Descriptive model and evaluation system to locate sustainable industrial areas

Journal of Cleaner Production 17 (2009) 87–100

Contents lists available at ScienceDirect

Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro

Descriptive model and evaluation system to locate sustainable industrial areas I. Ferna´ndez *, M.C. Ruiz ´n INGEPRO, E.T.S. Ingenieros Industriales y Telecomunicacio ´ n, Departamento de Transportes y Tecnologı´a de Proyectos y Procesos, Grupo de Investigacio Universidad de Cantabria, Av. de los Castros s/n, 39005 Santander, Cantabria, Spain

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 April 2007 Received in revised form 6 September 2007 Accepted 28 February 2008 Available online 21 April 2008

The application of the industrial ecology to industrial areas implies re-defining the design and development process of these areas to minimize the environmental impacts along its life cycle. The development of industrial areas include several phases, one of them is the location decision that is one of the most important, since it will determine the park operation. For a long time, the location theories have only considered the proximity to raw materials, existence of basic infrastructures and qualified manpower. Nevertheless, the new model of sustainable development demands to realize a planning that defines and integrates the different subsystems and influential aspects. The aim of this work is to create a conceptual descriptive model to locate sustainable industrial areas. This model is based on longestablished factors and new strategies and experiences of sustainability. The second step is the establishment of a diffuse evaluation system that determines the fulfilment of defined sustainable criteria. This model makes the planning process for the decision-makers easier through a system that considers multiple criteria that converge in order to get the balance of industrial activities with the environment. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Eco-industrial park Location model Evaluation Fuzzy logic

1. Introduction An industrial park is a set of industries, which are grouped in order to obtain the advantages of arrange common services [1]. Industrial areas represent an important part of economic strategy in many countries, especially in developed countries where planning and promotion of these areas play a fundamental role in urban planning [2]. Nevertheless, they have an environmental risk, due to the concentration of environmental problems of each company in a small space. This economic strategy considers that the resources and the absorption capacity of impacts over the environment are unlimited. This conception has caused an imbalance in the environment that entails a new model of actuation based on the sustainable development that ‘meets the needs of the present without compromising the ability of future generations to meet their own needs’ [3]. Its application has enabled the development of tools as the industrial ecology, whose target is to improve the environmental behaviour of the industry. This discipline establishes an analogy between industrial and natural systems by creation of matter and energy interchange networks between companies [4]. An application of these concepts is the development of the sustainable industrial parks, which try to increase their economic efficiency and minimize their negative impacts. Green design,

* Corresponding author. E-mail address: [email protected] (I. Ferna´ndez). 0959-6526/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jclepro.2008.02.011

pollution prevention, energetic efficiency and material and energy interchange between companies are necessary to get these objectives because these practices minimize resource consumption and waste production [5]. Some experiences have been gathered all over the world on the development of these parks in last years [6–9]. Nevertheless, its establishment is not widely extended [10]. In spite of the existence of these new industrial areas there is a lack of a common methodology for their design. However, some documents collect environmental strategies to design these industrial parks [11]. These strategies can be applied to all the phases: selection, design and planning of the location, design of the physical structure, and construction and operation. Industrial area location is one of the most important stages which will determine its integration in the environment as well as the operation of the future industrial park. Nowadays proximity to markets, communication infrastructures or manpower availability are still the main factors of industrial location selection [12–16]. Nevertheless, the new model of development demands impacts minimization, so industrial park location has to be well planned. The impacts reduction needs to integrate land, environmental and sectorial planning tools in the earliest phases of the industrial areas development. The European Directive 2001/42/CE guides [17] will make possible to get this objective. Its goal is the integration of environmental aspects in the conceptual phase of the plans or programs to reach a sustainable development. Therefore, the ‘strategic environmental assessment’ is a formal, systematic and global process to evaluate potential environmental effects in plans

