the national and at the regional levels. However, if the structures of the two economies were dissimilar, then the national

9 Department of Commerce, Bureau of the Census, Census of Popu­ lation. South Carolina (Washington, D.C.: 1970); and South Carolina Industrial Directory 72/73 (Columbia, S.C.: State Development Board, 1972-1973). 94

TABLE 16

EMPLOYMENT BY SECTOR, CHARLESTON REGION, 1970

Sector SIC Sector Number Codes Employment

Ag., Forestry fi, Fisheries 1 0913 2,188 Food A Kindred Products 2 2031 (2011-2099) 717 Construction & Mining 3 1441, 1511-1599 7,880 1711-1799 Textile A Apparel Mfg. 4 2211-2299, 2311-2399 3,062 Lumber A Wood Prods. Mfg. 5 2411-2499, 2611-2661 2,410 Furniture A Fixture Mfg. 6 2511-2599 217 Printers A, Publishers Mfg. 7 2711-2799 ‘ 624 Chemical Manufacturers 8 2812-2899 754 Petroleum & Coal Products Mfg. 9 2911-2999 614 Rubber, Plastic A Related Mfg. 10 3011-3099 784 Stone, Clay A Glass Prods. Mfg. 11 3211-3299 1,645 Machinery & Metal Shops 12 3312-3399, 3731-3732 9,976 3411-3499, 3511-3599 Miscellaneous Mfg. 13 1911-1999, 3111-3199 1,108 2111-2141, 3911-3999 Transportation 14 4111-4721 3,483 Communication 15 4811-4833 1,208 Utilities 16 4911-4931 2,138 Eating & Drinking Places 17 5811-5891 2,470 Hotels & Lodging Places 18 7011 2,293 Gasoline Service Stations 19 5541 665 Other Wholesale & Retail Trade 20 5011-5999 (Exp 5811- 14,137 5899, 5541) Finance A Insurance 21 6011-6499 2,741 Real Estate 22 6511-6699 1,312 Other Business & Personal 23 7211-8999 18,971

Source: Department of Commerce, Bureau of the Census, Census of Popula­ tion, South Carolina (Washington, D.C.t 1970). 95

coefficients would have to be modified or adjusted to reflect the conditions in the Charleston region.

Schaffer and Chu reviewed several techniques for constructing regional interindustry models by modifying national data (Appendix C).^

One method reviewed was developed by Miernyk, who suggested the use of

location quotients based on Intersector employment relationships.^

This method was selected and applied in this dissertation. The loca­

tion quotient for industry 1 on Industry J (LQ^j), is defined as the

ratio of regional employment in industry 1 to regional employment in

industry j divided by the ratio of national employment in Industry 1 to national employment in Industry j. If UQjjet 1* the national input coefficient is considered to be representative of the region and is

transferred directly from the national to the regional table. If U)^j<1,

the national coefficient is multiplied by the location quotient to obtain

the regional coefficient, and the difference between the computed coefficient and the national coefficient is transferred to the Import row of that sector based on the assumption that deficiencies in regional

production capacity will be compensated or equalised by imports.

The regional specialisation test described above was conducting

using 1970 employment data for the nation and for the Charleston region

for each of the 23 sectors identified earlier. Uhere IQtj

^William A. Schaffer and Kone Chu, "Comparative Evaluation of Alternative Nonsurvey Techniques for Constructing Regional Interindustry Models", Papers of the Regional Science Association. Vol. XXIII (1969), pp. 83-101.

^Miernyk, "Long Range Forecasting", pp. 165-166. 9 6 national coefficient was adjusted to reflect local economic conditions.

National coefficients can thus be adjusted downward but not upward.

This procedure is followed until a complete table of direct input coefficients has been constructed for the region. The adjusted technical coefficients computed for the Charleston region are presented in Table

17, and the location quotients computed and used in the test are pre­ sented in Appendix C. A Leontief inverse routine was used to derive the inverse of the technical coefficients for the Charleston region.

The adjusted technical coefficients in Table 17 represent the economic relationship between each sector in the regional table. For example, the Agriculture, Forestry, and Fisheries sector sells goods and services to itself as well as to most other sectors in the table.

The computed technical coefficient of .3015 in the first cell indicates the amount of goods and services required by the Agriculture, Forestry, and Fisheries industries to produce a unit of output from the Agricul­ ture, Forestry, and Fisheries industry in the Charleston region. Read­ ing down the first column, each dollar of output by this sector requires direct purchases from Itself of 30 cents, 1 cent from Food and Kindred

Products, 1 cent from Construction and Mining, etc. The total inter­ mediate input of .53414 indicates how much must be bought from all sectors in the column to produce one dollar of output of Agriculture,

Forestry, and Fisheries.

The final demand per employee for the regional table was assumed to be similar to the national final demand in comparable sectors. This assumption was checked against estimates of regional output and regional final demand and was found to be acceptable for estimating the regional TABLE 17

ADJUSTED TECHNICAL COEFFICIENTS, CHARLESTON SMS A, 1970

lit 171 tit 161 191 161 171 181 191 not 1. **;. ro9C5t»r * »t9H**Trs e.ists 0.7977 0.0009 0.0317 0.0C90 0.3000 0.3C30 C.8079 0.3100 0.8309 7. r i r r t • 47*i9»»0 Mioucn o.ti** 0.1993 0.0330 O.COOl 0.0300 e.oto? 0.3000 0.0191 0.0*11 0.03*6 1. ewt«ir;ttii • .turr. s.out. 0.9333 0.0*70 0.0376 0.3016 0.CC63 c.ce39 0.0769 e.6666 0.0369 6. TfjrTHC * 4*<*1»PL *•*•= t .; t u 0.0319 0.0036 0.677* 0.0307. 0.0118 0.006* O.OC73 0.0801 a.e*G6 " o V tH 0.3814 0.3313 0.0199 0.0033 0.7791. 0.1101 O.OCOl 0.8016 3.3301 0.336* "jfui'i*; . fi'i'Pt " m 1.1C8C 0.0100 e.isii 0.0103 0.339? 0.3776 0.0(3? C.8030 O.OCOl 0.0(36 *. «1*«T£*T • 3.0*91 0.0199 0.9000. G.3J34 0.1 COS c.oroo 0.1193 0.0309 0.8301 3.0(06 c«r»ic*L •*itni7*ct*i°r*5 0.61*4 0.0090 0.0319 0.0110 0.3C09 9.0C78 0.0319 8.7938 0.8769 0.176* 9. *Tl»(lF,J“ * COlt B.B074 0.0010 3.3399 0.0131 O.OCOl 0.010? ’ 0.800? 0.0133 0.0479 3.0336 1C. n i m i • "FtiTfn 3.1019 0.0076 0.0300 0.0937 8.9(0* 0.0730 0.0(2* 0.0167 0.CC77 0.1(79 11. Z T - v r , rear, • ctoc5 r»W5 3.0*09 0.0103 0.0197 0.0371 8.1C09 0.0170 0.3003 0.0066 0.807? 0.3(51 1*. -ar-Jtr’ * . «rrat 590*5 o.ctas 0.0774 0.0796 0.0097 0.3069 0.36*9 0.0173 0.0793 0.C37? 0.07*1 13. "i-cma'iTTi^ 9j<«>»r»cTtt»X9 0.1(95 0.1110 0.0319 0.0070 c.iroi 0.9096 0.0181 0.8106 0.GC76 3.0391 lfc. T5»«-,CMrHI')|y 0.9190 0.0*70 0.0999 0.0113 0.JC36 0.0193 8.3119 0.8719 0.0919 0.01*9 1?. ri^inrciiTit 0.0019 0.0331 0.0C03 0.0117 e.OBOt O.0C19 0.806? 0.3817 0.3(99 0.3311 1». MT1L1TIE*: 9.009 0.3046 0.0361 0.03*0 0.3C33 0.0066 O.0CS9 0.0113 0.01*1 3.0396 17. n i’r, • T*ti»ir, n»cri 3.0100 0.03C3 9.0000 0.0003 0.QCBQ 0.0003 0.3bB3 S.3330 a.cioo 3.0CC1 1*. K1T£15 • llSltlf; "t«CF5 0.0031 0.0310 0.0030 0.0006 0.1000 C.0CB6 0.0016 C.8378 0.CG06 0.3311 19. casniir 5e»*tce sTtrTr,*»s 0.001 0.0S70 0.0037 0.3107 0.0319 0.0C16 0.0079 0.1(39 3.0(36 0.3(39 ot-:* «**CLrs»tf nn o.ctsa 0.0141 0.0669 6.0130 0.3799 0.0393 0.9769 0.0778 0.811? 0.035? 71. rjxa*-:*' • iHCtioancr 0.3097 0.3336 0.0066 0.0363 0.3011 0.3067 0.3061 9.0(66 0.3(93 0.836* 77. irit Ellltr 0.0917 0.33 97 0.01*7 0.0117 e.ooo? 0.013? 0.8636 C.F76* O.C7J4 0.P17* 71. MHf* » P B ifr S'1*# 3.1614 0.0696 * 0.0117 0.8193 0.3096 0.0369 0.3710 0.3973 . 0.3681 0.3669

(111 (171 111) (161 (151 1161 1171 (lot 1191 (781 1. ■*.. *9»E6t1* • rnMr»TE5 0.8C00 f.0310 0.0031 0.0005 0.3000 o.ocoe 0.0071 0.0887 0.6800 0.0131 7. e r r-} . e.ocoi 0.7003 0.8307 0.0335 0.0303 0.0030 0.0080 o.ocio 0.6000 3.3331 1. CIKU'ICTIK ♦ 0.8719 0.0315 8.(189 0.0256 8.3255 0.0919 0.0615 0.0091 0.0816 6.0012 6. U *fltr . ner. 0.0C50 0..0306 0.336* 0.0316 0.0(17 0.(£61 0.0(80 0.3055 0.6302 3.0001 9. • wan •n '1ij(T; 3.056* 0.33*9 0.3316 0.C93C 0(3030 0.0000 6.0C03 0.0C65 (.(103 0.011? **Je'IIT*fs»£ • *1 *ti|6£ .H! e.cctc 0.8331 0.0373 0.0333 0.3C03 e.oeoo 0.1C03 8.0508 0.5(00 0.00(1 7. . *

»i/eo ooauaaititoavoi

_ « H 4 0 9 0 0 «4Ci iiO M » P O *"*iJ *44 «4 * a Ha oaoe euafS o»a(K«fiaaMWi v b o o ^ aneoannpesnaon « p p i

>0O0OO«*«*' •t) bUDa«oaui G

M » M C P ft1 H & U l O M *0 U l lU M tf W d « dr M O d M I HH m u MS 0 * re Ud db| t**- ftM irC J d O d ir f.S* u. i t ft' I'jp fcl M ss ^0 0 S§£ b*J ft56. ft ft ** * 6 rjbnu Mk u •* ft d- m »- • - f u .£ r rf?£HUJ \t b ft. * i J « 4 U a ♦ o ♦* r b C d « Id W vmh«j5 M ► 0lw »_ i$wr?uE .EMC*h ssrss 0 * ir no dO« 4 * d d « C d H dr O w U d t .* * it ►- S • r «j 0 d «d C J M J ■ Id* • Id df**dlA D4« • ft fc*d iv 0 ft 0 v ft ft u! •IS B»S u r ft * b ddCHH V lw i o*» d » * > Wldl •2 dC I hUVh l | *- d*C U ft* d*b ^ ? d ^ d •Jft' S ue5 c»?r r o cr? Tt« l *t ^jdi ^ w i0y« v ~ w « m«ibJ J88 e&a E: VpS? dbg d d b ft CtftV lldit?b I0 O6 I 99 12 vector. The adjusted technical coefficients developed were applied

to published statistics of regional total output by sector to compute

the total dollar flow table for the region shown in Table 18. This

table indicates the total annual dollar value of transactions that take place between the economic sectors in the region. For example, Con­ struction and Mining sold 187.7 million dollars worth of goods and ser­ vices to Agriculture, Forestry and Fisheries Bector and 24.0 milIon to

Food and Kindred Products in 1970.

IVo important additional assumptions were made in developing the regional table. First, because regions are not closed economic systems as arc national economies, it was necessary to estimate the employment balance for the region. The Charleston region Is a labor Import region, that is, part of the labor force working In the three counties have migrated into the region from the surrounding counties. Developers familiar with the region estimate that one-half of all major new employ- 13 ment opportunities in the region are filled by In-migrating labor.

Thus, it was arbitrarily estimated that new employment opportunities in the region would be filled one-half by the local labor force and one-half by in-migrating labor. Second, it was assumed that the average family size of the in-migrating labor force was 3.5 persons per family. This regional statistic was assumed to be the same as the average family size

12 Eugene A, Laurent and James C. Hite, Economic-Ecologic Analysis in the Charleston Metropolitan Region: An Input-Output Study. Water Resource Research Institute (South Carolina: Clemson University, 1971). 13 Personal interviews with staff of the South Carolina State Development Board and with local industrial developers operating in the Charleston region. TABLE 18

DOLLAR VALDES OF INTERINDUSTRY TRANSACTIONS, CHARLESTON SMS A, 1970 a: til 171 (71 (61 (51 (61 (71 (It i. an. * n ^ e t ^ 6.177.156 7*167.661 *S,6*t 685,360 285,179 3 0 tl.952 2. FT” ) • j|PUT/t*iW|T 16.157.668 7.118*799 163.*13.5*6 12.708,816 57.269,613 2*376,236 6.086.117 5.3*6.*06 I t i L I9T2*9£]HTE miTPtfl 6.713,717 1*996,671 15.535.312 5,986*776 22.736,913 211.157 6,229,786 3.379.397 ■mi o:*a*o 7.617,971 5.391,619 12*.277,776 6,221,31? 36,532.688 1,795.3*4 1*775.331 2.(37.262 . rinnTiIOT 1*557.967 5*825,617 162.769 5,212,3*1 378.508 1.852.285 1,118.961 •33.082 . st*»e a*** neat n i¥ f* w»eht 79,679 36.111 29.578.165 27,61* 5.722 *6.754 236.528 73,*18 . r( irett. C0r£T9"E«r •367,113 69.698 5.652.591 163,527 229,73* 37.511 61.817 231.15] . caiss et * o»ts 6.717.768 292,381 92.911,778 963,876 33,976,635 628.319 368.816 7*9,192 f>m onr^trr/itPyT 16*157.663 7.388,289 163.812,586 12,288.816 57,269,683 2.876.236 6*886.117 9.386.586

O o 101

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18 represents the basic economic structure of the Charleston study region in 1970. The economic data contained in the tables represent the base line economic input data required to operate Submodel 1.

The approach used to develop the Charleston regional table was suggested by Miernyk, Schaffer and Chu. The approach incorporates several assumptions which are frequently used in developing regional

Input-output models. First, it assumes that the Charleston Region follows the classical growth model for the basic and non-baslc sectors of a regional economy. Second, it assumes the region accurately mirrors national business cycles and trends and experiences no appreciable time lag behind national economic cycles. Third, In developing the regional table, intersector employment ratios were assumed to be an adequate surrogate for Intersector dollar flows.

Fourth, the approach represents the economic structure of the region, but does not identify capital formation within the region. This regional characteristic could be added to the model by developing the relationship between employment and capital formation. Fifth, the model Is designed as a static impact assessment methodology.

The model could be modified for the analysis of future Impact assess­ ment by incorporating a demographic and economic forecasting routine. 104 The above assumptions and qualifications are inherent In the approach adopted and have been recognized in this dissertation.

Regional Environmental Matrix

The environmental matrix constructed for the Charleston area contains twenty-three columns, one column for each of the endogenous economic sectors of the input-output matrix. There are twenty rows in the matrix, one for each natural resource input or emission from the

Charleston economy. The resource Inputs and emission outputs Included in the analysis are listed below. The resource Inputs and emission out­ puts are considered to be environmental requirements that are a function of units of_output such as square feet/employee, pounds, gallons, or cubic yards.

1. Particulates (lbs) 11. Process Water (gals)

2. Hydrocarbons (lbs) 12. Total Water Intake (gals)

3. Sulfur Dioxide (lbs) 13. Discharge (gals)

4. Gaseous Fluoride (lbs) 14. 5-Day BOD (lbs)

5. Hydrogen Sulfide (lbs) 15. Suspended Solids (lbs)

16. Solid Waste (cu yds) 6. C02 (lbs) t 2 7. Aldehydes (lbs) 17. Land Area (ft /emp) 2 8. N02 (lbs) 18. Floor Space (ft /emp) 2 9. Domestic Water (gals) 19. Parking Area (ft /emp) 2 10. Cooling Water (gals) 20. Building Site (ft /emp) 105

Interest in the resource requirement ratio is greatest when the resource is in short supply. For example, a settlement with a limited supply of fresh water presumably would be concerned with the rates of water utilization per employee for various industries and would attempt to encourage the growth or introduction of those industries with low water requirements.

The environmental data used in computing the environmental coef­ ficients were obtained from numerous sources. An extensive survey of industrial land use requirements was made by the Bureau of Public Roads, 14 U.S. Department of Transportation in July, 1970. This survey col­ lected and tabulated four types of land requirements data for each SIC category that will be used in the environmental matrixt (1) total land area (Variable 17), (2) floor space (Variable 18), (3) parking area

(Variable 19), and (4) building site area (Variable 20). Data on each 2 of these parameters are computed on a ft /employee basis for each SIC category.. The DOT report lists several tentative conclusions that are partially documented using the data collected. The most important con­ clusions that bear on the design of Submodel 1 are:

(1) All area measures are a function of the size of the establishment measured in terms of number of employees. In other words, it is worthwhile to calculate and ut- lize square feet per employee measures. Also there is substantially more uniformity in square feet per employee ratios than in square feet per establishment ratios.

14 Edward A, Ide, Estimating Land and Floor Area Implicit In Employment--How Land and Floor Area Usage RateB Vary by Industry and Site Factors. U.S. Department of Transportation, July, 1970. 106

(2) Different Industries or activities require differing amounts of area per employee, that Is, there is sub­ stantially more uniformity in square feet per employee ratios within an industry than across Industries, and

(3) Industry location and space utilization rates are a function of local environmental factors such as the density of the surrounding residential development, and the age of the surrounding development both resi­ dential and non-residential,l5

The coverage of the DOT data with respect to number of establish­ ments and number of employees for the various types of area measures is shown in Table 19. A given firm may appear In all four types of area categories or only In one. Clearly the coverage in the case of land and floor area is substantially greater than for parking and building site area.

The specific land characteristics considered most relevant to the land use planning model included: (1) the land area, (2) the park­ ing areo, and (3) the building site area. These three areal character­ istics were computed for each of the twenty-three economic sectors in the regional table and are shown in Appendix B.

A recent field survey of natural resource usage and waste dis­ posal characteristics of firms in the Charleston region was a valuable resource to this a n a l y s i s . T h e s e data are admittedly crude, but they

.*■ do represent a benchmark against which to test future resource usage rates. Specific information was obtained from this survey as to usage of fresh water, brackish water, output of liquid waste in pounds of BOD,

l5Ibid., p. II-1-2,

^Laurent and Hite, Economlc-Ecologlc Analysis, pp. 52-55. 107

TABLE 19

COVERAGE OF INDUSTRIAL LAND USE SURVEY

Type of Area Building Item Land Floor Parking Site

Number of establishments 16,042 28,779 2,463 1,689

Area in 000's of square feet 2,436,928 884,090 155,359 64,673

Number of employees 1,153,453 1,153,663 196,962 154,849

Square feet/employee 2,113 766 789 418

Employees/establishment 72 40 80 92

Source: Edward A. Ide, Estimating Land and Floor Area Implicit in Employment--How Land and Floor Area Usage Rates Vary by Industry and Site Factors. U.S. Department of Transportation, July, 1970.

i 108 and solid waste output. However, many firms which responded to the ques- tlonnalre did not answer one or more of the environmental questions.

Consequently, the survey data were supplemented mainly by data obtained from two other works. Air pollution data were drawn from a report by

Duprcy^ and data on water use and liquid waste were taken from a survey 18 of South Carolina industry conducted by Stepp. These data were fur­ ther supplemented by unpublished data collected in the Boston and

Philadelphia areas by Isard and Romanoff and by personal Interviews with industry specialists at Battelle Memorial Institute. Resource input and waste emission output coefficients were computed by dividing the input or output quantity by the sector's employment or output level.

The environmental land, resource Inputs, and emission coefficients are summarized in Table 20.

A critical examination of Table 20 will reveal that there are little or no data in many sectors which one would expect to have impor­ tant linkages to the environment. For example, Construction and Mining, which includes land and gravel operations in the Charleston area, usual­ ly produces some particulate output in the form of dust particles. It was not possible to obtain data for all sectors, either because the firms making up that sector did not report information in the survey or there were not published sources available or both. Because of those

^R. L. Duprey, Compilation of Air Pollutant Emission Factors, Publication No. 999-AP-42 (Durham, N.C.: U.S. Department of Health, Education and Welfare, National Air Pollution Control Administration, 1968). 18 James M. Stepp, Water Use. Waste Treatment. Water Pollution and Related Economic Data on South Carolina Manufacturing Plants. Report No. 8 (Clemson, S.C.: Clemson University, Water Resources Institute, 1968). TABLE 20

ANALYSIS OF IMPACTS ON SELECTED NATURAL RESOURCE INPUTS, WASTE EMISSIONS, AND EMPLOYMENT, CHARLESTON SMSA, 1970

i l l 12) 131 IJ1 (SI >S> 171 . tf) 141 1101

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a| 110 I 1 TABLE 20— Continued 5 X0J«0 4 IUUN0U0J4U4"| " 4 U 4 J 0 U 0 N U U I 41 0 MX « 0 J Q ^, 4 IN AC . .*)a 0h54hOJ OH 3040493 9 4 0 4 0 3 H tO O O JO O h 4 5 h y0 o j« - ~ NdU A «*** 'A «**JkNUdOU 4. W K O — — 4 i N S k y f t N W N U j U 4 U 4 f t H O O K J O I a m w MaOJMAtfAl4 4yww 0N 4 0 4 4 N 8 4 0«*Nrt#^0NV 0«*Nrt#^0NV 4 8 N 4 4 0 4 0N - - — u mm-0+ UJ0JA0 M 4 0 j

I U4 afNitI tk. JN o 4 B0 0-OO<»Oi •0-0’00'9<»0 0*00 O OOniOi 0O'#lNh> 0*00 •0-0’00'9<»0 • •• *1 *1 •» •» *1 *1 *1 •«♦* *1 •! •» *4*4 •( «l*| 0 Q Q o i v i v o o o o o o Q O o o o q i t o a 455 j j 5 5 Z4 9 t » 9 9 O 9 O O O « 0 O 9 * » O O D # 9 0 O • • - « M A W 1 jyy y j 9«JJ. 9«JJ. •« • ■ •( *4 •(*1 • • *1•» •» •( • ♦ *l ***4 •* •* *t *1 o o o o o o o a a o o o D O A i# * # o # o * i# A O D o o o a a o o o o o o o oooBoa oooAam^ M ^n a^m A o o ao ao o B o o ao .... ______2 awao a w xa l DO- O D 4 il J « > s J

..... H O ifiN K o o o o o o o o o o o " (d■ k 000444 , I — U J M J W & S U ' J? J J < 4 M N W A 4 4 4 0 ____ ^ a ____

n a 00O 0 (0 IOOO 0 0 0 * 0 0 1 > O O O O O N O ^ O M I K O S l l I O O O O ' O # *- *- — X ♦ 14 — NlkdW O 0044 4 jay^lUulMy

»| U 0»U| N^UKVI a Olt J40I 4 0

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— AO*- — H/(rt t C — — • XVIa « K j n v M 4 J J 4 OOANOaMM UJU m i i u i i JON 000 (J 4NNTDjMyMyyytf B 4 4 0 4

> u 0 0 0 0 > 44 _ _ - _ _ N t>No^o»* » o ^ y N»o ( y #tf>0N « 44 Ik 4 4 0 ( 4 O O U V N 0 0 ( AWOE oooooo0r 0 o o o o o o 4 jl 4 0*4

4 0 U 4 4 J OOO0OOOO O O O 0 O O O O 9 o K m O 4 « « 0 i ► (x w o Huy 0 J

BaO* OOOM^ QMJ oi d a ia jo 4 ¥ m • n o t t o n • &MOO«D JS IA»> « — *- _ 304 4 u j

3 Ml 4 O m ld(L k 4 4 0 • *t 4

J 9 Q lUW A k(LS #tffp Ik JOO v< 91 433 4 **ii 4

•MU ms 0 4 ~o. a 0 V* ► - 4 04 J . Ki , 4 3. J

« 04 111

TABLE 20— Continued

Source: R.L. Duprey, Compilation of Air Pollutant Emission Factors. Publication No. 999-AP-42 (Durham, N.C.: U.S. Department of Health, Education and Welfare^ National Air Pollu­ tion Control Administration, 1968).

James M. Stepp, Water Use. Waste Treatment. Water Pollution and Related Economic Data on South Carolina Manufacturing Plants. Report No. 8 (Clemson, S.C.: Clemson Univer­ sity, Water Resources Institute, 1968).

Walter Isard and Eliahu Romanoff, unpublished water use and water pollution coeffi­ cients, (Cambridge, Massachusetts: Regional Science Research Institute, 1967).

Marshland coefficients are derived from personal interviews with officials of Charleston District, U.S. Army Corps of Engineers.

Solid waste coefficients are derived from survey data, Charleston Area Input-Output Study, 1969. 1X3

cases where these blank cells should have numbers, but presently do not,

4 * t there will be a bias introduced into the estimates o£ the environmental

impact of economic activities, and this impact will be understated. No

attempt was made to collect additional primary data since the purpose

of this research was to develop and test a land use planning method­

ology on available data rather than to collect primary data.

Most of the coefficients in the environmental matrix (Table 20)

had to be computed from diverse data sources. An important assumption

made in computing the coefficients was the assumption of linearity. It was necessary to assume the same amount of natural resource usage or

environmental emission per dollar of gross output at one doLlar of gross

output as at one million dollars. Undoubtedly, this assumption of lin­

earity with regard to environmental linkages is not always realistic.

For example, it is unlikely that ecological damage is linearly related

to air pollution concentration. However, the model stressed physical

relationships rather than biological relationships in order to minimize

the problems associated with the linearity consumption.

The aggregation of the table into twenty-three economic sectors

potentially represents another source of error in developing the model.

For example, the waste of the dairy foods processing plants may be quite

different from the waste of a baker, yet they are both aggregated under

the broad heading of "Food Processing and Kindred Products."

There are three possible solutions to the aggregation problem:

(1) Use a weighted average of the environmental coefficients

using gross output of the component types of firms mak­

ing up the sector. 114

(2) Use mean survey data (which will be influenced by the

mix of firms responding to the survey).

(3) Build the input-output table at a very low level of

aggregation— i.e., the four digit SIC level.

The third approach is probably the most satisfactory, but such an input-output table would be so large and hard to manipulate as to be almost impractical. The survey data taken from the literature used various combinations of the first two alternatives, depending upon whether the environmental data were derived from secondary sources or from survey information*

Data Preparation for the Site Analysis Submodel (Submodel 2)

Submodel 2 is an empirical model that evaluates the suitability of alternative sites for industrial development. To restate, suitabil­ ity is defined as the degree to which the natural and man-made qualities of a location are economically and environmentally suited for the pro­ posed industrial land use.

The submodel has been designed to present diverse economic and environmental data describing the case study region in a simple visual form. Emphasis was placed on collecting secondary data for the Charles­ ton region. Consequently, available reports were collected and analyzed to identify the economic and environmental structure of the region. Some of the reports utilized as a basis of these data are presented in Appendix

A. Since the model was designed to use secondary data, it is Important to check the accuracy of these data and to update the data base through field observation and verification procedures. 115

The Information describing the economic and environmental char­ acteristics of the region was organized according to several descrip­ tive criteria that formed the basis for a series of map overlays.

These criteria were chosen from the candidate suitability criteria pre­ sented in Table 12, Overlays were developed for these criteria for which secondary data were available, A total of twelve overlays were developed as shown in Table 21. Each overlay was drawn at scale

1:250,000 to match the scale of the base map drawn for the region.

A series of unstructured interviews were held with experts from

The Ohio State University, School of Natural Resources, and The Battelle

Memorial Institute to evaluate the economic and environmental suitabil­ ity of each descriptor found in the table. A scale ranking of (1) high,

(2) moderate, and (3) low sensitivity was developed and used to evaluate each descriptor. These rankings were applied to the economic and envi­ ronmental conditions found in the Charleston region, and the results of the analysis were mapped on individual overlays. The individual overlays were then superimposed on a base map to identify areas that had highest economic and highest environmental suitability for industrial develop­ ment. A suitability index was computed to conduct a comparative quan­ titative analysis of alternative sites,

A series of map overlays depicting both economic and environ­ mental characteristics of the study region was prepared. The data col­ lected and analyzed on the case study area was presented in individual overlays for a base map at scale 1:250,000. A brief description of the environmental and economic overlays prepared for the study area follows. TABLE 21

CRITERIA FOR EVALUATING ECONOMIC AND ENVIRONMENTAL SUITABILITY OF SITES

Environmental Overlay Identification Suitability

Landforma 1. Flood Plains and Coastal Wetlands Tidal Marsh Low Freshwater Marsh Low Bottomland Forest Moderate 2. Extensive Woodlands High 3. Mixed Farmlands and Woodlands High 4* Beaches, Dunes and Coastal Sand Plains Low

F o re s ts 1* C o n ife r Longleaf pine High Lob lolly pine High Short leaf pine Moderate Virginia pine Moderate White pine—Hemlock Moderate Pond pine (swamp pine) Moderate 2. Hardwoods Oak>Hickory-Serub Oak Moderate 3. Mixed . Hardwood Pine Low Swamp and Bottomland Hardwoods (Oak, Cum, Cypress) Low Honforested High

W ildlife Habitats 1* Forested High 2. Grassland, Cropland, Brush Moderate 3. Coastal Wetland Low 4* Riverine Wetland Low 5* Aquatic Low 6* Beach Low

A ir Resources (Particulates) (Federal regulation of emissions from complex a ir pollution sources) >100 mg./cub meter Low > 80 <100 mg./cub meter High < 80 mg./cub meter Moderate

Watershed Resources (Quality C lassification) (state regulation of water effluents) Class A Low Class B Moderate Class C High 117

TABLE 2l--Contlnued

Economic Overlay Identification S uitability

Sauer and Water U tilitie s Area not served at a ll Low Area Served by Water M oderate Area Served by Sever M oderate Area Served by Water and Sewer H igh

Tram por ta t Ion Access (Hajor Highways—e .g ., Inters tatei and principal State Roads—Major R ail Lines, Major Watervays*-coastal and Inland) Area Outside Access Corridor & l mile elthet side) Low Area Served by One Access Corridor mile on either side of corridor) M oderate Area Served by Two or More Access Corridors (<1 m ile on either side of corridor) "" H igh

Existing Land Use Residential Public, C ultural, Educational Parks, Recreation, Open Space Low National Forest Water, Marsh Conmerclal and Services M oderate Manufacturing and Nonmanufacturing H igh Defense Installations H igh Unclassified Highland M oderate

Landform s

1. Flood Plains and Coastal Wetlands Low Tidal Marsh Low Freshwater Marsh Low Bottomland Forest M oderate 2. Extensive Woodlands H igh 3. Mixed Farmlands and Woodlands H igh 4. Beaches, Dunes and Coastal Sand Plains Low 118

TABLE 21-"Continued

Econom ic Overlay Identification S uitability

Topography/Slope Negligible Tidal Flats (elevation <10') Low > . 5 < 1 . 5 H ig h >1.5 Moderate

Soil Type Associations Chewacla, Swamp, C oxvllle, Bladen, Tidal Harsh, Fresh Water Marsh, Plummer, Craven, Leaf, S t. Johns, Mined Areas and Made Land, Rutlege, Firm to Soft Tidal Marsh, Dunbar, Hyatt, Weston Low Goldsboro, Eulonla, N orfolk, Kiawah, Weston, Craven, Scranton, Klej M oderate Wando, K le j, Goldsboro H ig h

Geologic Formations Sand, clay, and shell H od ora te Waccamav, Duplin, Hawthorn M oderate Cooper Marl and Flint River High Santee Limestone Low Black Mingo M oderate

Because of lim itation! In data availability and high auto c o r r e la tio n among characterlatte a u lta b lllty, aome of tha economic and environmental c rite ria presented Independently In Table 11 have been grouped together In Table 21, 119

Environmental Overlays

Landforms

Major land resources were identified and mapped by the Charles­

ton District Office of the Corps of Engineers. The types of resources

identified included flood plains and coastal wetlands, extensive wood­

lands, mixed farmlands and woodlands, and beaches, dunes, and coastal

aandplalns. The environmental suitability of each of these resources

was subjectively evaluated and outlined on a map overlay of the region

according to a scale of low, moderate, and high suitability. Areas

having high sensitivity to industrial development were ranked as repre­

senting low environmental suitability for development. Correspondingly,

areas of low sensitivity were ranked as having high suitability for

development.

Forests

The forest resources of the region were described in a series of maps prepared by the U.S. Army Corps of Engineers. Several forest types

were identified including conifers, hardwoods, and mixed forest. Forest

types that were Judged to have low wildlife habitat value were designated as having high development potential. Forest types with high habitat value were judged to have low development potential.

Wildlife Habitats

The wildlife habitat resources of the case study area were clas­ sified by the U.S. Army Corps of Engineers into many types including 120

forested, grassland/cropland/brush, coastal wetland, riverine wetland, aquatic, and beach. The environmental suitability of each habitat type was subjectively evaluated, and areas such as coastal wetlands and riverine areas considered to be highly sensitive to development were ranked as having low environmental suitability. Upland grassland and forested areas were judged to be more suitable for development.

Air Resources (Particulates)

The air quality of the case study area has been analyzed by the

South Carolina Department of Health who has mapped the sulfur dioxide and particulate concentrations across the Charleston region as of 1972.

The concentrations and dispersion of particulates and sulfur dioxide follow a very similar pattern in the region. Areas of high particulates concentration (arbitrarily 100 milligrams per cubic meter) were ranked as having low industrial development potential while areas with moderate particulate concentration were ranked as having highest suitability for development. These evaluations reflect recent Federal legislation cover­ ing complex air pollution sources. The intent of this legislation is to disperse the concentration of polluting industries into moderately pol­ luted areas while trying to reduce all stack emissions.

Watershed Resources

The availability of water as well as the quality of water has been mapped by the South Carolina Water Resources Conmission. Major surface water lakes, streams, and coastlines were classified according to Class A, Class B, and Class C water quality. Class A is considered 121 to be suitable for bathing, drinking, and abstraction of edible food, while Glass C is considered to be suitable for water transport, industry, and other lower quality uses. Watershed water quality was mapped from the surface quality of lakes and streams. Tributaries that were not

Included in the original survey were assumed to have the same water quality as their principal stream or lake. Areas of low quality are considered to have high suitability for development while areas with high quality are considered to have low suitability.

Economic Overlays

Sewer and Water Utilities

The existing sewer and water distribution for the case study area was identified in a report by E. M. Seabrook, Jr., Inc., Cummings 19 A McCrady, Inc., and Sigma Engineers, Inc. Three categories of util­ ities were identified and mapped. Areas that had no sewer or water service were judged to have low suitability for development. Areas served by water or sewer were considered to have moderate suitability, and areas served by water and sewer were considered to have high suit­ ability for development.

19 E. M. Seabrook, Jr., Inc., Cunnings A McCrady, Inc., and Sigma Engineers, Inc., "Water, Sewer and Solid Waste Disposal Facilities— Berkeley and Charleston Counties, State of South Carolina" (prepared for the Berkeley-Charleston Regional Planning Commission). 122

Transportation Access

Maps prepared by the South Carolina Department of Highways were

analyzed to determine the location of transportation corridors including

major highways, rail lines, and waterways. Areas beyond two miles of a

major highway Interchange or one mile of either side of the highway were

judged to have low suitability for development, as were areas beyond one mile of rail or water facilities. Areas within two miles of major road

Interchanges were considered to have moderate economic suitability, while areas adjacent to road Interchanges and water or rail facilities were considered to have high economic suitability. Areas outside of

t transportation corridors were considered to have low economic suitabil­

ity.

Existing Land Use

The existing land use of the region was mapped by the Charleston-

Berkeley-Dorchester Planning Commission. Areas with residential, public, cultural, educational, parks, recreation, open space, national forests, water and marsh were mapped as having low economic suitability. Areas with commercial and service industries were considered to have moderate suitability, while areas with manufacturing and non-manufacturing, de­

fense Installations, or unclassified highland were considered to have high economic suitability. 123

Landforms

Major land resources of the area were napped by the U.S. Army

Corps of Engineers. These features can also be considered from the economic suitability point of view. Flood plains and coastal wetlands are considered to have low economic suitability as do beaches, dunes, and coastal sand plains. Bottom land forests were considered to have moderate suitability, and extensive woodlands and mixed farmlands were considered to have high economic suitability.

Topography/Slope

Topography and slope was analyzed using standard USCS topographic maps. A modification of the Potter index was developed to compute the mean slope in each major watershed. The modified index utilized was E1 ' Ez slope g , where E^ and Ez are the elevations, respectively, at the vim and mouth of the watershed and d is the stream mileage between these two points. Depressional and low lying areas rich in fauna and flora were judged to have low economic suitability for development while slopes £ 1,5 feet/mlle were judged to have moderate suitability, and slopes > .5 < 1.5 were Judged to have high suitability.

Soil Type Associations

The U.S. Soil Conservation Service has mapped the soil types in the region. Sandy and wet coastline soils with delicate ecosystems were judged to have least economic suitability for development, while poorly drained clay soils with high strength and bearing capacity were judged to have high suitability. 124

Geologic Formations

The Division of Geology, South Carolina State Development Board has mapped the subsurface geology of the region. Ecologically delicate coastal areas comprised of sand, clay, and shell were judged to have moderate economic suitability for development, while the Waccamaw and Cooper Marl formations with load bearing strength were Judged to have the highest economic suitability. The_subsurface limestone formations are highly susceptible to subsidence and underground washout and were Judged to have only low suitability for development.

The twelve overlays discussed above were prepared at a scale of 1:250,000 for the case study area. These overlays are presented on

the following pages. Because of the difficulty in superimposing twelve overlays on a base map of the region, it wao decided to reverse the process and superimpose the base map on the overlays. This procedure

Is explained in the next chapter along with a description of the appli­ cation of the model to the case study area. environmental overlays

125 O' FIGURE 6 LZl 128 FIGURE 7 FIGURE 129 FIGURE 8 FIGURE

ECONOMIC OVERLAYS FIGURE 10

u

FIGURE 12

Topocmrwrttion >l

FIGURE 14

c < o > .o o c r o — ATicmt

FIGURE 16 CHAPTER V

MODEL APPLICATION AND RESULTS OF ANALYSIS

The land use planning model developed in the previous chapter Is applied to a case stud/ area, and the results of the analysis are pre­ sented in this chapter. The model is proposed as a tool to help the development planner design and implement a selective industrial develop­ ment program. The key questions facing the development planner are:

(1) Which industries should be solicited and attracted

to his region?

(2) What would be the regional economic and environmental ' i impact from locating these industries?

(3) Where should the industries be located spatially

within the planning region to assure high economic gain and minimal environmental degradation?

The land use planning model developed and evaluated in this dis­ sertation is an important contribution to land use planning research.

The application of the model provides information basic to the three questions above and provides a rationale for the design and implementa­ tion of a selective industrial development program.

Overview of Model Experimentation

The testing of the land use planning model is conducted as a controlled experiment in which it is hypothesized that a series of

139 140

Industries desire to locate in the Charleston planning region. First, this dissertation proposes Submodel 1 as a tool for evaluating the re­ gional impact of locating industries within a planning region. Second,

Submodel 2 is proposed as a tool for evaluating the potential suitabil­ ity of alternative sites within the region for accoomodating the pro­ posed industry. As developed in this dissertation, Submodel 1 is an automated computerized model that is operated on a CDC 6400 computer whereas Submodel 2 is a noncomputerized model operated manually placing a series of map overlays on a base map of the case study area and cal­ culating a suitability index for each industrial site included in the experiment.

Experimentation with Submodels

A controlled experiment was designed to test the utility of the land use planning model. It was hypothesized that 23 types of industry sought to locate in the Charleston case study region. Each industry represents one of the sectors in the 23-sector input-output table devel­ oped for the Charleston region in Chapter IV.* Submodel 1 was used to test the regional economic and environmental impacts of locating an industry with 300 new employees in each sector of the 23-sector table.

In essence, 23 individual experiments were conducted using Submodel 1.

The basic approach followed was to conduct the impact experi­ ments with and without the proposed industry. Initially, baseline

*The rationale for developing a 23-sector table was presented in Chapter IV. The principal reason for using 23 sectors was that environ­ mental coefficients were developed and available at this level of detail from secondary sources* Every effort was made to use secondary data where available. 141

conditions, e.g., sector employment levels, were established for the

Charleston region without the proposed industry) then, Submodel 1 is run

again with the proposed industry to determine the economic gain or envi­

ronmental damage that might occur In the region because of the location

of the proposed industry.

The controlled experiment provides an assessment of the regional

impact of all industries that could potentially locate in the Charleston

region. The output of the tests were analyzed to classify each industry

according to industry profiles constructed from the information devel­

oped. A subset of these industries was selected for use in Submodel 2,

the Site Evaluation Model.

Description of Input Variables Used in Submodel 1

The Regional Analysis Model (Submodel 1) is based on an expanded

regional input-output analysis. To operate the model, the planner must

have (1) population data, (2) employment data, (3) an estimate of the

size of in-migrating families, and (4) an estimate of the proportion of

in-migrating families that enter the region to fill new employment op-

* portunlties created by the proposed industry. The input variable and

their value range are specified In Table 22.

The regional population and employment data are readily avail­

able from the U.S. Bureau of the Census, Department of Commerce. The

average size of in-migrating families and the proportion of in-migrants

was estimated from personal interviews with South Carolina officials as

discussed in Chapter IV. Since no official source maintains regional 142 data on the average size or proportion of in-migrating families, the model was run with ranges arbitrarily specified in the table to deter­ mine the sensitivity of the model to these variables. The results of these sensitivity analyses are presented in Appendix D. All production runs of Submodel 1 reported in the text assumed an average value of 3.5/ family and 50 percent in-migration which were best estimates available based on interviews with South Carolina officials.

TABLE 22

INPUT VARIABLES FOR SUBMODEL 1

Identification Variable of Variable Values Variable Description

POP 336,125 Population in Region

EMP 99,969 Employment in Region

AVS 2.5-4.5 Average Size of In- migrating Family

TNI 0-100 Proportion of In­ migrants to Region

Description of Output from Submodel 1

The output developed from the Regional Analysis Model provides an assessment of the regional economic and environmental consequences of locating a specific industry in the Charleston planning region. A comparative analysis of the Impacts resulting from alternative proposed industries is conducted by identifying and monitoring the changes that occur in key environmental and economic indicators that represent 143 pollution and economic gain potential. The selected indicators for each category are shown in Table 23.

TABLE 23

OUTPUT INDICATORS FOR SUBMODEL 1

Environmental and Economic Criterion (c) Potential Output Indicator

Air Pollution Particulates (lbs)

Water Pollution 5-day BOD (lbs)

Solid Waste Solid Waste (cu yds)

Water Demand Total Water Intake (gals)

Land Consumption Total Land Area (sq ft)

• Economic Cain Employment Levels (no. of jobs)

The indicators shown were used to develop environmental and eco­ nomic profiles for each industrial sector evaluated. The profiles were developed based on a statistical index of standard deviations. The environmental and economic Impact was statistically compared to the average impact from all 23 industries. These comparisons were used to rank the Indicator values for each sector as high, moderate, or low environmental or economic potential. For example, industry impacts that fell within one standard deviation of the average industry impact were arbitrarily ranked as moderate. Industry impacts that were less than one standard deviation were classified as having low potential, while industries with impact greater than one standard deviation were classi­ fied as having high potential for that indicator. The standard 144 deviation technique used here is based on arbitrary cutoff limits for

"high," "moderate," and "low" ranking. The approach to ranking is log* leal and systematic and can be applied with any arbitrarily determined limits. The contribution of this technique is that it provides a sys­ tematic approach to ranking regardless of the cutoff limits used. This relationship can be expressed as follows t

c where*

R « rank index of environmental and economic potential

(where R - High, Moderate, or Low)

C ■ average impact for 23 sectors

c^ ■ impact of individual sector on each indicator

S~ ■ standard deviation of average impact for 23 sectors.

A statistical index was developed for each principal environmental and economic indicator analyzed and formed the basis of the industry pro­ files computed for each sector. The profile provides a means for com­ paring the regional impacts on the various industries tested and pro­ vides input on industry characteristics to the Site Evaluation Model

(Submodel 2).

Description of the Input Variables Used in Submodel 2

The principal input variables used in Submodel 2 are the envi­ ronmental and economic criteria identified in Table 21 of Chapter IV and summarized in Table 24 below. The data are displayed on overlays for 145 the region to develop a composite environmental/economic suitability map for the region and to compute a composite index for each site evaluated.