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and programs during the design process, so this instrument integrates the environmental considerations in the strategic decisions. This technique complements the Environmental Impact Evaluation tool that only corrects the impacts during the design and execution of the project. In last years several strategies have been applied in the planning of policies (transport, energy, soil use.) in order to reach a sustainable development [18–20]. Bad planning limits the economic, social and environmental development, so it is necessary to create tools that help to develop an integrated planning. Moreover, the social awareness influences in the success of any strategy, so it has to be considered in the planning [21]. An integrated planning inside this new socio-economic model implies that the decision-maker has to consider additional aspects (quality of life, existence of good environmental practices, environment’s capacity to support new activities.) to define the most suitable area to locate an industrial park. Therefore, the coexistence of an industrial area inside the urban development needs to adopt sustainable principles that will be developed through the Agendas 21 [22]. The selection of the most suitable emplacement to locate an industrial park through an integrated planning is a complex decision problem. This decision problem has to consider different criteria that help to achieve the objectives of industrial ecology and eco-industrial parks. Therefore, the aim of this work is the creation of a location model of sustainable industrial areas in order to choose the most suitable emplacement. This work explains the steps that have been followed to develop this decision-making tool, which includes long-established factors and additional factors. These factors help to achieve an integrated planning of the resources and the minimization of negative impacts that are generated by an industrial area. 2. The Analytic Hierarchy Process (AHP) The method used in this work to locate industrial areas is the Analytic Hierarchy Process (AHP). This is a multicriteria analysis, introduced by Saaty in the 1970s to develop a decision support system [23]. During the last decade the AHP has become one of the most used methods for the solution of a wide range of problems in different areas of human needs and interests. For example, the AHP has been used in various industrial applications as operations management decision-making [24], managing the risk of projects [25], benchmarking logistic operations and project management [26,27]. This method is a systematic process to represent the element of a problem hierarchically and includes procedures and principles which are used to visually structure complex decision problems involving multiple criteria. This method also illuminate inconsistencies and help the decision-maker to understand unavoidable trade-offs. The AHP allows the active participation of decision-makers in reaching agreement, and gives managers a basis to make decisions. The AHP is based on three principles: decomposition, establishment of priorities and logical consistence. The first step of AHP is formulating the decision problem in a hierarchical structure to get problem decomposition. In the hierarchy, the top represents the final objective of the decision problem. The objective of this work is to select the most suitable emplacement to locate a new industrial area. The elements that affect the decision are represented in intermediate levels. This work considers several criteria that influence on the emplacement selection as social, economic and environmental factors, planning, infrastructures.. Once a hierarchy is constructed, the decision-maker begins a prioritization to determine the relative importance of the elements in each level of the hierarchy. The elements in each level are compared as pairs

with respect to their importance in making the decision under consideration. An absolute scale, which enables the decision-maker to incorporate subjectivity, experience, and knowledge in an intuitive way, is used to make the comparison (Table 1). The comparisons two-by-two of the variables give a matrix (Fig. 8) that is raised to the square. After the elements that form each one of the rows is added and the obtained values are normalized. The normalized values that have been obtained are the weights. After comparison matrices are created, relative weights are derived for the various elements. The relative weights of the elements of each level with respect to an element in the adjacent upper level are computed as the components of the normalized eigenvector associated with the largest eigenvalue of their comparison matrix. Composite weights are then determined by aggregating the weights through the hierarchy. This is done by following a path from the top of the hierarchy at the lowest level, and multiplying the weights along of the path. The outcome of this method is a normalized vector of the overall weights. This method has made possible to develop a decision-making tool that helps to choose the most suitable industrial emplacement to get the objectives of industrial ecology. The AHP makes easier to resolve a complex decision problem because it breaks up hierarchically the decision problem through different criteria that help to choose the best alternative (the most suitable emplacement). The industrial location is a decision problem that has to consider different variables because its future operation needs guarantee the balance of the industrial activity with the environment and its economic viability. The industrial location should consider the existence of basic infrastructures, proximity to raw materials or markets. and new factors whose aim is to get a development more sustainable. The variables that should be considered make the decision problem very complex, so this work has used AHP to develop a new model of industrial location.

3. Location model The aim of the location model is decided as the most suitable emplacement to locate a new industrial area. The developed model is a decision-making tool that could be applied in the urban planning. This tool applies multicriteria evaluation in order to analyze the suitability of different areas to locate a new industrial area. This model could evaluate the suitability of the existing industrial areas too. Its design has followed these stages: hierarchical structuring,

Table 1 Two-by-two comparison scale Intensity

Definition

Explanation

1

Equal

3

Moderate

5

Strong

7

Very strong or demonstrated

9

Extreme

2,4,6,8

Between previous values

Reciprocals

If the activity i has a number that is different of zero when this is compared with the activity j, then j has a reciprocal value when it is compared with i (aij ¼ 1/aji)

Two activities contribute equally to the aim fulfilment. The experience and the judgment favour slightly to an activity. The experience and the judgment favour strongly to an activity. An activity is more favoured that other one; its predominance was demonstrated in the practice. The evidence favours an activity absolutely and clearly. When the parts need a commitment between adjacent values. Model hypothesis.