TABLE 24

INPUT VARIABLES FOR SUBMODEL 2

Overlay Variable Variable Variable Number Identification Range Description

1 ENLF High, Moderate, Low Landform

2 ENF tt Forest

3 ENWH n Wildlife Habitat

4 ENAR n Air Resources

tt ■ 5 ENWR Watershed Resources

6 ECSWU it Sewer & Water Utilities

7 ECTA tt Transportation Access

8 ECELU tt Existing Land Use

9 ECLF tt Landform

10 ECTS tt Topography/Slope

11 ECSTA tt Soil Type Association

12 EGGF tt Geologic Formation

A composite overlay map could be developed by superimposing all

12 overlays on a base map of the region. For practical purposes, five sites representing a cross section of the region were selected for testing Submodel 2. These sites were evaluated for their industrial suitability based on the variables presented in Table 24. Submodel 2 was applied to the location of three selected "desirable" industries on these five sites. The desirable industries were chosen from the 146 subset of Industries having high economic potential-and moderate environmental potential as developed in Submodel 1*

Secondary sources were used to develop the basic information needed to use Submodel 2. Maps and reports published by the Corps of

Engineers and the State of South Carolina on the Charleston region were utilized extensively.

Description of the Output from Submodel 2

The output from Submodel 2 may be presented as a comprehensive visual map display of the region showing areas of high, moderate, and low suitability for industrial development, or as a numerical index com­ puted for selected industrial sites. Due to the difficulty of viewing a composite display of 12 overlays, it was decided to proceed by superimpos­ ing each overlay one at a time on the base map and recording the individ­ ual values. The suitability index (SI) is then computed as follows:

n m SI - E k . EVS. + £ k . ECS. i a- 1 i J J where*

EVS « Environmental suitability for each overlay

ECS « Economic suitability for each overlay

Ku ■ Weighting constants. Three "desirable" industries and five representative industrial sites were selected as a basis for testing Submodel 2. 147

Model Experimentation and Results of Analyses

The Implementation and testing of the land use planning model on

the Charleston region was conducted in two separate steps. A total of

24 trial runs were completed using Submodel 1, including a base run plus

23 test runs; 16 runs were completed to test Submodel 2, including a base run plus 15 test runs representing three industries at five differ­ ent sites. The characteristics of each run are specified in Table 25.

The output from Submodel 1 identifies and categorizes each of

the 23 industries according to their regional environmental and economic

impact. From the total proposed industries, three were selected from

those that had the greatest economic benefits (i.e., generation of new

Jobs) and moderate environmental degradation (i.e., resource and pollu­

tant Indicators) to the case otudy region. These Industries were used

as inputs into Submodel 2, the Site Evaluation Model, and a Suitability

Index (SI) was computed for each of five representative selected sites.

Each site was evaluated and the output used to rank the sites accord­

ing to their economic and environmental suitability for the industries proposed.

Analyzing the Output from Submodel 1

Submodel 1 was run 23 times to simulate the impact of locating

23 different types of industry in the Charleston region. The impacted

sector for an Industry is represented by adjusting the employment level

for that industrial sector in the regional input-output table as well as ZABLE 25

LAND USE PLANNING MODEL EXPERIMENTATION

MngBBEk.______Simulated Location* SUBMODEL 2 trial Dumber of 300 Employee* Trial Dunbar Deairable Industry Site Evaluation

Base Run none Base Run none none 1 Ag.,Forestry A Fisheries 1 Food & Kindred Products (S IC 2 ) 1 2 Food A Kindred Products 2 Food & Kindred Products (S IC 2 ) 2 3 Construction A Mining 3 Food & Kindred Products (S IC 2 ) 3 4 Textile A Apparel Hfg. 4 Food & Kindred Products (S IC 2 ) 4 5 Lumber A Wood Prods .M fg. 5 Food & Kindred P ro du cts (S IC 2 ) 5 6 Furniture A Fixture Mfg. 6 Construction & M in in g (SIC 3 ) 1 7 Printers A Publishers 7 Construction & M in in g (SIC 3 ) 2 8 Chemical Manufacturing 6 C o n s tru c tio n & M in in g (SIC 3) 3 9 Petroleum A Coal Mfg. 9 C o n s tru c tio n A M in in g (SIC 3 ) 4 10 Rubber.Plastic, A Related Mfg. 10 Construction & M in in g (SIC 3 ) 3 11 Stone.Clay, A Class Prods Mfg. 11 F u r n itu r e & Fixture Hfg (SIC 6 ) 1 12 Machiner,Repairs,A Metal Shops 12 F u rn itu re & F ix tu r e H fg (SIC 6 ) 2 13 Miscellaneous Mfg. 13 Furniture A Fixture Hfg. (S IC 6 ) 3 14 Transportation 14 Furniture A Fixture Mfg. (S IC 6 ) 4 15 Comnin Ic a t ions 15 Furniture A Fixture Mfg. (SIC 6 ) 5 16 U t i l i t i e s 17 Eating A Drinking Places 18 H o te ls A Lodging Places 19 Gasoline Service Stations 20 Other Wholesale A R etail Trade 21 Finance A Insurance 22 Real Estate 23 Other Business A Personal

All trial runs assumed that (I) SO percent of all new eeploynent opportunity eould be filled by ln*mlgratlng labor and (2) that each ln«mlgrating family consisted of 3.5 members. 149 adjusting the final demand In the table to reflect the Increased con­ sumption generated by in-migrating families. The output indicators were monitored to determine their change from the base run. The output indi­ cators included economic factors, such as value added by industry and employment opportunity. Land use and natural resource indicators in­ cluded domestic water, cooling water, process water, total water intake, land area, floor space, parking area, and building site. Pollutant indicators included waste emissions, such as particulates, hydrocarbons, sulfur dioxide, gaseous fluoride, hydrogen sulfide, carbon dioxide, aldehydes, nitrous oxide, discharge water, 5-day BOD, suspended solids, and solid waste. Each of these output criteria was used to

Judge the characteristics of the Industries proposed for the study re­ gion and to develop an industry profile for each sector in the economy.

For the purposes of this dissertation, the key indicators of (1) parti­ culates, (2) 5-day BOD, (3) solid waste, (4) total water Intake,

(5) total land area, and (6) employment were used to categorize the

Industries according to their economic and environmental potential.

Information is developed on 20 environmental and economic variables in the event that a more comprehensive analysis of industrial development proposals Is desired.

Table 26 presents the basic output from Submodel 1 derived from simulating the location of 300 new employees in each of the 23 sectors in the regional economy. The average impact and the standard deviation of the average impact for all 23 industries is presented. For example,

If 300 new employees were added to each of the 23 sectors in the Charles­ ton region, the average impact on land use would be 2.9 million square TABLE 26

ASSESSMENT OF IMPACT OF 300 NEW EMPLOYEES IN 23 SECTORS IN CHARLESTON REGION, 1970

AVERAGe T"P*CT GENERATE!) BY SIHULATEO NEK EMPLOYMENT* CHARLESTON SMS A* 1970

l.»ARTTCULATFSIL«Sl 781,695 2.HVQR0CAR9ONS(LBS) 3 6 5 .3 9 8 3 *SULFUR DI0*I0EIL9S1 1 2 0 ,5 5 1 6 .GASEOUS FLUORIOEILPSI a 5.MY0F0GFH SULFIortLDSl 13*663 6.CO 2 UPS) 2 6 3 * 8 0 7 7 . ALDPHPPPS CL9S1 ------~ ' 6 .6 3 0 9.MO 2 IL9SI 6 1 . 9 7 9 q.PO^FSTIC HATER(GALS» 7 8 1 0 .COOLING UATER(GALS) 2*161 1 1 .PROCESS MAT-R(GALS) 6 . 2 1 7 1 2 .TOTAL WATER INTAKE(GALSI 7 ,6 6 0 13.PPPrHAcr,E(GALS) 5,693 16.5 DAY D0DU9S) 5 2 J * 9 6 6 1 5 .S U S r r HOEO S O L IO S IL P S I 3 7 0 ,5 0 9 1 6 .SOLID WASTE(CU VOS) 66,210 17.LAND AOFA1SD FTI 2 * 9 3 6 , 8 6 1 1 8 .FLOOR SPACEISO FT) 2 9 1 * 9 9 9 19 .PARKING AREA(SO FTI ------5 0 9 , 1 1 3 20.BUXLOING SITE (SO FTI 1 7 6 * 9 3 5 21.NUMDER OF EMPLOYEES 6 9 0

STANDARD DEVIATION OF IMPACT GENERATED DT SIMULATED NEW EMPLOYMENT, CHARLESTON SNSA* 1970

l.P.ART|riiLAT£5Il«) 1*599*619.9 2.HVDR0CAR90NSILPP) 939*625.9 3 .SULFUR DT0*IDE(L9F) 319*636.6 6.GASEOUS FLU0RI0FCL9SI 0.0 5.MY0eOCFK SULFIOr tL05> 50*763.0 6.CD 2 IL9S) 963*367.6 7 .ALDEHYDES(LaSI 16*69:.6 9.NO 2 (L°S» 105*966.2 9*D0NrSTIC MATPOIRALS* 93.0 10.COOLING MATC*IGALS1 5.902.9 ll.P90P.PSS WATPRCGALSI 1 7 , 6 9 1 . 9 1 2 . TOTAL WATp R INTAKEIGALS) 23*593.6 lt.orPCHn®G£f«:«LS1 17.67*.5 16.5 OAY P00U9S) 1*623*961.2 1S.SUSPPNP-0 SDLinSILNSI 1*199*126.0 16.S0LT0 NASTEICU YDS) 151*993.8 17.LAHn ARPAISD FT1 3*190*266.9 18.FL00P SPACEtSD FTI 122*796.5 19.PARKING AREAISD r Tl 710*799.0 20.GUILOXKG STTE (SO FTI 119*567.2 71.NUNPER OF EMPLOYEES 6 3 . 9 151 feet (Variable No. 17) while the standard deviation of the average Im­

pact would be 3.2 million square feet. TWo-thirds of the land use im­

pacts fall within the range of 6.1 to -0.3 million square feet of land

(2.9 + 3.2 square feet). Similarly, the average impact on employment

from adding 300 new employees was the generation of 490 new jobs with a

standard deviation of 64. Thus, two-thirds of the employment impacts

fall within the range of 554 to 426 jobs (490 + 64 Jobs). High standard

deviations were experienced in some of the environmental Impacts*

The average and standard deviation impacts were used as a stand­

ard for comparing the individual impacts of each of the 23 industries

evaluated in Submodel 1. Table 27 presents this comparative analysis

with each sector evaluated according to the six key indicators iden­

tified above. Table 27 presents data on (1) total impacts, (2) number

of standard deviations from the mean, and (3) assigned rank for each

indicator. The individual ranks assigned to the indicators are used to develop the sector profiles that are used to compare industrial devel­ opment proposals at the regional level.

Five industries out of twenty-three were identified from the

analysis as having high economic gain and moderate environmental damage

potential including (1) Food and Kindred Products, (2) Construction and

Mining, (3) Furniture and Fixture Manufacturing, (4) Gasoline Service

Stations, and (5) Real Estate. Four industries were identified as hav­

ing low economic gain potential including (1) Textile and Apparel

Manufacture, (2) Communications, (3) Eating and Drinking Places, and

(4) Other Business and Personal Services. A complete set of data

tables developed from an analysis of the twenty-three sectors is TABLE 27

SUMARY OF IMPACTS FRCH 300 NEW EMPLOYEES IN EACH SECTOR ON KEY ECONOMIC AND ENVIRONMENTAL INDICATORS FOR THE CHARLESTON REGION, 1970

______ITOL.lKtftCT______glaalated Ltutlat' rtrtioiUtii 3 Day 100 Solid Vaita Total Watar Intake Total taod bfltjant of >00 ftalw ttl ______ilb t . l ______« *« .>______fO»._Tda.l______0111*. Cali.l Aram fHlli. So. Ft.l Wo. of Jnbtl Average for 23 Sactora 761,433 523,646 44,210 7,440 2,914,661 490 Toraitry t Flahertee 703,657 90,691 3,677 1,064 14,077,266 441 food I Kindred Froducte 2*7,741 510,401 4,452 3.261 10,838,209 611 Couttructlon 1 M ilo | 1,031,343 372,610 35,476 9.410 1,761,612 547 T actile 4 Apparel M (|. 74,*33 423,044 2,943 1,985 1,544,294 * 416 todnt 4 Vend tro ll Mfg. 7,714,292 6,049,316 752,104 117,14* 1,969,421 4*1 Furaltvre 4 n tta tt Mfg. 961,413 931,627 71,991 U .432 . 1,830,761 413 Frlntert 4 Fubltaheta U S ,575 49,614 3,362 995 1,251,179 312 Cbaalcal Manufacturing 317,411 117,969 5,227 3,103 2,731,933 302 t i lr o l n a 4 Coal Hfg. 2,712,725 79,770 6,650 1,754 5,907,354 443 Bobber, F la ttie , 4 Balatad Hfg. 145,611 1*5.651 4,234 2,500 1,769,756 313 Stone, Clay 4 Claaa Frada Mfg. 743,561 40,045 4,602 2,049 2,004,262 444 Hacktncr, Sapalra, 4 N ital Shage 1,094,415 59,140 5,301 3,641 1,310,142 415 Macellaoaoua Haas (ac ta r lag 264,00* 107,351 7,0*6 1,795 1,243,074 473 Trentportatloa 191,922 30,775 * 3,319 746 3,392,613 474 Dr»inleatlona 57,144 31,397 2,546 424 444,123 4 U Vtllltlaa 293,463 126,514 29,466 2,002 3,473,371 534 Bating 4 Drinking Blacaa 54,654 >4,372 14,113 416 1,216,640 416 Ketele 4 Ladling Flaaaa 111,611 56,126 6,169 764 950,165 453 Catollaa Service Statlaae •15,099 *0,341 4,030 2,219 2,121,550 374 Other Vhaleaele 4 la ta ll Ttada 150,114 66,743 7,436 1,244 1,343,145 466 ITnasca 4 leearaaca 70,461 37,913 .2,399 503 1,IU,634 467 Baal Batata 294,210 129,263 10,733 2,007 3,542,935 401 Other Daalaaaa 4 Fanaaal 63,724 43,160 2,732 569 1,139,450 409 TABLE 27— Continued

M uUgrof Standard Pori at Uma from Hran llanlatnd location* Fartlen- S Day 100 f a l l ! Waatn Tntal Ifalar In­ Tdtal Land EnglopnanC of NO EvlerHi lataa (Ui.) f U a .l (CO. Tda.> taka (Cali.3 Arta ISn.R.) f ib . o f Joba)

I|.f hnitty & Flabcrtaa -0.14 *0.11 -0.27 •0.24 3.49 •0.43 M 6 Kindred rn O ac ti •0.31 •0.01 •0.24 -0.14 2.44 1.92

Oonatructlon 4 Hlaint 0.1C 0.01 o.or 0.04 -0.34 1.20 ■ l U t l l i 4 Apparel Mfg. -0.44 •0.04 •0.27 -0.13 •O.U -1.13 ba4*t 4 Wood rroda Mg. 4.14 4.43 4.44 4.43 •0.10 •0.74 Furniture 4 Fixture Mg. 0.13 0.14 0.14 0.23 •0.33 1.92 F il a t m 4 Pub 11 abara •0.41 -0.14 •0.17 •0.24 •0.33 0.34 O nlcal KamifacturInf -0.13 -O.U •0.14 •0.19 -0.04 0.14 fctrolaoa 4 Coal M g . 1.11 •0.17 -0.13 •0.13 0.91 -0.71 la M t r , P laatle, 4 Raidtad Mfg. •0.31 •0.11 -0.24 * -0.21 •0.34 0.34 Itm , Clap, 4 Claaa Praia. Mfg. •0.01 0.14 •0.24 -0.24 •0.29 -0.72 Hacfelnar, Rapa Ir a . 4 Natal D a f t 0.10 •0.13 -0.24 •0.11 -0.31 -0.87 Klactllaocoua Manufacturing •0.31 -0.24 •0.24 •0.23 -0.32 -0.23 Transportation •0.37 •0 .1 } •0.17 •0.29 0.11 •0.23 Comntcatloaa •0.44 •0.30 •0.27 •0.31 •0.71 -1.21 DtllltUa •0.31 -0.14 •0.10 •0.24 0.17 0.49 gating 4 Drinking Flacaa •0.44 •0.30 •0.14 •0.31 -0.33 -1.13 Ms tala 4 lodging -0.41 •0.19 •0.24 •0.29 -0.42 •0.33 Caaellae Sarrlca gtatloaa o.u •0.19 * -0.23 •0.23 •0.23 1.31 Otktr Vbolaaala 4 la ta ll Train •0.40 -0.27 •0.24 -0.17 •0.49 •0.33 Flnanra 4 lnauraaca •0 .4 } •0.10 -0.27 •0.30 -0.37 -0.04 goal Katata •0.31 •0.14 -0.22 •0.24 0.19 i . n 0thar Baaloaaa 4 faraaaal •O .U -0.30 •0.21 •0.30 •0.34 •1.27 TABLE 27— Continued

Aaalgacd Saak tar ladlcatara Ita iU trf Location* ra rtlco * 3 Day KB Solid Vaata TOCal Water la * Total Lead CapleyaaaC . of 300 l a t l m i lataa (the.) flh a .l fO .. Yde.) taka fCala.) Area (So.F t.) fSa. of Jeba)

Ag.t n tM trf ft FlihtrtM MOO HOO HOD HOD RICH KB Food ft Ktodrtl Frodncta » 0 KB HOO HDO men m a t Cooitruction ft Mining HOD HDD KB KB MOO RICH T ilt He ft Appirel Kfg. HOD K» KBKB HDO LOW t a f t n ft Wood Fred*. Hfg. not .■ICS BIOS ■ICS HOO MOD rm ttm ft Flntarc Nf|< too KB HOO HOO K B ■ICS Frtotera ft h b l t i la n MX KBKB K B HOO H0D f t w l M l Haaafacturtng HDD KB HOO KB KB HOO h t n l m ft Cm I Kfg. ■ICS . KB KB KB w o HOO Robber, F la ttie ft RalataR Mfg. HDD KB KB KB HOO HOO t lo M , clay ft d a ta Freda Mfg. HOO HOO KB K B MOO KB Hecblatr, gaga Ira ft Ik U l Raya HDO 'KB KB KB KB KB fuecallaatotta Mfg. HDD KB HOO K B HOD MOO Tramportatloa KB HDO MOO KB MOO MOO Comal cationr HOO HOO KB KB K B UW D tlU tfe a KB KB KB HOO K B MOO ta t Lag ft Drinklog Flacaa KB* MOO H0O HOO K B LOW So tala ft Lodging Flacaa W 0 K B MOO KB HOO K B / Caaollna Service ftatlena HOO HOO HDO HOO HOO RICH Other Vboletala ft R etail Trade HOD KB HD0 HOO MOO HOD F in an ce ft tolerance HOO HOO HOO HOO HOD K B Seal Ceteta HOO KB HOO KB KB RICH Other Raalacae ft Fcraoaal HOO KB HOO K B M0D LOW All trial production runs assumed that (1) 50 percent of all new employ­ ment opportunity would be filled by in-migrating labor and (2) each in-migrating family consisted of 3.5 members. A test of the sensitivity of Submodel 1 to these assumptions is presented in Appendix C. 155

presented In Appendix E. Three industries vere selected for testing

Submodel 2 including (1) Food and Kindred Products, (2) Construction

and Mining, and (3) Furniture and Fixture Manufacturing.

Analyzing the Output from Submodel 2

Submodel 2 was run 15 times to evaluate the suitability of five

representative sites for three industries Judged to be environmentally and economically "desirable" from Submodel 1. The five sites selected for the evaluation are shown in Figure 17 and on the transparency enclosed in the jacket to this report. Sites 1, 3, and 5 are In diverse parts of Charleston County. Site 2 is located in central

Berkeley County, and Site 4 is in northern Dorchester County. The five sites represent the diverse environmental and economic conditions present in the three-county region.

The Site Analysis Model uses the output from the Regional Analy­ sis Model and evaluates the suitability of alternative potential sites for development. The (1) Food and Kindred Products, (2) Construction &

Mining, and (3) Furniture & Fixture Manufacturing sectors were used to test the suitability of the five proposed development sites.

The evaluation of Submodel 2 was conducted by developing a aeries of overlays depicting the environmental and economic character­ istics of the Charleston region. The overlays included information on: FIGURE 17. FIVE REPRESENTATIVE INDUSTRIAL SITES' IN THE CHARLESTON REGION - in as 157

Economic Environmental Sever and Water Utilities Landforms Transportation Access Forests Existing Land Use Wildlife Habitats Landforms Air Resources Topography/Slope Watershed Resources Soil Type Association Ceologic Formations

The overlays vere superimposed on a base map of the region that

was prepared at scale It250,000. The overlays developed identified

areas as having high, moderate, or low economic or environmental suit­

ability for development. A suitability index was computed for the five specific sites proposed for development by computing the sum of the

individual overlay values for the specific sites identified above. The

individual overlay scale vast

1 ■ Low potential for development

2 ■ Moderate potential

3 “ High potential.

The site with the highest suitability score was judged to have the high­ est potential for development.

The components of the suitability index indicate the specific environmental and economic sensitivities of the individual sites. For example, an industry characterized as having high air pollution poten­

tial should not be located at a site such as Site 3 having low suit­ ability due to existing air pollution problems. Site 3 is located in

the heavily congested area around North Charleston where heavy Industry

Is already concentrated. The sector profiles developed in Submodel 1 1S8 were compared with the environmental and economic suitability character­

istics displayed on the overlays. The comparison of the profiles with

the sites' suitability identifies those sites that most nearly match

the requirements of the industry proposed for the site.

The suitability index computed for each site is presented in

Table 28. The raw suitability index ranges in value between 0 and 36.

A value of 36 occurs if all economic and environmental factors have the

highest suitable potential for development. The raw score can be modi­

fied by using a weighting constant (K) greater than one. A constant of

K ■ 1 was used in each trial presented in this dissertation.

TABLE 28

SUMMARY OF COMPUTATION OF SUITABILITY INDEX FOR FIVE SELECT SITES

Suitability Index Computation n m SI ■ ZI k i. EVS.if + TIC, 3 ECS. 3 Economic/ Environmental Overlays Site 1 Site 2 Site 3 Site 4 Site Landforms 1 3 1 3 1 Forests X 1 3 3 1 Wildlife Habitats 1 2 1 2 1 Air Resources 2 1 2 Watershed Resources 1 2 3 2 1 Sewer and Water Utilities 1 1 2 1 1 Transportation Access 2 3 2 2 Existing Land Use 1 2 3 2 1 Landforms 1 3 1 3 1 Topography/Slope 1 2 2 3 1 Soil Type Association 1 1 3 3 2 Geologic FormatlonB 2 3 2 1 2 Total Suitability Score 15 24 25 27 16 159

Sices 2, 3, and 4 all had a relatively high suitability index

Indicating high aggregate potential for development. Site 4 had the highest suitability with a score of 27. Site 1 had an index score of

15, and Site 5 had a score of 16. Based on these results, Sites 1 and

5 were eliminated from further consideration. The components of the suitability indices were analyzed In order to rank the suitability of specific sites for the three specific industries selected and to identi­ fy particularly sensitive characteristics for the sites. For example,

Site 2 has high development suitability In terms of landforms and geologic formations, but low potential in terms of forests and sewer and water utilities. Site 3 has high development suitability in terms of forests, watershed resources, transportation access, existing land use, and soil type associations, but low potential in terms of landforms wildlife habitats, and air resources. Site 4 has high development sulta billty in terms of landforms, forests, topography/slope, and soil type association, but low potential in terms of aewer and water utilities and geologic formations.

The characteristics of the three industries selected, Food and

Kindred Products, Construction and Mining, and Furniture and Fixture

Manufacturing, were compared with the individual site characteristics derived in Submodel 2. Each of these industries offered "high" economic development potential as shown by their high Job generation character­

istics and a "moderate" environmental degradation potential as derived from the Industry profiles In Submodel 1. Food and Kindred Products had a high land consumption profile. The decision as to where the three

industries should be located spatially within the planning region is 160

Indifferent from an environmental and economic point of view except for

the Food and Kindred Products sector. Since this sector has a high land

consumption characteristic, it would be desirable to locate the Food

and Kindred Products sector at Site 2 or 4 that have favorable land

characteristics such as landforms, topography, soils, geology, etc.

Site 3 has less favorable land characteristics.

Table 29 depicts an acceptable allocation of the three industries

to the five sites analyzed. Suitable sites are indicated by an "X" in

the appropriate cell. However, if the Industry profiles developed in

Submodel 1 had a stronger differentiation of the environmental impact

potential for the three industries tested, more definitive siting

decisions could be made. Of course, it is not always possible to

attract Industry that has high economic potential like those identified

In this analysis. This is particularly true If a community has to

respond to industrial development proposals. Under these conditions,

the community may only have an opportunity to attract an Industry with

low or moderate economic potential. The model can be used to evaluate

TABLE 29

ALLOCATION OF THREE PROPOSED INDUSTRIES TO FIVE REPRESENTATIVE INDUSTRIAL SITES

Proposed Industry Site 1 Site 2 Site 3 Site 4 Site 5

Food and Kindred Products no X no X no

Construction and Mining no X XX no

Furniture and Fixture no _ X X X no Manufacturing 161

the environmental impact of these industries as veil and to provide

information on which of the low economic potential industries also have

low environmental degradation potential. The decision as to where to allocate industry should take these site sensitivities into account.

The Site Analysis Model has demonstrated the feasibility of evaluating the environmental and economic suitability of sites for pro* posed Industry. The results indicate that more than one site may be suitable for a proposed Industry. Thus, it is possible to develop more than one solution using the satisflcer concept of locating industries on sites that are good enough to accommodate the specific economic and environmental characteristics of the industries proposed. CHAPTER VI

SUMMARY AND CONCLUSIONS

The development and application of an economic-environmental trade-off model for Industrial land use planning is the subject of this dissertation. The work reported was undertaken to help meet a research need Identified by state and local administrators and plan­ ning offlclals--the need to achieve a rational balance between environ­ mental quality and economic growth.

National land use legislation currently pending In Congress as well as acts currently pending in several state legislatures are aimed at encouraging rational balanced development. The dissertation docu­ ments the development of an industrial land use planning model that can be used by state and local planners to formulate a selective

Industrial development program. The model can be used to address the key questions facing the development planner today.

(1) Which Industries should be solicited and attracted

to a region?

(2) What would be the regional economic and environmental

Impact from locating these industries?

(3) Where should the Industries be located spatially

within the planning region to assure high economic

gain and minimal environmental degradation?

The land use planning model developed and evaluated In this dissertation Is an Important contribution to land use planning research in the sense that the model responds to these questions effectively.

162 163

Application of the model provides Information basic to the design and implementation of a selective industrial development program.

Review of Propositions

Several propositions were established at the outset of this research to assure continuity and direction throughout the program.

Propositions were defined as theorems to be considered, discussed, proven, dlsproven, or unaffected by the results of the research. The following section presents a review of the propositions in light of the results developed from the research.

Proposition 1--The General Systems Approach Can Used to Develop an Economic-Environmental Trade-Off Model for Industrial Land Use Planning.

The general systems approach was used to formulate and test the land use planning model developed in this research. The approach, which was outlined in Figure 1, Included (1) the specification of program objectives together with related propositions and hypotheses, (2) the description of the industrial location land use decision process, (3) the Identification of regional and site specific location criteria for

Industry, (4) the specification of a model for regional and for site impact analyses, (5) the collection of data on a case study area, and

(6) the testing and operational use of the model on several Industrial development proposals. The advantages of this approach were that it provided a systematic approach for analyzing and representing the complex Interactions between the economic and environmental systems

Involved in industrial development. 164

Proposition 2— The Land Use Planning Model Developed Can Simulate the Industrial Location Decision Process.

The Industrial location decision process Is a complex process vhlch Includes the Identification and solicitation of desirable industries for a region. Included in this process is the need to evaluate the impact of industry on the region and on the local industrial site. The model developed Is an Impact assessment model that addresses the prin­ cipal land use and related impacts that result from industrial land use decisions. The model Is designed to evaluate the potential regional and site specific impacts from locating industry. The approach adopted

Incorporates the perspective of the state and local planner who must consider and respond to Industrial development proposals from the private sector. In this capacity, the developer generally reviews and may be expected to accept those proposals that have the highest economic benefits but least environmental damage potential for his planning jurisdiction. Thus, the model addresses a very fundamental part of the

Industrial location decision process— the evaluation of the potential economic and environmental consequences of locating Industry within a region and on specific sites within the region.

Proposition 3— The Land Use Model Developed Can Assess the Relative Impact of Proposed Industrial Land U3e Changes at Both Regional and Site Specific Levels. The Impact Can be Measured by Economic. Environmental, and Social Indicators

The Regional Analysis Model (Submodel 1) provides an Impact assessment at the county or eulticounty level. The Site Analysis Model

(Submodel 2) provides an analysis of the suitability of individual sites 165 within the county for Industrial development. Submodel 1 makes use of generalized economic and environmental data collected on a county-wide basis and provides an assessment based on a regional input-output analysis of the Impact of proposed industries on the counties involved. Submodel

2 uses the output from the first submodel to evaluate the suitability of alternative sites for accommodating the proposed industry. The prin­ cipal impacts are measured directly in economic and environmental terms only and do not Include social indicators. The social Impact of in­ dustrial locations was reflected Indirectly through such economic indi­ cators as Job opportunity and Income distribution in and outside of the counties. However, social impact was not directly measured as it was considered to be beyond the scope of this research.

Proposition 6— 'The Land Use Planning Model Can Serve as the Basis o£ a Comprehensive Planning Tool.

Comprehensive planning requires consideration of all aspects of t community development including education, health care, social services, economics, environmental quality, transportation, and many other func­ tional planning areas. The model developed concentrates on the economic and environmental impact of industrial development; thus, the model provides a basic understanding of the relationship between two important characteristics of the community which are frequently in conflict with one another. An understanding of economic and environmental relation­ ships Is required in order to develop a comprehensive plan for the future development of the planning region. This plan is implemented through a comprehensive land use development program for the region* 166

Proposition 5— The Land Use Planning Model Developed Is Generally Applicable and Can be Applied to ReelonB and Locations Outside of the Case Study Area.

The case study area selected for testing the land use planning model was the Charleston metropolitan region in South Carolina. This planning region vas selected because it is representative of a large number of medium-sized metropolitan regions along the coastline. The

Charleston region was also a convenient choice since the author was already working with several agencies in the area. Special emphasis was given to developing a model based exclusively on secondary data in order to assure transferability of the model to other planning regions. All data required for Submodel 1 were readily available from the U.S. Bureau of Census, while data required for Submodel 2 were readily available from published reports from Federal, state, and local planning agencies.

The general approach used is considered valid and readily transferrable to other planning jurisdictions similar to Charleston where a reasonable amount of secondary data is available.

Strengths of the Model

The principal strengths of the land use planning trade-off model developed are that it represents an operational planning tool for planners to evaluate the economic and environmental impact of proposed

Industry both at the regional and at the site specific level. The model Incorporates both economic and environmental factors into the analysis in order to trade off economic gain with environmental degra­ dation in the evaluation* The model is sufficiently accurate to 167

discriminate between the relative economic and environmental effects of

the various industries proposed for the planning jurisdiction.

A second major strength of the model is that it draws upon

secondary data and minimizes any dependence on primary data. Thus, the

model is transferrable to a large number of planning jurisdictions where

secondary data are available. A quick survey of the availability of

existing Information indicates that most metropolitan regions that have

' a planning agency would have the basic secondary data required to operate

the land use planning model developed in this dissertation.

A third major advantage of the model is that it provides a tool

for Implementing the Intent of contemporary land use legislation.

Planners are now required to take into consideration economic and

environmental factors in land use planning, particularly if such a land

use decision will result in a regional impact. The location of an

Industry generally has a regional Impact on the larger planning juris­

diction in that it stimulates and guides the direction of future develop­

ment. The model developed is a workable tool for evaluating the

regional as well as local economic and environmental implications of

Industrial land use decisions as required under proposed contemporary

land use legislation.

Recommendations for Further Research

A basic industrial land use planning trade-off model has been

developed and operationalized in this dissertation. Several recom­

mendations are made for further refinement in the model in this section.

Submodel 1 is based on a regional input-output analysis that assumes linear relationships exist betveen the economic and environmental coef­

ficients and the level of Industrial production. This assumption, which

is commonly made in most static input-output analyses, is important to

recognize since it means that the amount of economic and environmental

Impact generated per unit of production does not change as the level of

production changes. A review of the literature and discussions with

professionals in the field Indicated that the linearity assumption would

• not be accurate for ecological and biological variables. Thus physical

environmental variables were Incorporated In Submodel 1 and ecological

variables, that were apt to be nonlinear, were incorporated in Submodel

2. However, it is recommended that more research be devoted to de­

veloping the relationships between ecological effects and industrial

production so these coefficients can be Incorporated in Submodel 1 as

well. A second and related reconmendatlon Is that more specific data

be developed on the economic and environmental impact of industrlea.

Currently, the model lncorporatea sector-wide averages in the Impact

analysea and does not assess the impacts of individual Industrlea.

For example, the economic and environmental effects of locating a

Sector 4 industry (Textiles & Apparel Mfg.) in the planning region can

be readily developed from the model. The analysla assumes all Sector 4

industries have similar economic and environmental effects which is

obviously not always the case. However, data are not available to per­

mit a distinction between the effects of specific industries within each

sector. Several specialized studies on selected Industry were available

in the literature and were used in the data base. More studies of this 169 type are needed to fill the data gaps. As more refined economic and environmental data become available, they may be readily incorporated into the model, and a more definitive analysis developed.

Another improvement would be to develop definitive measures of social Impact and to Incorporate these measures Into the land use planning model developed. Social Impact, In addition to economic and environmental impact, Is required for a comprehensive evaluation of industrial development proposals. Social Impact Is generally poorly defined and requires the conceptualisation and measurement of social impact variables. Social impact assessment provides a third Important dimension to the evaluation of Industrial land use proposals. Currently, thia dimension is measured indirectly through the other variables in the model. Each of the above recommendations represents refinements to the land use planning model developed. The model developed is an Impact assessment methodology that can be used to evaluate the relative effects of alternative Industrial land use proposals. The model Is based on the satlsficer concept and identifies Industries and sites that are good enough to meet the region's industrial development objectives. The model Is not an optimization procedure.

The research reported in this dissertation represents one important step in the advancement of the state of the art in industrial land use planning. The model developed ties together economic and environmental characteristics In a way not previously associated and represents a practical tool that can be used by state and local planners to formulate and implement selective industrial development programs. APPENDIX A REVIEW OF SELECTED ENVIRONMENTAL

ASSESSMENT METHODOLOGIES

170 Ad Hoc Committee Approach

1. Eckenrode, R. T. "Weighting Multiple Criteria." Management Science. Vol. XII, No. 3 (1965).

This methodology is not directed toward environmental impact

per set but to the handling o£ multiple criteria in general. A team of

six to twelve experts rate the importance of criteria using several dif­

ferent ranking and rating techniques on a subjective basis. The out­

comes are compared for agreement or disagreement. This basic approach has been employed in developing weighting scores for various impact methodologies.

2. Lamanna, R. A. "Value Consensus Among Urban Residents." Journal of the American Institute of Planners, Vol. XXX, No. 4 (1964).

Priority areas of concern are identified from responses to a simple survey. Persons interviewed are presented with a list of poten­

tial concerns and are asked to weight elements according to importance on a 3 to 1 scale, 3 being most important. This method docs not insure a sound basis for indicated preferences; it determines probable areas of lesser or greater impacts, not extent of impact.

3. McKenny, C. E. B., et al. "Interstate-75; Evaluation of Corridors Proposed for South Florida." University of Miami Center for Urban Studies for Florida Department of Transportation, 1971.

An ad hoc interdisciplinary panel of experts is convened to con­

sider the qualitative advantages and disadvantages of proposed routes, making a recommendation based on a consensus judgment. Subunits of the

panel prepare written reports of probable Impacts in their area of ex­

pertise. These reports are then discussed in a series of deliberative

sessions and agreement on a recommendation is reached. 171 172

This method has been widely employed. It Is doubtful, however, whether extensive expertise could be brought to bear on all projects In a consistent manner, and whether sufficient time would be available for the painstaking preparation of reports and deliberations on a case by case basis.

Overlays

4. Baker, R. W., and Gruendler, J. D. "A Case Study of the Milwaukee- Creen Bay Interstate Corridor Location.n Paper presented at Highway Research Board Summer Meeting, 1972.

This method, developed at the Environmental Awareness Center of the University of Wisconsin's Department of Landscape Architecture, is a computer application of McHarg's overlay method. Considered is a broad range of factors including environmental, engineering, economic, and social aspects. Ten increments of shading are used to describe the total range of values varying from dark (more suitable) to light (least suitable) for each environmental parameter. The parameters are weighted according to relative importance (the weighting method is not described).

This technique, like McHarg's, does not predict actual impact, but only areas of greater or lesser impact. It does delineate those locations for which more detailed studies might be conducted.

5. Lacate, D. S. "The Role of Resource Inventories and Landscape Ecol­ ogy in the Highway Route Selection Process." Ithaca, N.Y.s Cornell University, Department of Conservation, 1970.

Highway route alternatives are compared and the optimum route selected based on a subjective analysis of "resource inventories." A resource inventory is simply the process of collecting data on a particu­ lar factor of social, economic, or environmental concern. The 173

Information produced by the resource inventories is aggregated in a series of overlay maps) thus, the method is actually the same as the

McHarg method. Unlike McHarg, however, specific features and details are not transformed into three color shades for evaluation at a gener­ alized, macroscale level. This technique, therefore, while avoiding the possible misinterpretation and unintentional neglect resulting from simplification, lacks ease and clarity in employment.

Only four overlay maps are prepared in the case study presented.

The first displays the various land uses) the second, the type and in­ tensity of farming; the third, soils; and the fourth, localized historic, cultural, and environmental values. A large series of overlays would easily result in some features being buried in detail. The advantages, in fact, of this method over a general collection and analysis of avail­ able information is difficult to determine.

6. McHarg, Ion. "A Comprehensive Highway Route Selection Method." Highway Research Record 246 (1968).

For each of several groups of environmental factors, a trans­ parent sheet is prepared. Through the use of three color shades it can be employed to divide a particular region by areas differing in vulner­ ability to environmental damage for that group of factors. By overlay­ ing all the given factors the route of "least social cost" is claimed to be "visually evident.” (This method was later expanded in a book en­ titled Design with Nature.) Extent or type of impact is predicted only indirectly, and a new set of overlays must be prepared for each new study area. 174

7* TUmec, A. K., and Hausmanis, E. "Computer-Aided Transportation Corridor Selection In the Guelph-Dundas Area, Ontario, Canada." Paper presented at High Research Board Sumner Meeting, 1972.

* This is another application of the computer overlay method. The

various parameters considered are weighted on a scale ranging from 1 to 10.

Checklists— Type A

8. Leopold, L. B., et al. "A Procedure for Evaluating Environmental Impact." U.S. Geological Survey Circular 620 (1969).

A matrix of 100 different possible actions resulting from vari­

ous types of projects and of 88 environmental factors is used as a

checklist for identifying possible impacts. At each intersection for which an impact is probable, an estimation of both magnitude and impor­

tance is made using a 1 to 10 scale. No criteria for using this scale

are'provided. This technique does not achieve much objectivity by being

quantitative because of possible bias on the part of the person rating

each interaction. The prime value appears to be as a simple checklist.

9. Kanhelm, M. L., et al. "Community Values in Highway Location and Designs A Procedural Guide." Urban Systems Laboratory, MIT, for Highway Research Board, September, 1971.

Coordination between an interdisciplinary "location study team"

and comminity groups is used in identifying impacts, the interests af­

fected by the impacts, and appropriate spokesmen for those interests.

An impact matrix is devised for each affected interest to describe each

alternative and the corresponding impacts. The information contained in

the matrix may be qualitative, pictorial, or numeric. It is the respon­

sibility of the location team to use this information in assisting a 175

"politically responsible official" to make a decision on the proper course of action.

Although more documentation and more detail might be required, and a more comprehensive and expert input be attained, this technique resembles the method developed by Leopold in both its application and its shortcomings.

10. Sorensen, Jens C. "A Framework for Identification and Control of Resource Degradation and Conflict in the Multiple Use of the Coastal Zone," Unpublished M.S. thesis, University of California, Department of Landscape Architecture, Berkeley, 1971.

A set of matrices is presented for linking uses of coastal zone areas to impact-causing factors to initial and conseqnent environmental conditions, to possible environmental effects, and, ultimately, to cor­ rective actions or control mechanisms. A separate matrix is developed for each of four broad types of development possibilities for coastal zone areas t

• Residential, coomercial, agriculture

• Recreational

• Extractive

• Industrial, transportation.

The framework is basically a tool for identifying sources and types of environmental impacts and to assist an analyst in insuring, as much as possible, that all potential impacts have been checked.

Checklists— Type B

11. Arthur D. Little, Inc. "Transportation and Environment, Synthesis for Actions Impact of NEPA on the U.S. Department of Transporta­ tion." 1971. Two methods are presented. In the first, a "multidisciplinary team of experts" rates significance of a project according to various categories of environmental deterioration (depletion of natural re­ sources, loss of parkland, decrease in air quality) on a simple scale from 0 (low significance) to 10 (high significance). The results are submitted to the decision maker.

In the second method, a list of potential environmental "credits" and a list of "debits" are prepared, to include process factors such as

"A-95 favorable comment" or-"defective 102(2)(c) statement." Positive values are assigned to the credit list and negative to the debit. Sev­ eral experts review a project, develop and compare scores, and arrive at a consensus through an iterative process. In this second method, the ranking values are fixed within a certain numerical range, but how the results are aggregated for decision making is not specified.

12. Atkins, W. G., and Burke, D. "Social Economic, and Environmental Factors in High Decision-Making." Texas Transportation Institute for Texas Highway Department, October, 1971.

After extensive data have been collected and analyzed, a person described as the "highway engineer-planner" rates each alternative on a scale from -5 to +5 for a specified group of environmental parameters.

Each alternative plan is rated using the existing street or highway as a base for comparison, +5 reflecting the maximum possible beneficial impact and -S the maximum possible detrimental impact. There is no ranking of the importance of the various parameters. Comparisons be­ tween alternatives are drawn from two computations! (1) the ratio of the number of plus ratings to the number of minus ratings and (2) the average rating calculated as the algebraic sum of the ratings divided 177 by the number of parameters* The method does not describe what criteria are to be used for setting the rating numbers, and the use of sound, unbiased, experienced judgment is not certain. Also, the method does not fully comply with the requirement that both short- and long-term

Impacts be accounted for, and that impacts be evaluated with reference to changes.

13. Highway Research Section, Engineering Research Division, Washington State University. "A Study of the Social, Economic and Environ­ mental Impact of Highway Transportation Facilities on Urban Com­ munities." Report prepared for Washington State Department of Highways, 1968.

Three forms are to be completed for each alternative route for evaluation: one based on appearance considerations, one on sociological considerations, and one on economic considerations. Various parameters describing each of these three subject areas are listed on the respec­ tive form.

In evaluating a particular route on appearance, for example, a number between 1 and 10 is assigned to each appearance parameter to de­ scribe the route's "desirability" for that parameter. The rating is to be done subjectively by the "administrator and his staff." The rating number is then multiplied by a weighting factor which has been estab­ lished by administrators and interested citizens prior to the route rat­ ing process) the weights are to reflect the objectives the road is in tended to serve. (Hence the technique is more an effectiveness evalua­ tion method than an impact-assessment technique, since environmental impact is not a function of project objectives.) This process is re­ peated for each parameter three times, as the life of the project has been divided into periods of from 0-5 years, 6-25 years, and 26-50 178

years--the weights and desirability rating may change with time. The

combined 50-year weighted ratings for each appearance factor are aggre­

gated to indicate the overall appearance rating. If a route has similar

conditions throughout its entire lengtht it can be rated as one section.

If not, the overall rating for a portion is multiplied by the ratio of

its length to that of the entire route* (This process, unfortunately,

would'make the importance of a particular portion dependent upon its

length. Also, no criteria are presented to determine when similar con­

ditions are or *are not present.)

Finally, the total weighted rating values on the appearance,

sociological, and economic forms completed for each route are listed

with construction cost and other monetary considerations on a "Route

Comparison Form." This method is very subjective, and as Is stated, its

value "depends on the skill and ability of the user.* Quantification in

this technique appears to be primarily for the purpose of making the

decision process systematic.

14. Hill, M. "A Method for Evaluating Alternative Plans: The Goals- Achlevement Matrix Applied to Transportation Plans." Unpublished Ph.D. dissertation, University of Pennsylvania, 1966.

A matrix is prepared. Across one axis are specific environ­ mental goals (e.g., decrease in air pollution)} the other axis contains

various land use categories (e.g., residential districts, open space),

subdivided into specific areas, buildings, and so forth, which are af­

fected. At each specific subdivision-goal intersection, a "+," or

is used to Indicate for each alternative route whether there is an

increase in goal attainment, a decrease in goal attainment, or no change.

A comparison between the alternatives themselves in then made at each 179 land category-goal intersection, using the results of the more specific intersections as a basis for judgment. In other words, each alternative is first compared against the attainment of a goal for a group of spe­ cific locations, then compared against another alternative for the broader land-use category; with the basis of the latter comparison is based on how each alternative fares in the first comparison (in terms of the number of plus's, minus's, and equal signs). By examining the matrix horizontally, a comparison can be made between alternative routes in terms of one specific location for all the goals. By examining the matrix vertically, a comparison can be made in terms of one goal and all the land-use categories.

Many subjective decisions are required with this method, both in determining goal achievement for an alternative and in determining the relative importance of each land use category and each goal. Further it is more suited to assessing the degree to which project objectives/ goals and met then in assessing environmental consequences of meeting these goals/objectives.

15. Klein, G. E. "Evaluation of New Transportation Systems." Defining Transportation Requirements— Papers and Discussions. American Society of Mechanical Engineers, 1969.

This technique was designed to evaluate systems in terms of eco­ nomic and social factors; the method could possibly be'applied to envi­ ronmental factors. A utility index similar to the "value functions” devised by the Battelle method is employed. Instead of one function defining the quality state, two functions representing the upper and lower limits are presented. The evaluator is allowed to make a decision somewhere between the two extremes. Specific criteria used in 180 establishing the functions are placed on the horizontal axis to a 0-10 utility scale. Zero on the utility scale represents the best situation ten the worst, and the utility index for each factor is translated di­ rectly into dollar figures. This dubious procedure is intended to put actual dollar signs on intangible values; the total evaluation is based on relative costs and benefits among alternatives.

16. Oglesbyt C. H., Bishop, G., and Willeke, G. "Socio-Economic and Coimunity Factors in Planning Urban Freeways." Stanford University research project for California Transportation Agency, October, 1969.

For those nonmonetary aspects of a highway project a "profile" of alternatives is prepared and a list of environmental factors is devel­ oped. The route with the most beneficial (or detrimental) effect for a particular factor is set at 100 percent (or -100 percent) for that par­ ticular factor. The effects of the alternative routes are then expressed as a percentage of the effects of the best (or worst) for that factor.

The results for all factors considered are shown diagramaticaily on a scale from -100 (worst) to +100 (best). Any alternative routes that are clearly dominated are eliminated. Paired comparisons are made for the remaining alternatives. Subjective decisions are required, as each factor is considered separately (there is no categorization or grouping) and there is no ranking of factors. The concept expressed is that sub­ jective decisions must be made and that a systematic, organized process of data presentation is most appropriate.

17. Southeastern Wisconsin Regional Planning Commission. "Land Use Transportation Study— Forecast and Alternative Plans 1990." Plan Report No. 7, Vol. II (June, 1966). 181 Various environmental objectives are stated. These are ranked in order of importance for each situation, then weighted values are as* signed on a direct reverse listing of the numerical importance rank.

Each of the alternative projects or routes is then rated against the environmental objectives--no particular rating value system is specified.

The two numbers for rating and ranking are multiplied together for each objective, and the resulting values for all the objectives are added for each alternative. These final values represent the evaluation of spe­ cific alternatives against their achievement of the objectives and can be used for comparison.

In this method, the assignment of weights is arbitrary rather than objective. Subjective judgments are required in ranking and in the rating of alternatives against the objectives. Some measure of the rela­ tive value of alternative plans is achieved, but impact itself Is not determined.

18. Dearinger, J. A. "Esthetic and Recreational Potential of Small Naturalistic Streams Near Urban Areas." Water Resources Institute, University of Kentucky, April, 1968.

This technique was designed for evaluating esthetic and recrea­ tional aspects of small streams. Environmental factors, such as water quality, wildlife, and scenic views were weighted on a scale from 1 to 5 depending on their importance for types of potential recreational uses: hiking trails, canoeing areas, etc. In evaluating a location, a rating number is established for each particular environmental factor in each use category. This number is between 1 and 10 and is determined through a set value function (e.g., BOD and turbidity for water quality). The weighting and rating numbers are multiplied for each factor and the 182 results from all the factors added for each type of use. This final number is made a percentage of the number that would apply to the suit­ ability of the location for a use if all conditions were optimum (all rating numbers equal to 10).

19. Dee» Norbert. "Environmental Evaluation System for Water Resource Planning." Battelle-Columbus Laboratories for the Bureau of Recla­ mation! U.S. Department of the lnteriorf January, 1972.

A total of 78, explicitly defined environmental "parameters" are used to assess environmental impacts of water resource development proj­ ects. These parameters are arranged in a hierarchical structure of four major categories— ecological, physical/chemical, aesthetic, and human interest— and 17 subcategories or "components." With each parameter is associated a "value function" which describes the range of quality with­ in that parameter. Each particular state or level a parameter (e.g., concentration) is associated with an environmental quality value ranging from 0 to 1, the number 1 representing the best possible situation.

Thus, using the criteria specifically established for each function

(e.g., dissolved oxygen In mg/1), the environmental evaluator is able to establish the environmental quality that would exist if no project were undertaken, as well as predict the resulting quality after a proj­ ect is built. These two numbers can be employed to measure actual change in environmental quality for each parameter.

All parameters are not held to be of equal weight in terms of overall environmental quality. Instead, the relative importance of each parameter is determined by an interdisciplinary team of experts using the Delphi technique. A total of 1,000 "environmental quality units" is assigned to the entire system, and through this Iterative process a 183 consensus Is reached on the optimum distribution of these units among all parameters. By multiplying the weighting for each parameter times the measure of its quality (the environmental quality number from 0-1 determined from the value function) t and then combining the values from all parameters for both the "with" and "without" project situations, the overall change in environmental quality, or impact, can be determined.

Besides measuring relative overall environmental impact, the method also provides a system of major and minor "warning flags" to indicate those parameters for which impact is particularly large or intense. If the change in a parameter, as shown by the value function, exceeds a certain set limit, a warning flag is raised (the type depends on the extent to which this limit is exceeded). Provision is made for analysing short-term and long-term impacts.

20. Institute of Ecology, University of Georgia. "Optimum Pathway Matrix Analysis Approach to the Environmental Decision-Making Process." 1971.

A linear combination of 56 environmental parameters categorized into four areas (economic and engineering, environmental and land use, recreation, and social) is employed as a quantitative method to choose the optimum route with the aid of computer programming. The parameters are weighted and scaled on a project-by-project basis by a panel of six experts— three from the environmental field and three from the social and economic. Long- and short-term impacts are considered with the im­ portance of long-term impacts weighted ten times that of short-term im­ pacts.

This technique is rather sophisticated! however, if the paramet­ ers are developed, as well as the weighting and scaling, on a project- by-project basis, comprehensiveness and judgment would probably not be achieved* The relevance of several of the parameters employed in deter­ mining environmental impact is also questionable.

21. Orlob, C. T*f et al. "Wild Riverss Methods for Evaluation." Water Resources Engineers, Inc., for the U.S. Department of the Interior, October, 1970.

Nonmonetary and intangible values are expressed in dollars, on the premises that such values are at least equal to the economic devel­ opment benefits that are foregone in favor or preservation, and that nonmonetary benefits equal between 0.25 and 2.0 times monetary benefits.

Environmental values can then be subjected to benefit-cost analysis.

The assumptions made in this method are arbitrary, and no provision is made for analyzing the nonmonetary environmental impacts of development.

The evaluations required are very lengthy mathematical computations.

22. Walton, L. E., and Lewis, J. E* "A Manual for Conducting Environ­ mental Impact Studies." Virginia Highway Research Council, June, 1971.

An environmental team conducts an Inventory of residences, pub­ lic buildings, and businesses affected by a certain project location and multiplies the actual number count times a predetermined weighting

(scaled from 1 to 10). Noise, air, and water pollution impacts are quan­ tified as the number of persons affected times the percent increase; the percent increase for noise is measured in dB(A), but units of measure for air and water pollution are not defined. Dollar values are assigned where appropriates change in tax base, relocation impact. An "Environ­ mental Ratio Worksheet" is drawn up after the study is completed to com­ pare alternatives according to the weighted environmental impacts and dollar costs and benefits. No mention is made of bow the weights were 185 established or why the methods used for determining impacts (e.g., per­ centage increase times number affected) is valid. The list of environ­ mental factors Included is crude and extremely incomplete.

23. Lewis, P. H. Upper Mississippi River Comprehensive Basin Study. Washington, D.C.t U.S. Department of the Interior, 1969.

A comprehensive environmental assessment methodology was devel­ oped and applied by Lewis to identify, locate, and evaluate significant landscape features for the development of an open space system in Iowa with multiple use potential. The procedural analysis encompasses ten steps Including an analysis of (1) demographic characteristics, (2) human desires, (3) kinds of uses, (4) selection of a case study, (5) inventory of major resources, (6) inventory of additional resources,

(7) numerical rating of major and additional resources, (8) summation of point scores, (9) assessment of demand and priority setting, and

(10) allocation of resource uses based on resource assets and limita­ tions. The resource Information is displayed and evaluated through a series of map overlays that depict resource nodes and resource corridors. APPENDIX B

LAND AREA REQUIREMENTS OF SELECTED INDUSTRY

AND TEST OF LINEARITY OF LAND COEFFICIENTS

186 la nd area requirements o f se lected i» ustry

AND TEST OF LINEARITY OF LAND COEFFICIENTS

A comprehensive survey of land area requirements for selected industries was conducted for the U.S. Department of Transportation in

July, 1970. The total land area, parking area, and building site area for each three and four digit SIC was computed on a per employee basis.

The information extracted for use in the regional input-output table is presented in Table 30.

For example, it was computed that Agriculture, Forestry,

Fisheries (Sector 1) consumed an average of 56,509 square feet per employee, while Food and Kindred Products (Sector 2) consumed 2,256 square feet per employee. Some of the data for parking area and building site area in the table seem erratic. This was probably caused by the small size of the sample included in the survey. For example an Inordinately large amoung of parking apace was reported for Stone,

Clay, and Glass Products (Sector 11), while Transportation (Sector 14) reported a large building area. In each case, the saaple size is small and probably includes a few a-typlcal industries, however there is no way of verifying this conclusion from the data available. The survey results are believed most reliable for the total land area data. This variable had 16,042 respondents while only 2,463 responded on the parking variable, and 1,689 establishments responded on the building site area variable.

187 188 TABLE 30 LAND AREA REQUIREMENTS OF SELECTED INDUSTRY PER EMPLOYEE

SIC Land Parking Building Site

1 56,509 . 2 2,256 359 711 3 1,646 159 120 4 718 186 308 5 2,227 286 650 6 1,241 378 697 7 849 145 379 8 5,536 377 491 9 19,752 655 391 10 2,158 193 573 11 4,555 13,574 528 12 2,419 270 530 13 910 164 322 14 11,952 1,350 2,574 15 426 30 m 16 14,287 204 110 17 1,718 - to 18 500 - to 19 4,631 666 - 20 1,877 4,438 25 21 1,152 113 - 22 1,782 716 - 23 1,180 346 178

Source; Edward A. Ide, Estimating Land and Floor Area Implicit In Employment— How Land and Floor Area Usage Rates Vary bv Industry and Site Factors. U.S. Department o£ Transportation. July, 1970.

The data presented In the table were summarized for each four digit SIC sector and were incorporated in the data base as Variables 17,

18, 19, and 20. A test was constructed to test the linearity of the total land coefficient (Variable 17) using correlation analysis* The test correlated (1) the rate of land use for each sector with (2) the level of industrial production. Employment in each sector was used as a surrogate for the level of production* 189

This experIntent was used to test an important assumption of input-output that a linear relationship exists between the environmental and economic coefficients used in the model. Basically, this assumption implies that the rate of environmental impact is unaffected by the level of industrial production (e.g. the rate of environmental impact per unit of production would be the same at a level of output of one dollar as it would be at a level of one million dollars). The purpose of the test was to determine if this Is a realistic assumption for physical environmental variables such as land area, total water Intake, etc.

To test the linearity assumption used in developing the physical coefficients, an experiment was conducted using correlation analysis on

208 caBes for which detailed data were available. The experiment was designed to determine the correlation between land usage rates and the level of industrial productivity. The results of the analysis are reported In Figure 18. The data are incomplete in some SIC sectors; however, it Is demonstrated that a basic relationship of linearity does exist between land usage races and the size of the Industry. A correla­ tion of .31182 was computed for the 208 cases with a significance of

.00001. The linear relationship appears to break down or deteriorate as the size of the firm Increases. It is assumed that smaller size plants are older plants in more congested areas where land consumption rates are relatively controlled. However, newer plants in suburban locations have a weaker relationship because of expansive designs utilizing large quanti­ ties of landscaping or large parking lots on less expensive suburban land.

Under such conditions a weaker correlation would exist. This test was 190 not conducted for other coefficients used In the model since the required detailed data vere not available.

As discussed elsewhere, most ecologists suggest that nonphysical ecologic variables are nonlinear to production. Thus physical environ­ mental variables were incorporated In the regional input-output analysis while ecologic and biologic variables were incorporated in the site evaluation submodel. . «e£rixic« ra.tmTtnc.enuu

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» i r

id u APPENDIX C

DEVELOPING A REGIONAL INPUT-OUTPUT MODEL

194 DEVELOPING A REGIONAL INPUT-OUTPUT MODEL

The development of a regional input-output model is faced vith two principal problems. First, it Is necessary to calculate local coef­ ficients representing local interindustry trading. Second, it is nec- cessary to estimate the expo'rt-import balance for the region, that is, the value of goods and services produced and consumed locally versus the amount Imported to or exported from the region to the rest of the world.

Primary data can be collected and analyzed to develop local trading coefficients and an export-import balance, but these procedures are generally time consuming and expensive. The emphasis in this dissertation

Is on utilizing secondary data and acceptable secondary data manipulation procedures. Consequently, a literature search was conducted to identify secondary data and data manipulation techniques that could be used to develop the regional input-output model for the Charleston region.

Comparative Evaluation of Alternative Nonsurvev Techniques for Constructing Regional Interindustry Models

Schaffer, Chu, Miernyk, and others have suggested several tech­ niques for constructing regional interindustry models. An excellent

195 196 survey of these techniques was completed by Schaffer and Ghu who discuss three families of techniques.1

• The locatlon-quotlent procedure, with three variations:

the conventional location quotient, the purchases-only

location quotient, and the cross-induBtry location

quotient;

• The commodlty-balance or supply-demand pool procedures; and

• An Iterative simulation procedure.

A comparative evaluation was conducted by the authors using the various methods discussed to construct a regional interindustry model for the State of Washington for the year 1963. These estimates were compared to a survey based table of the State which was arbitrarily assumed to be accurate. The Schaffer and Chu survey is summarized below because of its significance to this research. The authors

.••computed balanced transactions tables followed by tables of direct requirements, direct and indirect requirements, direct, Indirect, and induced require­ ments, and income multipliers....The locatlon-quotlent procedures required balancing corrections. Industries with location quotients greater than 1.0 were expected to show exports after satisfying local input require­ ments. They did in all (nine) cases excepting the food and kindred products Industry, for which local gross flowB had to be reduced below the amounts required by local purchasing industries. On the other hand, industries with location quotients less than 1.0 are expected to produce less than required locally. This

Hfllllam A. Schaffer and Kone Chu, "Comparative Evaluation of Alternative Nonsurvey Techniques for Constructing Regional Interindustry Models", Papers of the Regional Science Association. Volume XXIII, 1969, pp. 83-101. 197

was true in all (14) cases excepting the Iron and steel Industry, which produced a slight surplus for export. To balance the grosa-flows tables for both the simple location quotient and the purchases-only location- . , quotient procedures, the location quotients are adjusted.^®' After these adjustments, the results of the two proce­ dures are identical, since the input requirements of local Industries are completely satisfied and the remaining output of a selling industry is exported or the regional gross flows for a row are computed as a constant proportion of national gross flows (but less than required) for that row and exports are rero. And again as noted, the cross-industry quotient procedure may yield negative exports and gross flows might have to be adjusted. But exports are positive in the test model, and no adjustments were required. The pool and Iterative procedures were self-balanctne.

To compare the estimated regional production coeffi­ cients with the survey-based coefficients, we com­ puted chi square for each column in the direct requirements tables for each estimating method taking the survey-based coefficients as true values. Though weak, the results arc fairly consistent, see Table 2. By the chi-square test, we have no reason to reject the hypothesis that the nonsurvey methods can yield production coefficients which are the same as the survey-based coefficients for only seven indus­ tries. Surprisingly, the locatlon-quotlent procedures (after balancing) and the cross-industry quotient proce­ dure are the most successful, followed by the iterative procedure.

TA B LE 2 INDUCTKICS WITH ACCIFTASU PRODUCTION CoirnCUNTS

Location* Cross* Iterative Industry Quotient Industry Pool Procedure Methods Method Technique (R -I-0 -T )

Food and kindred products X X X X Lumber and wood products X Stone; clay, and class products X X XX Construction XX X Communications and utilities X X X B id s X XX X Finance, Insurance, real estate X X

Note; x Indicates that chi square for this industry (column) is sufficiently small to be wiihin the acceptance region, with a - ,03, ^ G r o s e flows become x . . ■ A..»LQ.* *1 whichever is 1 (xt - et) greater. 198

Although the Iterative procedure yields the closest estimate of total imports into the state, the cross- industry procedure yields the best estimates o£ imports by Industries alone o£ exports, see Table 3. Both Imports to industries and exports are lowest for the Iterative procedure, but, since it attempts to allocate the maximum possible of local output to local trade, these low estimates are expected.

TABLE 3 T otal I mports , T otal Exports , a ^o M can I ncome MuLTtrutRS rox the State of W ashington , 1961

Mean Total Imports Income Multiplier; Estimating Method to Total Imports Exports Industries Simple Total

Survey 4367.7 2424.2 3317.4 1.365 2.262 Location quotient 4624.7 1892.5 2007.0 1.638 3.329 Cross-industry quotient 5496.9 1972.6 2878.8 1 .887 3.444 Foot 4619.0 1897.7 2000.9 1.669 3.353 Iteration (R -I-O -T) 4619.0 1624.I 1805.3 1.872 4.061

When compared with those based on the survey, mean income multipliers are high for each estimating method. When only direct and indirect income changes are accounted for in the simple (Type 1) multipliers, the locatlon-quotlent procedure yields multipliers which average only 21 per cent higher than survey results while the cross-industry method produces multipliers which are 38 per cent higher. When Induced income changes are also considered in the total (Type II) multipliers, the mean multiplier under the locatlon-quotlent technique is 47 per cent higher than for the survey and under the iterative procedure is 79 per cent higher.

Miernyk has also suggested the use of location quotients for

adjusting national input-output coefficients to regional input-output

coefficients. Miernyk used both the locatlon-quotlent and the cross-

industry quotient procedure to develop regional coefficients. The

Miernyk approach develops location quotients based on Interindustry

^Schaffer and Chu, "Comparative Evaluation", pp. 94-96. relationships. The location quotient for industry 1 on Industry J (Iftjj) is defined as the ratio of regional employment in industry i to regional employment in industry j divided by the ratio of national employment in

industry 1 to national employment in industry j. If HJjj > 1 * the national input coefficient is considered to be representative of the region and is transferred directly from the national to the regional

table. If UQj^

the computed coefficient and the national coefficient is transferred to

the import row of that sector. This test assumes that deficiencies in

regional production capacity will be fulfilled by imports from outside

the region.

The cross industry location quotient method suggested by Miernyk,

Schaffer and Chu was used to develop the regional technical coefficients

used In the Charleston regional table. The computed location quotients

for each SIC sector Included in the 23-sector Charleston table are shown

in Table 31. The adjusted regional lnput-output coefficients computed

for the Charleston region based on these location quotients are presented

In the text and were used In the production runs of the model presented

In Chapter V of this dissertation. TABLE 31

LOCATION QUOTIENT, CHARLESTON SMS A, 1970

f i t 121 . 11) tb l 151 ID 17) I D 111 IIM 1 . at, * rri?*tci t . ; s t 1.1113 6.7251 6 .4126 6.3545 6.4711 (.4319 ?.?:*3 ?.?*** 1 .4 1 *4 ». r9C1 * st'iiiri? t.»"U 1.1166 6 .6 *7 5 6 .7 4 *1 6 .317 4 9 .2 49 4 *.»?« 8 .* 4 ( 4 2 .1 71 7 1 .4 .1 ) 4. CtM” !!??!!'* » 1.114b 14.4143 1 .693 3 4.3121 •.**42 4.3183 4.1*31 5.7927 4 2.17 94 4 .0 *4 3 b . TCrritr • •"( 1.1121 3 .111 2 6 .2 2 1 ! 1 .636 3 6.1*66 6.4662 8.4*41 2 .2 1 4 ) 7 .3 7 6 * 1 .4174 s . iw *js . to«y) •ta'iiri*; 1 1 .61 66 1 .745 9 16.1161 1.1(86 11.3116 1 5 .4 7 1 * 3 7 .3 *5 4 1 2 1 .7 (6 4 3 9 .5 3 *4 t . nntiriillr ♦ «'t»Tii»r art l.l?V 3 .1 1 7 * 6.2126 1 .6176 6 .3 (1 3 1.3CC4 C.4637 2 .2 7 1 ! 7 .1 (4 6 1 .1 4 *4 f . •‘s lit - .* * : • 1.1211 J.1216 6.7bt! 1.6514 6 .363 4 1 .0 *6 4 1.3783 2 .1 *1 4 7 .7 7 9 7 1 .1 1 (1 • t r . f i u 3 .4 *1 ? 1.51*6 6.1)21 6.4194 (.1 2 7 6 6 .1 *6 2 6.1224 1.6(39 3 .2 45 7 9 .*2 1 6 1. rri’u r/" • IM*1 f*#K,>ll 6 .1 *2 1 6 . b i l l 6.6111 6 .1 35 6 6 .9 ra ? * .1 ) 1 0 6.1247 6 . 1 : * ) 1.8(60 •.?*(« 1C. n tfip • ttifii? 6 .4 t1 7 I.D»* 1 .1 2b ! 6 .5 *1 2 6.1174 6.43b? 6 .5 1 3 * 1.2151 3.4*7* i . i : » it. ft VI?. ctl*. * f.t«—: rtooi t . 1 7 7 1 * 1.1161 9.2153 1.1471 6.6731 1.1*31 1.3444 2 .4 9 7 * 6 .5 1 *5 2 .1474 p . • . f j l i ■jH'jta l.b « b » 11.1112 6.7421 l . l t b * • . i t * : 3 .193 3 3.2416 7.7(4* 25.3197 *.1.14 i * . xtirinc’ll't* e . t i 2 i e.Jici 6.6*1* 6.1143 6.1676 1 .1 1 7 * 6.1(92 (.2541 •.•1*2 6.2125 1b. 1•■622 1 .3 1 b ! 6.1171 1.77(6 6 .1 (7 * 1 .7 *5 6 1 .4 64 4 3.4*»5 11.1(1! 3 .2 9 )5 i t . ••■ 9 *1 1 .1 15 2 6.1416 6.51*1 6 .1 2 3 * 6.1776 6.1(77 0.444A ?.»**» 3.715? )». • j M i t m * ; 4 ,7 41 1 11.111! 1.1)52 5.6415 6.1114 5 .6 7 (1 5 .1 8 5 ) 1 2 .7 4 (9 *1 .4 4 7 6 1 1 .5 1 4 * I’. *tT1 • * iitMfi***; Ptarrt t l . W i T 15.21*2 1.8157 1 3 .15 44 6.115? 13.1(64 17.7774 18.2174 64.245* 2 * .* 4 4 7 -'1^1'. * t-nttv; *l*rr* ?.(i?r 1.4561 6 .4 *4 1 2.6141 6.1214 2.971! 1.5*24 * . 5 * 1 * 1 9.1412 1.7435 11. d s i i i w ; e »* k * s t »t w « 2.1121 2 1 .1 2 1 * 1.1143 6.4764 6.1722 * .( 6 6 6 *.6 1 7 3 15.**49 51.1143 !!.»’•) d •*£.■' mit'tUE Oftm 12.»1%1 *1.112* 2.7431 12.1611 6 .7 1 7 ! 1 2 .6 3 *6 11.56 5 4 2 7 .1 5 1 * 69.9466 22.5tat 2 1 . 2 .1 f t ? l . l l b t 6 .1 5 *1 2 .651 0 6 .1 7 2 ! 2 .6 2 (2 2.7(41 (.4872 ? l.J « ? 8 5.2711 P. l . V b i 1 .3 55 b 6 .2 44 8 1 .212 1 1 .177 7 1 .7 )7 7 1.2171 7 .*7 4 1 4 .1 5 4 * 2 .1 ( 4 * 2 * . r tttfs ♦ **ir S iM 2.3941 *.1 2 1 1 0.1717 2.1511 6 .1 2 1 * 2.8276 1.114) * .* 1 9 2 1 4 .1 1 *1 1.7911

1111 1121 1111 1141 115* 1111 117) 111) 1141 •261 1 . »<:. » *|4 M r4 fp s 1 .1 b lb 5.2111 4.51*6 6.5512 2.4171 6.172* 6.1736 6.4661 . 6 .1 *1 6 6 .646 7 *.»«’ ♦ |.t j r . r p ' f .M C b 6 .1 3 *2 4.1131 6.9174 2 .7 1 4 * 6.1446 6.0741 6.4114 6 .1511 6 .6 1 (5 «. ‘.iiiinniB 'sa 3 .» » S i 1 .1247 1.4714 1 .211 7 1 .1 * 4 ! 6 .074 2 6.3111 8.2177 6 .3 4 1 4 3 . 1 H * •. ®S»’ riE ,i'* * c n n m o i u c t * 3 .112 2 6.614! 1.1746 6 .0 7 *1 6.1560 6.6234 6.6101 0.6(43 6.at** l . l l t t )!. "LittlC * ?U*TE* l . b t r i 6 .1 5 7 * 4.7)6! 2.3146 1.1972 6 .(9 4 1 6.8192 6.2(15 9.8776 6 .8 1 1 * 11. fffit, Ct*». * *51*11 r»»«* l . C I I 6.111* 16.6424 6.6413 2.1976 6.2(12 8.6446 6 .5 (5 5 6 .1 ( 4 * 6 .1 4 5 ! 1’ . • m u j w i n 2 .H 2 1 1.3)10 24.6113 1.412! 6.4*52 6.1231 6.2451 1.1761 6 .1 4 3 5 9 .2 * 1 ! 11. •tvt'u.oM'm '•fwiritiu*!* j.im 6.6115 1.1300 6.6*17 6.2514 2.0202 C.0C45 6.056? 6.61*5 8.634* l b . tti-j'ppnrni 1.5111 6 .5 1 7 * 15.15)1 l.C6)C 4 .4 4 *1 6.312C 6.1328 3.4MJ 6 .2 1 * 4 6 .1 *4 4 I t . f f *-nJtlltfZ J . i i b * 6 .1121 3 .1 *1 7 6.2146 1.1330 6.6(46 6.6214 6 .1 4 *3 9.6556 9.311! I t . uttlUIE-. b .i» J 2 1*1546 14.5112 3 .231 7 14.144? t.QtCl C.12.1* 2 .7 *7 4 6 .9 1 *4 0 .1 (7 1 1 * . *WK ♦ M M U U l f t l 11.1121 3.4141 117.J411 7.5712 3 4 .7 *7 7 ? . i r * t 1 .6 (6 8 • *.5 7 * ? 1.4314 1.1349 11. m t * l ; • nufii n»crt 1.7*4* 6 .5454 17.7115 1 .1 5 1 7 5.2423 . 9.354* 6.1426 1 .6 3 6 ! 6 .2 91 9 6 .1474 11*r.»:u»w ‘■miou «.cm 2 .6 2 4 * 60.6206 3.42*6 17.4941 1.22*3 6.417! 9.46(7 t.oeoo 6.4723 *C. ^TH!-9 I I P ®F11IL t 9 .474? 1 .5 .2 4 1 6 5 .4 1 1 * * .* 4 7 7 11..5H 2.134! 6 .4 85 2 5.4543 1.7*76 1.0361 >1. r i M M t • ? .b M 5 6.1111 71.6144 1 .616 4 7.1*77 6.5(13 6.2126 1.39*4 6.K4* 6.211.1 2 2 . P f U r j m t 1.1111 6.173b 11.1125 6 .7 *1 1 3.316* 6.2252 6 .8453 6 .6 7 *7 6 .1 (1 8 6 .1353 rttrr* . Pint 574* 1.7?** 6.1114 17.4514 1.1556 5.3002 6.3(0* 6.1525 . 1.663* 6.24*5 9.1(75 201

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MODEL SENSITIVITY TO FAMILY SIZE AND IN-MIGRATION RATES

202 MODEL SENSITIVITY TO FAMILY SIZE AND IN-MIGRATION RATES

Submodel 1 Includes two Important input variables, (1) average size of in-migrating families and (2) the percent of labor force that ln-oigrates to the region. All production runs of Submodel 1 reported in the text assumed an average value of 3.5 members per family and a

50 percent in-migration ratio.

A sensitivity test utilizing data from Charleston, South

Carolina, was conducted and is reported to test the sensitivity of the model to these input variables. Six output variables were monitored including particulates, 5-day BOD, solid waste, total water Intake, land area, and number of employees. The test included running Submodel

1 several tlmcB using a range of values for the variables indicating average family Blze and proportion of ln-mlgratlng families and monitor­ ing the changes that occurred in the six output variables. The average size of in-migrating families was tested at values of 2.5, 3.5, and A.5.

Each time the proportion of in-migrants to the region was held constant at 50 percent as in all production runs in the text. Next the test was run again, UBing proportion of ln-mlgrants to the region at values of

0, 50, and 100 percent with the average size of in-migrating families held constant at 3.5 members per family. The results of the test runs are ausmarized in Table 32.

203 204

TABLE 32

RESULTS OF SENSITIVITY ANALYSIS FOR VARIABLES: AVERAGE SIZE OF IN-MIGRATING FAMILIES (AVS) AND PROPORTION OF IN-MIGRANTS (PNI)

Sensitivity to Average Size of In-Migrating Fomiliea (AVS)

AVS - 2.5 AVS 3.5 AVS 4.5 PNI - 50 PNI 50 PNI 50 Particulates (lbs) 771,876 781,495 791,113 5-Day BOD (lbs) 516,446 523,846 531,247 Solid Waste (cu yds) 43,829 44,210 44,590 Total Water Intake (gals) 7,553 7,640 7,726 Land Area (sq ft) 2,819,654 2,934,861 3,050,075 Number of Employees 466 490 514

Sensitivity to Proportion of Tn-Mierants (PNI)

AVS 3.5 AVS - 3.5 AVS - 3,5 m . — 2. FHI.-— 5&. PyiJLlOfl- Particulates (lbs) 747,834 781,495 815,163 5-Day BOD (lbs) 497,945 523,846 549,751 Solid Waste (cu yds) 42,877 44,210 45,542 Total Water Intake (gals) 7,337 7,640 7,943 Land Area (sq ft) 2,531,670 2,934,861 3,338,140 Number of Employees 405 490 575 The results Indicate that Submodel 1 is sensitive to both

input variables. The sensitivity o£ the model ranges between 1 and

2 percent for each person added to the variable average size of in* migrating families (AVS). Similarly, the sensitivity of the model

ranges between 4 and 5 percent for each SO percent increase in the variable proportion of in-migrants to the region (PNI).

The model sensitivity is due to the final demand vector in

the regional table that is inflated by the amount of new local con*

sumption generated by the Increased family size or proportion of ln- mlgrants. While the model is not considered to be overly sensitive,

it is important to develop accurate data for both of these input variables In Submodel 1. The actual input values used in the produc­

tion run in the text were 3.5 persons per family and 50 percent ln- mlgration, respectively. The values were based on the best estimates

available from South Carolina officials and local developers consulted during the study and are considered accurate for use in the model for

the Charleston region. APPENDIX E

RESULTS OF IMPACT ANALYSIS FOR 300 NEW i EMPLOYEES BY SECTOR DERIVED FROM SUBMODEL I

206 TABLE 33

YRTAL T ^ A C T GENERATED OY STHULATM NEW EMPLOYMENT. TN'UISTRY GROUP 0 1 * 1970

1 . p a ®t y c u l a t e S(L"S» 203«B57 2.HY0R0CAR9CNS(LDSI 9 1 .1 0 7 3.sulfur mi oxideil«si A li2 7 7 6 * g a s f o u s f l u o r id e i l *»s i 0 5 . h yd r o g e n SUL® W E IL OS 1 R65 6 .c n 2 ilpsi 37.011 7 . ALOEWYnES(L®S 1 1 (1 1 2 A.NO 2 IL ° S I . 1 5 .2 8 0 o.BOMFSTTC WATE*>(GALS» 29 19.COOLING WATCR'GALSI 336 ll.PR D C C SS WATER (GALS1 1 (6 1 9 1 2 .TOTAL WATER TNTAKEIGALSl 1 .0 0 6 13.0IStMARGE(GaLSI 769 1 6 .5 nay d o d il d s i 9 0 .6 9 3 1 ? . s u s p e n d e d s o l i d s (LRSt 6 7 .5 3 1 16.SOLID WASTEICU YOSI ’ 3 .8 7 7 I7.tasn Ate-Acso m 16*077.280 1 0 . FLOOR SPACEISQ FTI 2 0 0 *6 6 5 1 9 . PARKING AREA(SO F T I 1 8 8 .C 6 9 29.BUILDING SITE (SO FTI 9 3 .1 1 1 7 1 . NUMBER o r EMPLOYEES 661

NUH9ER or snupacn n"vian«M<: f p p n m e a n rot i n p a c t g e n e r a t e d b y s im u la t e d n e w f m p l o y n e n t * I n o u s t r y g r o u p 01* 1970

l.PA?TirULATESILR5I • 0 . 3 6 2.HVOBOCARROHS(LnSl -0.27 3. SlILFU? OIOXMEILMSI -C.2S 6 .GASEOUS FLUQRIQEILflSI 0 .0 0 S.NYDROGew SULFTOr (LRS) • 0 . 2 5 6.CO 2 (LPSt • 0 . 2 2 7 ■ ALMr H *i’ E5 (LMSI • 0 . 2 6 8.NO 2 (LRSt - 0 . 2 5 B.OP^STI'*. waterigalsi - 0 . 6 9 10.CCOLING WATERIGALSI - 0 . 3 1 1 1 .PROCESS UATr9 (CALSI - 0 . 2 7 1 2 . TOTAL WATER INTAKE(GALSI • 0 . 2 6 l3 .',TSCwaor,E(r,»Lsi • C .2 7 16.5 DAY DODILDSI - 0 . 2 7 15.5USFFNPE0 SOLinS(LRS) - 0 . 2 7 1 6 . SOLID WASTEICU YOSI ■ - 0 . 2 7 1 7 . LAND AREA(SQ FTI 3 .6 9 1 8 .FLOOR SPACEISQ FTI • 0 . 0 9 19.PARKING AREA(SO FTI - 0 . 6 5 20.BUTLOING SITE (SO FTI -0.70 2I.NUMPEP OF ENPL0YEE5 - 0 . 6 5

K> o •vj TABLE 34

n v ^ s s ^ s s s s s s b s s s — a a s g g g s a a rnj r~ r- ■ s sas asaaa aa" , m"vj

TPTAL TM»ACT GENERATED HY SIMULATE*! HEM £**PLOYI'£NT, IMHUSTRY GROUP 82* 1978

1.PACTICULATFSIL9S) 267,761 2*Hro>iocAP90Msa"S» 96.222 T.SHLFll® OZOXXQFfLMR) 50,30* 6 . GASEOUS FLUORIOE(LBS) 8 S.MYntOGPH SULFIDE (LflSI 1 ,0 8 9 6.CO 2 ILPSI 61,530 7.AinFMypFSIL"S1 1,329 a.MO 2 (LRSI 19,119 M .D O ^ E S T K *UT£RfGAL5» 72 lO.cnoLTMG uaterigalsi 500 »l.PR0r£9S MATr®(GALSI 3,622 12.TOTAL MATEP INTAKE(GALS) 3,201 13.niSCHARr.E(r,aLSt 2,755 16.5 OAT OOOILOS) 510,603 JS.SUSFEunED SOLTOSIL»S» 5 2 ,3 6 3 16.SOLID WASTEICII VOS) 6,652 17.LANH AREA(SO eTI 18*938*209 10.FLOOR SPACEtSQ FT) 185*961 19.p a q *ING AREA(SO FTI 613,532 28.BUILDING SITE (SO FT) 229.687 21*MUMPER OF EMPLOYEES . 613

NtlWER flF «!T£'n»cn n-VJArTn‘'S f «09 M E M FOR IMPACT Gt'ltPATFO PY SJ“ULATE9 MEM EMPLOYMENT, IMOUSTRT G«»0UP 82* 1978

I.PARTICULATES IL^S) -C.32 2*HYDR0CAP'10MS(L9S) -0.27 T.S'tLF'l* 0I0TI0ECL9SI -0.22 6,GASEOUS FLU0RI0EILBS) 0.00 S.MVornr.F^ SULFTOEUPSI •0.25 f t .c n 2 (LPS) -0.21 7.AL0CMT0CS(LPS1 -0.22 8.MO 2 ILPSI -8.22 9.D0HFSTIC UATER(GALS) -0.07 13.COOLING MATERIGALS) -0.29 11.PROFESS HATFO(r.ALS) -3.16 12.TOTAL MATER INTAKE(GALS) -0.19 lS.PISfMAQSECGALS) -0.15 16.5 DAY PODILPSI -0.01 15.£USF?MrE0 SOLIDSILDS) -0.27 16.SOLID HASTEICU » O S ) ■ -0.26 17.LANO AREAISO FTI 2.68 IB.FLOOR SPACEISQ FTI 0*77 19.°ARICTMG AREA (SO FT) -0.13 20.BUILDING SITE ISO FTI 0.66 2i.NUHP£R OF EMPLOYEES 1.92 208 TABLE 35

TftTAL TMP*CT GEKERATFO NY SINULATFO NEW El'PLOY**FNT* INDUSTRY GROUP 0 3 * 1970

* i.oARTICULATFSILRS* 1 .Q T 2 .7 6 3 2 .MYOROCAPRONS(L9S1 7 9 ,6 7 6 3 . SULFUR oioyioS C LO S I 5 6 .2 6 5 6 .GASEOUS fLU0RI0FCL9SI 0 5.HVDF0GFN SIA.FTPEILBS1 16.912 6.CO 2 (L9S1 6 9 *1 7 6 T.ALDFMmO-SILDSI 1 .2 5 1 9.NO 2 tLRSl 20*563 9.00NrcTir WATeR(OALSI 310 1 0 .COOLING WAT*R(GALSI 3 .0 9 3 ll.FP'*Cr,:R W6KR(GAL*» 6.1.37 1 2 . TOTAL HATER INTAKE(GALS* 9 *6 3 0 lR.FTSCMACf.ccr.aL^I . 6 .3 1 9 16.5 OAY QOOILQSl 572*910 15.SUSFff*i0‘ 0 SOLIDS (L9SI 6 1 9 .5 6 9 16.SnLI0 HASTE(CU Y0SI 5 5 *6 7 6 17.LARI' AR^AISO *11 1 * 7 3 1 .6 1 2 1 6 .FLOOR SPACE(SQ FTI 2 9 9 *6 9 3 1 9 .PARKING AREA ISO FT* 8 2 6 *6 5 6 20.BUILDING SITE ISO FTI 195*260 21.NU**PFR OF EMPLOYEES 567

*IUM9f9 OF ETM;n*tn (I'tfl AT r°OM MEAN FOR IMPACT Gf MERATEO PY SIMULATED NFW EMPLOYMENT. INDUSTRY GROUP 03* 1970

1.®A*>TTCULAIES(L«S1 C .16 2 .HY PR OC ARSONS (L**S1 - 0 . 2 9 3.SULr»»J OIO»IO“(L9SI -6.20 6 .GASEOUS FLUORIDE(LBSI 0 .3 0 c.uvnenOFA SULFtOFILPSI 0 .0 6 6.GO 2 ILPSI - 0 . 2 1 7.AL1fNY0eS(L9SI • 0 . 2 3 6.NO 2 (L°S1 • 0 . 2 0 9.0OM FSTIC WATERIGALSI 2 .6 0 1 0 . COOLING WATERIGALSI 0 .1 6 ll.PPOFEKS WATERIGALSI 0 .0 1 1 2 . TOTAL WATER INTAKF(GALSI 0 .0 6 13.nisruARGfiGALSI 0 .9 5 16.5 OAY 900IL9S1 0 .0 3 1 5 .SUSCE90”0 SOLIOSILPSI * 0 .0 6 1 6 . SOLID WASTE(CU YDS! 0 .0 7 17.LANP APEAISQ FTI • 0 . 3 6 1 6 . FLOOR SPACE(SQ FTI 0 .0 6 19.PARKING AREA(SQ FTI 0 .6 5 20.BUILDING SITE (SQ FTI 0 .1 5 2 l.N II-» E R OF EMPLOYEES 1 .2 0

ro vOo 210

Ift O •» M IA tO U IK *4 #V n ‘f N U i M UtO'WO'0 a>«e p • #*•*•••• » ** » » p • • C g ftooaoaoo M <0 fti (*> tft M (PM I I 4 I « • • • « n « im a n ► a «< «4 ft K P 5

* K X ktf «b t ft in ► •n c aJ C O' 0 «J c 13 K a m a *» %4 •M W r >■ w in u I0 i/: u p iL h i 3 W m m ► lb tfi 0 c 13 K ■* la c e i- J H T. — 9 0 44 X ** D O r w r M l/ U in k; O" f t H V U in T , IP o 1l* IT 90 4» ^ !-• u e * « 44 S P h O' J I*1 h)M 3 9 G mi ~ *4 0 Urf ** MOW C J»a 4 O k l / 1 i a 3 h C w « e b^V1|bCt/14 4- a a a 4 0 . 0 ti cc « c < a X 4 (/) J J L" 3 Oa m x *» j j l* j e* x t/i lb c s - * 44 a. c x •• •* * X C Q m *j ► O f t o *• c C H O tf ► h UjNfU J 4 4 440 J bn a hn n«i«4ho c c in CMC JO h e* I* 0 1 * 0 JO mi k 0 a o o o O J 9 v > a c o o O O J a x e u SUMP in w 0 e 5 C(J!UHIAV)b » • « • • • • • ■ • • to UJ o r o c fg 4«cai m •4*4 M la a K z .f inrtf o*ir}ai a in444IA(Tff 0 3 3 4 r NM4 H ? * 0 4 « e (TVSNpJ 3ifl N P 3 * •••••••• !*• ill*! J a o n U N «4 W S * • m • • » » c tj n o o g u a o o < It 0 •r an 4 3 3 • i i • i a i • K K K 3 f l r w r ? • M *4 a in r ► r u

U* a s tt jr . ? . - £ C5 •* m ^ J *J V. Il ^ -IV J *- UJ r • m «i «• C — « J •* UUJ WMJ a -iu. u * in a* > U 4 40 ^ **c “ c c «• a — n . CKO o H M • o • V tH U j in h « ir » v. hu in r - C U . I H I 0 J *J * a w ^ U*ft •J .J H h ui 4 s C M I*. « c c x t J 4 b o in in •>■ n a -in . u w S S UJ bv» • 3 4 h O U I * * < " • Of ** •« M V. 3 U O < 0 u. v a W C 4 f r C I»*b jc a t i i* ir U’ III c r la. C H V t a U C HVtor 06 O « a c nr f. v ► a- it+ T m, t J ft* c ► . 1/ « 3 4 Z a c = Cl a ir I, t rc iirii zIU H UJ w u U U. O X UJ ^ bu li.l «. C b t r c J( U b D Of -JO c » cm m? r r e r r r 0 s :- > w c a H S 4 4 3 ^ JCB N X 0 « 9 *■*•3 C. m 2 « C b o m*j a X 4 O I. c m j • •••••• • • • • • • • H h w rur 9* f , IP *. 4 «4K K «4flj 19.PA9KING Zl.NUNPER APEAISO FT) PF EMPLOYEES * 1 . 1 -0.N5 3 ZO.8Ull.OING SITE ISO FT) - 0 *

i. 9 211

(O C <#«* « 3 n n Nr r K O n n N N ID* *!«»<* «4 fuifi^nn «4(tk Q • ••• •«»••• • » » • oooo4*««ao h) i I I in lA M N ► « 4 o n n N or ►*5 s

UJ & & m • * o a O or ft 0m _ l O in O h- VJ ff* ^ * — IL » — 3 e cr • Or ,o* m in o in uj * nr O ft l A u i n u z in c ti IT mm mm t* r v c b* pm X 3 h » J UJUJ H h i ? 3 ♦ - • «JUJ UJ « C J » ft bt * h U i l C J * «•0 V " N U Ifl * m u. w m s t- c* CAft a f t f t f t j « < o- O J VI (» «i« IW fW ■1 H O J o c in 0 1 - 0 _lO H c m O h Q J O h •j h ^ C O O C O J 3 ► ► ft o e o o O J 3 o XCUZUhtfk IT U «C 0 i e o sr U h w in u » 7 • • • • • • • • • • • • • • u< ft 4 C 0 Q fU J iT 0 O f t ■X.C as o *4 ftftft i0N(M -* •* in *4 i'(u«r(v« 0 • • *4 * m # ifi« D K N 0>

m UJ UJ o GU £ — V. & • t? £ - K V _l -i in - I x w k m j -/*» o — c — — ^ w it it. • i r •* ft Ifl _l III 19 — V. — X V VJ •* u C f t if . <• ■ a e - c — C a x o o * c *■ c • c - o x o T _J l| HkB" - x u in . j c J h ft • i f x - u in C U. in hi t» -i w a • O b v b i r J J v h j a x u< «* o e m t u* *- -J u h U r c e a i x s _i« *- o in in bi uj *♦ h 3 - * 4 h B in in hi O V » T — cr ► C ir .- 3 f t ■ — 1> m tn 9 tu cm m it «t n i/t 9 IUCI4 4 C Z h • i " o DU. O •l - j c st u- C C U' b' U Qi h m u CO u c 3 L b . > - ir O' C O' o (. f f C X , |/> IV j m 9 w i ft I? ft h f t m T m S. M 3 C J v u * U M III f t * : c : ITU. X I I xi X I I u ul l n U U L. C K C J >* U U b* b L U b e k o J C C r c b tn z J l t l » H D « m 3 c C h . J C ft x g m m ft vi a * C*. C l I J I a u-1 ■*l O k l b ' J C . k «3 • ••*■• m « • t » • • • . •. n in f* w •* xj I f K O’ H x i in x O'

««U Vl ft in ?l.ftUHP£* OF EMPLOYEES - 0 . 7 6 y

z 3 X TABLE 38

TOTAL TMPACT GENERATED AT SIMULATED NEW EMPLOYMENT, INDUSTRY GROUP 0 6 * 1970

1 . rarticulatesilrsi 9 0 2 , H 3 2.NY0RPCARPnMS(L?S> 5 7 ,7 0 1 T.SULFUR RIOYinEILRSt 5 1 , 3 - 2 A.GASEOUS FLUORIOEILBSI 0 S.HYDROGEN SULFtOFILPSl 23.1.56 6.CO 2 ILPSI 3 5 .9 0 0 7.Al«jrHYnrS(LOSI 1,176 8.MQ 2 (LRSt 1 0 ,9 5 6 9.no-fr.TiG watepigalsi 97 1 0 .COOLING WATERIGALSI 3 ,5 6 2 11.FOOCFSS MATE®(GALSI 1 0 .5 2 6 1 2 . TOTAL WATER INTAKE(GALSI 1 3 ,6 3 2 1 3 .niGCMARFE(GALSI 9tB3*» 1 6 .5 DAY R O D ILIS l 9 5 1 .0 2 7 15.SUSFrnn~n SOLTOSILRSI 7 2 2 ,6 0 6 16.SOLID WASTEICU YOS1 71,991 1 7 . LAMP APEAISQ FTI 1 .0 1 0 ,7 0 1 1 0 . FLOOR SPACE(SQ FTI 3 6 1 ,7 7 1 19.PARKING AREA(SO FTI 5 1 5 ,6 6 6 20.BUILDING SITE (SO FTI 2 9 9 ,0 6 2 21 .MtlMRPR OF EMPLOYEES 613

NUMBER OF STANQAFI DEVT AT ('"IS FPQN MEAN FOR IMPACT GfNEPATEO AT SIMULATED REM FWFLOYNENT, INDUSTRY GROUP 06, 1970

l.PARYTGirLATrSILRSI C.13 E.HYnP.OCAFfiPMSILRSt • 0 . 3 1 3 . SULFUR 9 I 0 v1!Jc (L nSI *0 .2 2 %.GASEOUS FLUORIDE(LRS1 0.00 5«HYOcOGEM SULFIOEILRSI 0.19 6.CO 2 ILRSI • 0.22 7.ALPf H»0r SCLPSI * 0 .2 6 A.MO 2 ILPSI • 0.22 9 .DOMESTIC W4TE»tGlLSI 0.23 lO.COOlXNG WATERIGALSI 0 .2 6 1 1 .PROCESS WAUR ISBLSI 0.21. 1 2 . TOTAL WATfP INTAKE (GALSI 0 .2 5 ll.PISrHApr.EIGALS) 0.25 It .5 OAT OOOIL9S) 0 .2 6 15.SUSFEM0*0 SOLIOSCLAS* 0 .2 9 1 6 . SOLID WASTE(CU YOS1 0.10 1 7 . L * NO APEACSfl FTI *0.35 lft.FLOOP SPACE(SO FTI 0 .5 7 19.PAPK1NG AREA(SO FTI 0.01 20.RUILOING SITE (SQ FTI 1.02 ?1.MUMPER CF EMPLOYEES 1 .9 2 TABLE 39

T'lTAL IM BiCT GENERATEO STtRJlATef) NEW E^RLOYMFNT, INDUSTRY GROUP 0 7 . 19TB

I.PARTICULATES ILR*1! 135.575 Z.HTOROClPnONSILISI 58.949 3 .sulfur oioyiofilisi 65.320 6.GASEOUS FLUORIOEILRSI B 5.WVDB0GEW S U L F in flL ° S I 739 6.CO 2 ILnSl 37*392 7.ALnrH»nFSaPSl l.CBT 8.MO 2 ILNSI 17*621 9.no*us»ic watfrigalsi ?63 10.CCOLIHG WATERIGALSI 372 lI.P«0rc3S WATERIGALSI 1*164 1 2 . TOTAL WATER INTAKEIGALSI 995 U.niSCHAP^ECPaLSl 622 16.5 OAT eODILNSI 6R.614 1 5 . SUSPENDED StJLIOSILBSl 4 9 .5 4 5 1 6 . SOLID WASTEICU tn S I 3 .3 6 2 1 7 .LAND AREA ISO FTI 1 *2 5 1 *1 7 9 IB.FLOOR SPACEISQ FTI 263*969 19.PARKTNG ARE*ISO FTI 226*954 20.BUILDING SITE ISO FTI 183*097 2 1 . MUMPER OF EMPLOYEES . 512

NUMBER OF STAWP»cn D"wlATinNS F«ON MEAN FOR IMPACT GENERATED GY STfJlA TFN NEW EMPLOYMENT* INOOSTRT GROUP 0 7 * 1970

l.BARTI^ULATrr.lLnSl - 3 . 6 1 2.NY0ROCAROOMSIL9C1 -C .3 1 3 . SULFUR n iO V IO E ILG S I - 0 . 2 3 6 .GASEOUS FLUORINEILBSI 0 .3 0 5.MT0E0SEII SULFIOEIL«SI -0.25 6.CO 2 ILPSI • 0 . 2 2 7.ALGEMT0ESIL°SI • 0 . 2 6 s .n o 2 a n s i - 0 . 2 3 9.P0**r STIC WATEFIGALSI 2 .2 3 to.COOLING WATERIGALSI • 0 . 3 0 ll.PBOr^SS WATERIGALSI •0.29 1 2 . TOTAL WATER INTAKEIGALSI - 0 . 2 5 1 3 .niSCWAPGE|GALS» - 0 . 2 5 1 4 .5 o a t n o o a n s i - 0 . 2 9 15*SU Sr ENNE0 S O LIO SIL"SI -0.27 16.SOLIO WASTEICU YDSI . - 0 . 2 7 17.LA un APEAISO FTI • 0 . 5 3 1 8 . FLOOR SPACFISQ FTI • 0 . 2 3 19.PA9KING AREA ISO FTI - 0 . 4 0 * 2Q.BUIL0ING SITE ISO FTI 0 .0 5 21.NUBPER OF EMPLOYEES 0 .3 6 214

n. r emMa>nB^ (Pff i#m s K dhnoiOiUNiA £ M BN OilNNn *» n • r• . r • f u » i• r M » N • B• fi*J a ■OO •« O O•• t t • O • B * O • Q • in t r •< • * w k m tn n» I 1 * 1 * 1 * — WM H •**» n n n « i m o9

s u 9 VI-I o► VI•J O'Cl 4T © ^ o VI 9 VI e 0% •» *■ ft 9 - 2 - t ► VI Ul VI *4 or JV O te O 2 S S ^ o *• V) 14* 4 « te ft V) 3 V> tel < ■ ► li VI V) c a C te jJ C © 13 I - — J N ** z ~ 9 c* 9 .J te •* c & • or O H M u te v i — V o' h i / ) o in u r 1A © ii* r C £ O iii »— *»»- X 9 te ft oJUUM li I- O J b l U H O ^ 4 b • te U VI o «« u,«•»- o tn e it viM X h>C M rn oCT U VI o VIa 9 teO V)4 o. o v o cj «o « o o o o o J 9 V ► «c co o a ^ a a z v o s o»- in v> u. o a. X c u 7 U K I M f l b. It r » • • » • • • • • • • • i < m * * © O M 4 4 S O ft' 4«r c o M * « « a o u •» telz c n•4^0«rr(unnu>o NOlAVU'tf'N V'K ini\| o*in«4M MOrtHNNON' d n a d io o i 3co ^ r j o * < ^ cr k cr m tf\ u * I I •• ■•••• » » » • * * • * * C n uo oa oaoooi s ft. 0« «rt <# v4«4N «4tft til* •••• mm m«r . %n «4 *) «0 i K r o D 9C V! « £ * o. VI■ M ccte Itie luc 0 UJX Ul r 19 VI o -If r ~ S’ «- VI u -if p - J? - VI V) -J J VI te tei IT -I JV) J . Ill «■■ 0>te te tel ©te* ft y © 4 VS ** V -ib 4 V i «• te a C » C *» o te C O r o* e te O O x o » © te* U VI u c l«‘te«* 0 -Viw ft IT m i OkVI tei IV J J — ft ©ft VI bl O J J a Vs** ^ *r * © 04 r V*te J V te irm c * x ^ 5j C VI VI tei tei li1> 9 teCIOSi_ UJ bi © © *- 9 4 te* or C VI te»» - or te» VI 3 tei © 4 4 k 9 te» V) XtelO* * ft C St litCi © u l u O I ©2 b C e »*»te C 3 _ H VI a e q e C Ui C v* V’tt © O C cot1.► te V? m x 4 2 Or o t- te te V «l z 4 2 tt ^ 9 0 7 Cl l«l a u te- tel c sc X© b X C H te' ► te te te»te L u u C 9 C. c. te te h * b ecu C W ft o je r r o v* VI X O » JC C 9 o © VI 7 fr X 4SV.J c o M 9 « m 9 S te o n : 4 4 2 ft VI T * c t © V*- J f t Z VI* «• c•f t © v i piOZ V. tA N 9* te telA ftff «ih in k a •« 4«4v4te N V. teteteteviN teD 0* III » 7 TABLE 41

TOTAL T ^ A C T r,^Hfo*frn 9V SIWl/LAfn N£W E M°L(1Y»*PHT» TNIUR*®* GROUP 09* 1970

I,r*7TIClJL*Ir< llnS) 2 *? 1 2 .7 ? 5 »,HVPrf*C AP9f)*lS (L ® *) 2*361.367 i .s u l f u r nio*iosn.nsi 1 8 .6 9 3 6.GASEOUS FUJCClor ltfVS| 3 5.Hvneo5EN SULFIDE ILBSI 1.719 6.CO 2 (L«S) 27.139 7.ALirwvnESCL9s> 793 8.90 2 (L«*S) 16.096 9.0'"*rSTIC MAT®0(GALS1 255 10.COOLING WATEPIGALE) 656 11.PR0CF5S WATERfCALS) 1.2C5 12.total mate® intake( g a l s ) 1.756 li.uiRCMAorciPALSi 1.286 16.5 OAT noOCLTS) 79,770 t5.SU9P£Hn«-0 5(11 JOS Itnsi 55.389 16.SOLID NASTEICU VOS) 6*650 17,l a m i a«i*»fso *ti S.987.156 18.FLOOR SPACEtSO FT) 222.870 19.PARKING AREA(SO FT) 353*635 * 20.QUILOING STTE (SO FT) 173*202 21.NU^E® OF EMPLOYEES 665

STAWJARU 0eViaiI?*l5 F®ON HeAM FOP IMPACT G*;H£PAfEn 9Y SIMULATED MEM EMPLOYMENT* x n o u s t r t group » l.®«»Tir.(IL*Tf5Cf»5l 1.29 2.HvnFOG4POONSILnS) 1.81 3.SULFUR ninv|PFfL9S) •0.26 6.GASEOUS FLUORIOFtLnS) o.ao 5.Hvi)*or.FN sulfiomlosi - 0 . 2 6 6.CO 2 IL9S) -0.23 7.»LnrHY0fS«L"SI -0.26 8.HO 2 (LPSI -0.26 9.np**l5TT0 WATEPIGALS) 2.13 10.COOLING NATER(GALS) •0.25 U .P B tr F S S WATERtGALS) • 0 . 2 9 1 2 . TOTAL MATER INTAKE(GALS) -0.25 l?.niSCu4or.F(r.ALS) -0.26 16,5 HAT 90DIL9S) •0.27 1 3 . SUSPENDED SOLTOE(1 9 5 ) -0.26 16.SOLIO MASTEtCU VOS) -0.25 17.LAND A®EA(SQ FT) 0.93 18.FLOOR SPACE(SO FT) -0.56 19.PARKING AREA (SO FT1 - 0 . 2 2 20.BUIL01NG S ITE (SQ FT) •0.03 21.NUNPER OF EMPLOYEES -0.71 215 TABLE 42

TOTAL T*«BCT GENERATED RV SINULATFO NEW EHPLOTHENT, INDUSTRY GROUP 10, 1970

l.PARTICULATESIL9S1 165. PAT 2.Hvno0CAP90NS(LP51 60,695 3..EIILFIK DIOiriOEtLRSI 63,872 N,GASEOUS FLUORIDE(LflSI 0 R.HTRCOOFV RIILrinPILPRI 991 6 . CO ? IL " S I 3 1 ,3 1 0 7.»LnEMY0eSIL95» 1.H7 O.SO 7 (LPSI 15,761 9.POH*-STK MATFRIG»L5| 56 1G.COOLING MATERtGALSI 1,066 ll.^onr^SS HAT?s>tOALSI 3,593 12.TOTAL HATER INTAKEIGALSI 2,500 t3.usrp»R';Eir«L5i i ,« to 16.5 DAT QOOTL9SI 165,955 15.SUSPEND'D SOLinSTLRSI 120,123 16.SOLID HASTFICU TOSt 6,236 17.LAND A°‘AISO FTI 1,799,750 1 9 . FLOOR SPACEtSO F T I 3 0 5 ,1 1 9 19.PARKTNG APEAISQ FTI 272,926 20.BUILDING SITE ISO FTI 236,036 7 1 . SUPPER OF EMPLOYEES 513

NUS9ER OF STAMPAsn nfyTATintlS FPQH HEAN FOR INPACT GENERATED OT CI**ULATrn NeH EMPLOTNCNT, INOUSTRT G°OUP 10, 197C

l.PA9TICtlLAILStL,»SI -C .39 2.MTOROCA*nONSIL9Sl - 0 . 3 9 3.SULFUP nT0»T0stl9SI •C .26 6 . GASEOUS F IM O R in rtL F S I 0 .0 9 S.NYHPncrs SULFIDFtLBSI - 0 . 2 5 6 .CO 2 ILPS) • 0 . 2 2 7.ALn«-HVOeS(LPS» • 0 .2 ? A.NO 2 ILBRI • 0 . 2 5 9.PO-F5TIC U»TE»tr.AL9l • 0 . 2 9 1 0 .COOLING WAT-RtGALSI - 0 . 1 9 1 1 .PROFESS MATFRtGALSI ' - 0 . 1 5 1 2 .TOTAL HATER INTAKE(GALS1 - 0 . 2 2 H.nisrHARGEtGALSI - 0 . 2 0 1 6 .5 OAT 9 0 0 IL 9 S I - 0 . 2 2 lS.SUSrESDRn SOLinstLRSI -0.71 16.S0LI0 HASTFtCU TDSI - 0 . 2 6 17.LASP AREAISD FTI •0.36 1 8 . FLOOR SPACEtSO FTI 0 ,1 1 19.PARKTSG AREA(SO FTI • 0 . 3 3 20.BUILDING SITE (SO FTI 0 .6 9 21.NUPRER OF ENPLOTEES 0 .3 6 217

tr> o f u k 0> i p n i t w M nn«4f44*mcm m Bt4 #4)4 BM h o «i temnancop « DIM MM M N M H n o O• O•••«••••• O Q Q O a o d O *0

o 3 K 9 S a 4 • 5 ft. Ah 3 f t ► • 0 O - 1 O ftr » 4 Ah m 4 ^ o t o o s? t o C ► f f A * 4 * 0m u» E a • • * Ah U . ► J 10 U I f t * •j t o U I . 10 4» o r 4 * 4 * J Z O ^ o PA mm J 2 P b O ► to lu 4« ► tl t o » UI U» 4 4 ► Ik to 10 c r c i s i * 00 (u c r o t 9 tA v J M m 2 A 3 0 mj 14 m 7 a D O r - or o H f t 0 40 U I m m o r ft M f t U f t bl 3 t o © u i t r mm mm t o o UI P A A H H Z 3 b - ft -J l u l u M 3 b f t J U U N fl J A A 4 b| W 1 - U to C * i« h » * I U « * b O f t i C bftftYM O CO4 u 10 *» tf (U C i 4 0 4 CL IS a c 4 C < a o X 4 f t J J C 2 ( T 3 f t z 3 co«i JCYOSMZ U i 14 r 3*- *•* H a. CO O f t ’ o 14 O h j ^ o o r c ► b U I M M J 4 « HC IbN CM «J4 4 M O -I o 0 ( 0 C 1 C JO 1-4 IO O ^ C J C M - i ► 4 0 0 0 0 o » j 3 ► 40 Q O O O J3 a XC U ZU blA toil Cb tf co 2 U h m m l t 0 t • • • • •«»•«• m hJ ( u j t f i r o o N Q O M l O K O *4 4 *4 «4«4 fU U i *» f t i* UI 4 z fte ON 4 -ft bJ «» *4ia H c C M M f t N M f W f t r fW JT 3? Cl rv

► ft

o U l m 4 or u. z Ui A * p» . ft o - r r ~ JT * 1 0 to *» to n ft«l J to _l b U I lO. ^40 iii u a» cr mp 4 . j 44 t l U I s m> 4 *J • h. lu ■J tr. «j Ui 0 4 f t A ► ip *JUJ C* € to — >• c C — c MftA Ob OO «* o Ob- c o a Jb M A fr A ft MU t o - J c b-H n a M b t/) J M « c U ft 111 O *i **& ru. ir j -i •* a f t m j r t - b » 4 r *c 4 r H J C M- L' 4o c « r •1 ba P JftH C ftftU ibJ j V) IO 111 IU 4 b O f t « * I 4 » mm o r ci^** w or ► 4 M t r 3 Ul 0 4 4 U. i* tr 2 Ui C4«(l c j r z n * c c l i * | . C b C? li' U L* *jj br U 3 kJ C M ft Q O C ft t r C ui C HV)b c o o t 5 ‘ C ► b ft « X 4 z r r Clft 1? ► *a tA 4 2M 7(1 i r c z i / b < ; b t i - b r res IAU 3 111 H IaI b k b b U C U UQ u c a Cub. U C ^ L O V C. o j e t r O f t f t 7 o z j c r a e tr t0 3 O' Z 4 3 > JC ftM r 4 4 3 s> u c or + * 3 * 4 3 ft. tO Z 4 O U C ft w &Z cfi e (O •« C ft * • • • • • • * • • ■ • • * « 4 0 I M > 9 v 4 C I f K f t J nm K IP P O' • . «4 W* JN ip it. o cff r ? TABLE 44

TOTAL I*«>erT G£NE®ATEO nv SI**ULATE0 NEW EHPLOVHENT, IiniiSTQy GROUP 12. 147*

l.PASTTfULATESCLiSI 1.046,<.45 Z.HYOPOCARRnNSILPFI 3 9 .6 8 2 3 . s u l f u r ninriO 'tinst 4 4 ,4 5 6 6 .GASEOUS FLU49IQE(LOSI 3 5 .MYf»Pnr.F*t SUL* IOE ILPSt 1 .1 3 3 6.CO 2 ILPS1 27.835 7.ALncMYn*S(LnS1 7 1 4 4 . NO 2 (L e S I 1 5 .6 5 6 R.OOMFSTir WATERtr.ALSI 64 lO.rCOLIMG MATroiCdLSt 3 ,2 1 0 ti.p®orxss MATr.pffiAtsi 723 1 2 .TOTAL HATER INTAKE(GALS) 3 .4 6 1 13.9ISrMA=G£IGALSl 5 4 7 16.5 OAY 9001L4SI 5 9 ,3 6 0 is.susr'-NnEn solidsclpsi 61.527 16.SOLID HASTEICU YOSI 5 . 3 0 3 1 7 .L A N P AREA (S ') F T | 1 . 3 1 0 . 1 4 2 i a . f l o o r s p a c e i s q f t » 2 2 5 * 3 6 1 * 1 4 .PARKING AREA ISO FIT 2 6 6 ,6 1 4 20.BUILDING SITE ISO Fit 1 9 6 .7 3 0 2 1 . MUMPER OF EMPLOYEES 4 3 5

o f sm ir4r? o^viationf from m e a n f o r i m p a c t lit m e r i t e d n» sim jlatfd mfw e m p l o y m e n t * i n o u s t r y g »o u p 1 2 * i n t o

1 .P A R T IC U L A Tr S ILBSI 0.20 ?.HY0R0CAc90*iS(LBS) -0.31 T.SUL*-!'! ni(WOF.ILnSI -0.2W 6.GAS-0US FLUDRIDEILPSt 0.00 5.HYIJC0GFV 5ULFT0EILPSI -C.2S 6.CO 2 ILPSt -0.23 7 ..ALnEHVnrSILn SI -0.27 8.NO 2 (LBS1 -0.25 9 . d o m e s t ic hatfrigalsi -0.61 19.COOLING WATERIGALS1 0.18 1 1 .PROCESS HATC0 (GALS» -0.T1 12.TOTAL HATER 1NTAKFIGALSI -0.16 lT.OIPCMAer.EiGALSt •0*24 16.5 DAY ROD(L9S1 -0.29 lE.SUPPENO-D SOLIDSILPSt -0.27 16.S0LT0 HASTEICU YOSI • -0.26 17.LAND AREA(SO FTI -a. 51 18.FLOOR SPACEISQ FTI -0.56 1 4 .PARKING AREA(SO FTI -0.37 20.BUILDING SITE ISO FTI 0.17 21.NUNFER OF EMPLOTEES -0.87 219

& I O N tA J e s M 4 - t t r <£ ^ — M n N I M A « 4 9 £ ftOIUN M*M IMM4 M f N f lAoPn ft • t ■ • # « * « . • » * • 9 » • e 0 a o a o o a e e * *0 M l 1 • t I • I I I » M * K

«

a. 9 n in o v o in a IA c — It & © ► in iu Ift r u* m i IAU. tA ~ or _ i v O M O m • • j y a t» »- in lu ► b W V hi > i t in a - a © a s - i — J N • ■ X » s c c* — t r a n m S Ift (M • or o r * - tA U 1/1 r in c U. — — M tA C u T 9 M o _J U U M X © J U l u r ^ , i u u m u tn O J*»* WHO s b. in in a • - o Ift 4 U. (A IA7 k f i t f \ m u Q< e- « o 4 L D u cu a «a o ^ o . • V J J L ' J f f V Ift X «ttA j j e x C" X IA 0 3 — — X *4 L) 3 — — O C *4 .4 f O Or O O C ► O t t ► 15 U M N -J «* « M O _J li b 'N M 4 M O o c in CMC J O H o v% C ft- o J O f « o o o o O J O > ► « o e c o o j a x e Li r c m ift IA U. © c x © o a f t i h If t (A I t • • • • • • • • • • • • A i # e e o « M ^ t p 0 O c e i M 4 « o o t n II’ •4 < * a lu a « j r < H L* i rm ift Ktf ut * • » o U o Ci □ CO U O P g J l O J f l I II ! • I t I I .4 c * g o *4 a Ift

C u*

X bJ C - i f r - e m © 0 -IT Ui~ ? ► K J JIA J »- Uf u tn •JtA «J c < * r - U UI — tr — „ tr _ b e «t (A M ► b Ift -J u IA«~ c c *- C* *»* e « O K c o z t — c ^ C h r «jb *N M o - H h u in j c J u- — *»fl ^ y.Hb. Ob IT ih cr •* CL — Q b Ift I f t •J J H J6 N III C C7 • w m j a N I. m e c * 3-1 1 V. tA I UI > 3 _» 4 I- tr ia (A O tA *- x « cr *- o in — 7 4 *# ** (A o > 4 H tn X o.- o * r t li C* «• U< O' I j r ? t j e e u ui £ *_ IM& H 1/ C' Cso e S k t HIT o c a O frO *- tr z * ? or I ' f r O k *-tn m t m MSC t IA It. UI N UI — CCS 0 b V u h k ft If u c t c b a *• b li U U L1 o u o If JPO 9 C e. r or a. ic j r c XC 0 0 2 « X ► o o z m <* 3 * x ►

UI r x XD 2 2 0

a POtf>KO «1A9 fr N D N4S *t fr •4 |A O o MaHonM«wND« * O * N N fr n p s a ft ft • * • » » c a o e « 4 n #4 O fr 19nvN I I I • • I M 9 « 0 0** ► ft* fr « *

D s

U a 0» K 3 V) ► •i o •J O W O' •• 0b •J « e VI o fr fr VI (9 fr r ^ *■ * Ift. X cc m *p — It ► •i V* w V) m u ml Vital IA ft* cr A «* •J V OHO W 3 OHO *- in iaj « « Mb VI 3 Vi Ibi « m MIV) IT e c e m • 0 W a. ■ ft- m OOo a C -J 3 L. x o u z U H»ip V) fr CD cr 2 19 u up* ia v>y>0 X. • • • • # • • • • ■ • • • # • * » • » » UJ O N o c e o N 3 *0« ON# 40 AO \C> ft* *4ft* ft*ft*fr Ui •4 ft* N 9 ft* u» m to fr Mn#Not«oa^inie4 u* ft* ft) IAIM Ota «CH# g 2 IAN MOU\r NNNo o N«4#(DlVa«Ki4NN • • • u 9 ia f r * ^ j fr c *ft 3“ li • ft ft • • • « C o o Ou a o o o d Q n y> .» NO • 1 • I ft 1 • • f> j Pt^tt fr 4 IA «# O ? « M a VI ► e ofr

fa* & HI ftft r id -ic V r — V) ? 1? r - JT - fr V) w w «r w H It u VW JV J H o f t T H ftV • i •» It U 0b cr w « W •* fr w V Jb? ir N V. ftft *- V VI wUi 0 4 Vft L. c*- o ftft c p» O H o o 2 ff •* 9 •* c ► o h a 9 J lb Mft 0' IA ftft u. IA J r J u* ftft b ft^H fr v) f r • D i l l A Ui 0 •i •1 •* a •ft 9 fr (AbJff J J ftft I I H J S fr ;•• c c « c HV ►* J a H b1 4 O c 4 •J ui n d J * p» C IA VI Ui ui m u X 5 •j 4 HO HHbJ « H O H ^ 3 « •ft •ft or M C Vf •* X 4ft —a fr « H V 2 ul c < < it > NM IA 1 1 ) 0 4 4 r J P X !>•O L* 4*4 ||l o* ii c z b c C III b f r 3 b. C fr IAA C O’ o c 5 Ui C H M 4 C 0 Id u v o > f r 1* < Z N T 0 i* rr c V H H4 Z4 Z H O C 2 IA b 2 Uf ftft lu c M 3 c 2 V. fr* 2 U* H fr W ft Ui U U 1* u c 3 e u H U o fr L UL U 9 9 C J C C X c V V* 2 a s 0 •j c 9 r r r w r v 4pta«io o m 2 « N 3 c. N 3 ► •J G Cl* H O 4 4 fr H X 4 © a c V w fr Z » a IA2 «4 C l C VI Wfr • • • • ft • ft • • m • « •• 4 • • • • • « H r Vita cr *4 H) iA P- cr *4 H IANOftA IA fr cr •ft H H •4 N V) 21.NUMPE* OF EMPLOYEES -0.25

It o w r■ TABLE 47

*OTAL IMPACT GENERATED 8V SINULATEO NEW E-PLOTHFNT, INDUSTRY GROUP 15» 1978

l.PA»TTriJLATBStLnSI 57,166 f.MYDROCAFOOUStLREI 38,917 * . SULFUR OT0FJDSM.OSI 3 3 ,5 5 6 6.GASEOUS FLUORIOEtLRSI 0 5.M*OcnKFN SULFin£tL9S» 6 2 9 6.CO 2 fiasi 26,096 7.AL'>FMVrBSIL*»SI 5 8 0 S.HO 2 tLBSl 11.613 O.n.vu-CTTO WATERIGALSI 1 3 10. COOL I Nr. WlTEOfGiLS) 126 H.TRO rrsS UATF.Ptr.ALSI 3 8 1 12.TOTAL HATFR INTAKEIGALSI 626 l ’ .DISrmar.EtCALSl 2 9 7 16.5 OAT 900tL9St 33.397 15.SUSrFNOBn SntlOSILOSI 2 2 .6 8 5 16.S0L10 HASTEICU TOSI 2,568 1F.LA N O AREA ISO PT I 6 6 6 .1 2 5 16.FLOOR SPACEtSO FTI 128.160 19.PAOFIU0 AREA(SO FTI 1 0 8 ,1 2 5 29.BUILDING SITE ISO FTI 36,972 21.NUHPER OF £NPLO»EES 6 1 3

NUN9ER OF SIANpArn OBVIATIONS FPflN MEAN FOR INPACT F.FNERATED 07 SIMULATE! NFW EMPLOYMENT, INOUSTRT GROUP 1! • 1978

1.FA9T1CULATFSIL0S1 -C .66 Z.HYnPOCACijONStLOSI -0.31 3.SULFUR OIOFIOEILOSI -C.27 6.GASEOUS FLIlQRIDEtLASl 0.90 s . h y o f o g f u sulfioeilpsi -0.26 6.CO 2 tLPSI -0.23 7.ALOfn y o f s ILOSI •0.28 A.NO 2 tLPSI -0.29 ®.00*FSTIC WATEPIGALS1 •0.78 10.COOLING WATSPtGALSI •8.36 11.PROCESS WATEMGALSI -0,33 If.TOTAL WATER INTAKEIGALSI • 0.31 1.S.OTSFHARCEIGALSI •0.29 16.5 OAT BOOtLSSl •0.30 15.SIISFENDF0 S0LI9StL«SI -0.29 16.SOLID WASTEtCU YOSI •0.27 17.LANO AP*A ISO FTI -0.71 IB.FLOOR SPACEtSO FTI -1.31 19.PAQKTNG AREA(SO FTI -0.56 20.8UIL01NG SITE ISO FTI -1.17 21.NUMBER CF EMPLOYEES •1.21 2 2 2

a. WDN* W * • « *» 3 peNCiA««ao4 « a K a n « ^ i A O MON

* s h * a m l . o « m ^b o iA e O i a « lu 1. cr a %/i Ui V)i» ► • j IA hi IA — Ui V•J V OH> O •IK BHO ► IA Ul 4 4 * CA UI «« FftklO IA C c c H- m m l* OSD H c o ► 0' Ci fu IM•J 4 4 H O J ca rv u> MM J 4 4 H O J o o IA c o JON c ui OUOUOM ► h 4 O © o C O J9 - j ►4 O O c c O J S UXOhll\(ftUlC 0 X 12 u z u H IA vi u» 4 *9 4 (0 0 O o M < >(i«oN«d(ia CO V* «4 n n m UI

Ui z I* m •O N IT *0 4 h N i r •ll ^ O' *4 jritN^nKiAV c IT IA cr n 4 ftjN N U> n f'-«CNO*4N

IU

«- m 0B 4b T ft* u ** IP iA § -IP £ - ? - Vi h V, _J •4 w oJ H UJ u «A J J V> *j k UJ ** 4 m i - ILUJ o r 4 oi U UJ > 4 IA •i Ui C 4 IA >- V IA mi V* id 4 IA 0 C o c « OHO o 2T D *»C ■* 4: Oh O o r miu* H mm tv m m IT H U IA C jb .H • O w tr HU CAw Hi m m c u IA u* tr •J•J w a w du ia ui rr •I mJ “ a it H IT >■u 4 o 4 r 1/tN J H u; 4 0 0 4 z L«K «J4 o IT' W UJ U. H 9 J«H tr tr ia uj UJ 5 ^ » 4 ** ** c r 4 H* C IA ** z 4 w «#or b* O IA 4 H CA z IU 0 4 4 u. 4 in IA 3 UJ0 4 4 u C c Z |M c c U li» o li JCZ li* t c b IU c c 9 UJ QHVI o a n o £ UJo M ir V c o o O' L ft o HK tr 4 z 4 r O’ Cft'C > H IA4 Z 4 Z N* “ o X V it z UJ Ui c h SQ Z V li1Z M H UJ H u U. w u Co o z e Ci Hk li UHU Ul u o u c. u u ca z tr *J c O 7 c IA V* ? or s 4 Q* JC CSC IA z cr 4 9 > •JC cr H4 9 4 m 9 c 4 9 > J c

c or Ui cr * 9 Z 223

& m a m n a< e M n o a 2 ci in *» m n « C naNNnnfiHOfC cr « «*4 * CM *• «4 10 tr *•*••*•••# * * * * » » » o uaOODDOOMtC P> «4

0 so IA VI o Or . 4* 13 IA 40 H a IA 40 H & ft *• Ik ft 4 Ik V) UJ IA*» IA UJ UI — • i J If OHO O J w 0 4 - 0 IA Uj « m . ► Ik IA H V b* « «■ ► Ik V) 31 C O U N ia ft O C u UI ►* 4 - 7 -1 **• • 7 < * > o •J T ~ s c *>ct OHinUMUl c tr Q u lA UIAU 1 V* o u* r c w o u< r 7 • • N S 3 h * J WUIH *- 3 3 h v j b lU H UI C HOW O J * w * Ui ~ C U. IA tA » H C tA ^ • c U.ITIA > > o I/I « u (pc « o « a o H u e cj 4 O 4 a. u •1 (A (9 > C X IA Z 3 4(AjJLkirVUl2 7 & o to - «* x U o 2 ** •* Z *4 o C « J> - GOTO 7 o C H J > o o e o r> l.(\j n p J < « h q j ». o •i««m HO J ia LPJM Cto D h Q JG H O o IA Oh P •JOM ► > 4 0 0 0 0 o j d ►4 0 0 o o Q J O c* x c u z u x A V i u a a X COZ UHIA IA Ik O • ••■ « ••••» r • • • * • • • • • • N^iflroN^OCO as w IU i i r r OM ^ O o -a 4 4 4 UJ «4«4 v4«f HM 7 UJ a toUS 3 l^ iO D p» h h d n i A INMNK^NNtPIP c IA 4 a n o i D M • ••#••**•• u * a j k •j r> ft IT. ** » • • c anooooanoo * IU P j 4 4 I I I I I I I » I I IA 7 ( y jH N H M«4 ' o« a

UI X T r. - i 55 a IP Min S' I? - u in _ -J ♦- U «J m » % T J h Uj a *» - u. *» ft HP m _i ** Ik UJ w •J u U 4 tn — (r j i u C 4 IA ^ H *• o oCI>0 e - © O H c O c If. V H l i V J (t H*< a v ia H b (T j ll* N * e u ia U' O' _ _ *> O U IA tua* j j “ a KU 4 O 0 4 V H J C H l|i 4 0 0 4 1 M — ft b > O J 4 H G IA IA U UJ * D «. O' *- r ia *- > 4 * » ir « M IA X U C 4 4 U. > H V* Sluc«1 III c ? I*' o c if u' JC 7 « O C It. lit C m tr o o o o 5 J D Hlrto- a a i> c I* c U IH Cl > ► |T 4 a e > KK«Z«Z 7 4 ZD c 3 c 7 IT Ci 1 111 ** NOCI IT !♦ T ll* M Ui b uli H u U UJ b« U U ( . e r a o wutocv IC C IA 7 » fir JCC t C 1 IA 3 IT r j c r C U 4 D > J C O' H d * * r> 3 ► ^ CO.C ^ J t fi IA & 4 c c © U lJ (L Z W x * • • • • • • • • • • • 17 ••■«•»••■> i- Mr'ioKO'^nioro' JAIAN 9 ** A i p k p m J «4*4 *4 *4 fU in OF 21.NtlHnep EMPLOYEES -1.13

«r r 3 JE TABLE 50 aap

IPTAL I-P A C T GENERATED NT SIMULATED NEN FMPLOYNEMT, INDUSTRY GROUP 1 9 * 1970

l.PAPYTCULATFSTLOS1 1 1 1 *9 3 2 2.MY0C0CAPR0NSILPS1 71*397 3 . SULFUR 9IQ Y T 0 E IL R 5I 5 6 *2 9 5 6.GASEOUS FLUORIDEILDSt 8 5 . HYDROGEN SULFinETLPSI 626 6.CO 2 TLPSI 92*766 T.ALnFMVOe-SILRSl 1*152 9.NO 2 (L»SI 18*969 9.00»trSTIC HAT£p(GALSI 20 10.COOLING WATED(GALSI 279 lt,p*>orsss hatepigal«i 795 1 2 . TOTAL KATE® INTIKC1GALSI 796 lS.nicrHAOGETGALSI 511 16.9 DAT 300ILOS1 56*126 15.SOSFFNOr O SOLIDSTL"SI 6 0 *1 7 7 16.SOLID HASTEICU YOSI 9*269 1 7 . LAMP ACEATSO FTI 9 5 8 *1 5 5 1 9 . FLOOR SPACETSO FT) 3 3 9 *7 9 7 19.PA9FTNG APEAISQ FTI 1 7 1 *2 1 0 20.BUILDING SITE (SO FTI 66*876 21,NtlM reo op EMPLOYEES 655

MUMPER OF STA*,nAr;0 C-VIATTQH« FCOH MEAN FOR IMPACT GENERATED DY STMUlATEO HEN EMPLOYMENT* INDUSTRY GROUP 1 9 * 1976

l.PA=TTr.ULAt*S(L1Sl -0.62 2.HvnROCAeqONSTLP5l • 0 . 2 9 3 . SULFUR OtOYTOCTLPSI -0.21 6.GASEOUS FLUORIDE(LDS1 0 .0 0 S.MVncnGE‘l SULFIDE TLPSI - 0 . 2 6 6 .CO 2 TLPSI • 0 . 2 0 7 * ALCFHYOES TLDSI • 0 . 2 6 9 .NO 2 TLPSI - 8 . 2 2 R.DOMESTIC HAIEOTCALSI • 0 . 7 0 1 6 .COOLING HATERTGALS1 - 0 . 3 2 tl.FROr£SS HATEPTGALSI • 0 . 1 1 1 2 . TOTAL HATE* INTANETGALS1 • 8 . 2 9 1 3 .DISCHARGE(CALSI - 0 . 2 5 16.5 nar aoo(L9Si - 0 * 2 9 15.SllSr£N3~D SOLTDSTLDSI * - 0 . 2 9 16.S0LI0 HASTEICU YOSI • 0 . 2 6 1 7 .LAMP areA(SO f t i - 0 . 6 2 1 9 . FLOOR SPACETSO FTI 0 .3 9 19.PARICTNG AREA ISO FTI - 0 . 6 7 2 0 . BUILDING S ITE (SQ F T I • 0 . 9 3 2 1 . NUMBER OF EMPLOYEFS - 0 .S 5 224 225

dl>49Sma><4 3 1 0 ^ 4 «4 O fU Q fO N « 4 M N W O M o ••••♦••••* h ffiir^noat » »•*•*•»» O i b # aa o o o o s *« NHMMOiKO • ll«« • N « 9*(A n* « » n h «* *

X H e O' o to C‘ H tl UJ VI « too VI ae J y oOHO j y OHO *- H- U V) to u Mhln in OH * 0 c to* v^aSO .J H ‘ D e» c ft H V U ^ U — a ftHlT O VI UI i*4 ir c III ff •-ft JhlluM *■* > «• « Uj ui h » 4 bl *• h D tl O ftUJ — HO VI Ik VI V ))N O II< r u. lid VI * C” C* 404&0 O O1 IT m c 4Q.U V* J j u s t r s n ? 9 II J J OSffX VI X D —— SC M A. ►to o HjVOttO c c Ott o HO J V) u i»i m m HO J Vi N JOH o ir . O H C JOH C V I OH O •J •« o O O O OJD H ^400 OO O J 3 o h C. sou* oh mVI Ik D c c u z in tr u e • • « X « • • • • • • • « • to to u ft <0coiu

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«4 fr fr fr K f\J in Z1.NUMO£0 OF EHt*LOYE?S -0.35 u o ui TABLE 53

tptal T*i»a CY GENERATED ST SIMULATfO NEW EMPLOYMENT, INDUSTRY GROUP 21* 197®

l.PA3tir.ULATrjlLn^| 70.B 92 2.HV0ROCAR9ONSIL0SI 6 9 ,1 3 1 1 . SULFUR n I ' l*TOPtLNS| 5 6 *7 1 9 ,6.g a s e o u s fluqrioeilrsi 0 S.HYOFnr.EN SlfLFIOEtLPSI 699 6 . CO 2 iinsi 3 0 *1 0 9 7 ■ ALOPHYnES H 9 5 I 907 a.NO 2 IL9SI 1 9 *0 7 3 R.OP-PSMC UATE»ir.ALSI 22 1 0 . COOLING HATEPtr.ALSI 166 Il.eeoPESS WAT2P|G*LS) 651 1 2 . TOTAL WATER INT*KE(GALS) 503 t3.»'I

NUMBER OP STAMpA*!) DEVIATIONS r RON HEIN FOR IMPACT Cc,JEP*TEn OY SIBILATED NFH EMPLOYMENT* X NOUS TRY G»OUP 2 1 * 1970

1 . particulates t t o s i - 0 . 6 5 2.HV0?0CA*90NSILBS) -0.32 3.SULFU? OIOYIIlFfLRSI - 0 . 2 0 6.gaseous PLuoRinEansi o.oo 5.MYnr0GpN SULFtnEILRS) - 0 . 2 6 6.CO 2 ILPSI -0.22 7.AL0FHF0ESILQS1 - 0 . 2 5 S.NO 2 ILPSI -0.21 R.O O M rR Tir WATERIGALSI - 0 . 6 0 10.COOLING WATERIGUSt -0.3<» H.pe^rES* MATFRtr.ALS) - 0 . 1 3 1 2 . TOTAL WATER INTAKEI GALS) - 0 .3 0 i i . oifcmacoeigalsi - 0 . 2 9 16.5 OAY 900 IL9S) -0.30 1 5 . SUSPENDED SOLTOSILRS) - 0 . 2 9 16.SOLIO HASTEICU YOSI -3.27 1 7 . l a n d area is q f t i - 0 . 5 7 1 9 . FLOOR SPACEISQ FTI - 0 . 6 7 19 .DS°KING AREA ISO FTI • 0 . 6 6 20.BUILDING SITE ISO FT) -0.01 21.NUNPFR OF EMPLOYEES - 0 . 0 6

to ro TABLE 54

TOTAL I-PACT GENERATED NY SIMULATED NEW EMPLOYMENT. INOUSTRY CROUP 2 2 . 1970

1.PARTICULATEStLOSI 296,210 2.HvnR0CARB0NS(LBSI 97.799 1 . SULFUR T IO Y IO -tL H S I 6 1 ,7 8 4 6.GASEOUS FLUORIDE(LBSI 0 S.HYftCftCFl SULFT9E ft IS | 2, AT? 6 . CO 2 CLPSI 6 7 ,4 1 1 7-AL*'rHvnpSIL»'S» I,3S6 A.NO 2 tL°SI 23,036 9.nni=«lTTC MATEPiGALSI 81 10.TOOLING WATERICALSI 687 ll.PPOCrSS WATERIOALSI 1.1.3 6 1 2 . TOTAL WATER INTAKEtGALSl 2 .0 0 7 tY.niS^HAO'IEtMLSI 1.320 1 4 .5 HAY PCOCLOSI 1 2 9 ,2 6 3 tS.susrf.-inEO sOLinstiPSi SR,A2i 1 6 . SOLID WASTE(CU YOSI 1 0 .7 5 3 1 7 . LAND ARfACSP FTI 3 .5 6 2 .9 3 5 IS,FLOOR SPACEtSO FTI 330,110 19.PA«tfT»»r, AREA (SR FT* 6 3 5 ,6 2 2 20.RUXLOING SITE tSQ FTI 146,525 21.KU**PEP OF EMPLOYEES 601

NUMBER OF STA»'flA0n DOTATIONS FROM NEAR FOR IMPACT GrNERATEO BY SIMJLATF-) M£W 1 NFLOYHENT. INDUSTRY GROUP 2 2 * 1970

l.PARTTCULATfSILPSI -2.T1 2,HTOROCAF9n*iS|LnS| • 0 . 2 6 3 . s u l f u r nioxioriLnsi - 0 . 1 5 4 .GASEOUS FLUORIDE(LBS1 0.00 S.HYnfPGCH SULCIDFILRSI - 0 . 2 1 6.CO 2 (LBSI • 0.21 T.ALOEHvprsiLnsi • 0 . 2 2 S.NO 2 tLPSI • 0.10 9.00NFSTIC HATERtGALSI 0 .0 1 1 0 . COOLING WATFRIGALS1 -0.25 1 1 ,PROCESS WATF»tGAL*t - 0 . 2 6 1 2 . TOTAL WATER INTAKE(GALSI - 0 . 2 4 1 3 .0 IS fM A R r.fi GALSI - 0 . 2 6 1 6 .5 nAY BOOtLRSl • 0 . 2 6 IS.SUSPENDED S0LIQSILRS1 • 0 . 2 3 16.SOLTO WASTFfCU YOSI - 0.22 17«LA**n AREA ISO FTI 0 .1 9 IS.FLOOR SPACEtSO FTI 0.‘3 t 1 9 .PARKING AREA ISO FTI • 0 . 1 0 20.BUILDING SITE ISO FTI - 0 . 2 5 2 1 . MUMPER OF ENOLOYEFS 1 .7 3 228 229

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£ z BIBLIOGRAPHY BIBLIOGRAPHY

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235 FIGURE 19. J OVERLAY OF FD/E R&REj kYDUSHlL SITES IN THE CHAj&ESTON REq