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allocation of scores and weighting. Each of these stages is explained individually. 3.1. Hierarchical structuring This work has used the Analytic Hierarchy Process to create the location model, so the first stage has made a decomposition of the industrial location decision in a hierarchical structure (Fig. 1) which represents the elements that influence the location decision. Firstly, the model has been divided into three levels (Fig. 2): geographic area selection (Phase 1), evaluation and selection of suitable areas (Phase 2) and finally evaluation of specific zones (Phase 3). Each of these phases possesses a geographical scale of application that is different. Initially an analysis is done to regional scale (Phase 1). This analysis studies a wide area. The aim of this phase is to evaluate the need of the development of new industrial areas in which emplacements would be the most suitable to locate them. Once delimited the possible locations to regional scale, the next phase evaluates local scale (Phase 2), which can study one or more municipalities. This second phase delimits with major precision of the areas that would be the best to locate a new industrial area. Finally (Phase 3) the model determines with precision of the specific plots where it is suitable for the development of the new industrial activity. Once the hierarchic levels have been established the following step is to define several variables, which are grouped in categories and subcategories. These categories and subcategories represent intermediate levels that affect the decision. The variables begin analyzing the existence of requirements that are necessary for the industrial development and these variables finish evaluating if there are enough resources in order to a new industrial park that can operate. The categories, subcategories and indicators must be clearly defined within each great group. 3.1.1. Phase 1: geographic area selection Phase 1 includes five categories (Fig. 3): social, economical, environment, planning and infrastructures. The aim of social and economic factors is to analyze the need to develop new industrial areas and its viability. These categories evaluate general aspects of the population (demography, labour occupation.) and of the economic sectors, especially the industrial sector. The existence of manpower or the economic strategy followed in a region can influence decisively the economic viability of new industrial activities [13,28]. The environment and planning factors contribute a major value-added to specific zones where the social and economic indicators are favourable. The category of environment factors analyzes the climate of the zone, the environmental performance done by municipal entities and the degree of implantation of environmental management systems in public and private organizations. These indicators try to reflect the quality of life of the population [29] and the environmental conscience in the public

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and private sector. A high awareness will facilitate the development of environmental policies that get a balanced development, as well as the necessary information to create material and energy exchange networks [30]. Finally this category evaluates the implication of the society in the reduction of resources consumption and environmental pollution through implantation of environmental improvement practices whose objective is to do an efficient consumption of resources, residual streams minimization and implantation of end of cycle steps, like reutilization and recycling. The running of renewable energies, sustainable transport and city-planning management are valued too. A society with a high execution of sustainable systems and services whose aim is to reach the balance with the environment favours the sustainable development [29]. The planning factors study if existing master plans are suitable to the industrial needs. This means that there are urban development instruments (Regional Plan, General Plan of Urban Arrangement .) that make possible the development of new industrial areas. The category of infrastructures evaluates the existence of basic infrastructures that are necessary for the development of new industrial areas. The existence of basic services and endowments that are necessary for the development of industrial activities is analyzed. The existence of suitable infrastructures can affect considerably to the costs that are a key aspect in the viability of a new industrial area [31]. The application of Phase 1 delimits large areas where a first analysis considers that there would be viable in the location of a new industrial park. Once the most important aspects to consider in the location of industrial areas have been analyzed, some legal restrictions are applied (Fig. 3). These restrictions can delimit more the possible emplacements where is possible to locate an industrial area. They identify protected zones due to its environmental interest, so these restrictions reduce the possible zones of industrial location. 3.1.2. Phase 2: evaluation and selection of suitable areas Phase 2 of the model includes two categories: physical-environment and infrastructures; and services and urban issued factors. The area of application of this phase is local. This phase specifies more than Phase 1 the zones where is possible in the location of a new industrial area. The category of physical-environment factors evaluates availability and quality of natural resources (Fig. 4). The analyzed natural resources are air, water, noise and soil, because they are the most representative of the pressure exercised on the environment as well as of its state. These indicators analyze the absorption capacity of the potential impacts over the environment, originated by the installation of new industrial activities. Moreover, they evaluate the effects on the environment, produced by the new industrial activity. A natural environment can be closed to the limit of its absorption capacity due to the concentration of activities (population or industrial activity) or a bad management [32]. In order to avoid

Fig. 1. Hierarchical structure.

´ndez, M.C. Ruiz / Journal of Cleaner Production 17 (2009) 87–100 I. Ferna

90

PHASE 1: GEOGRAPHIC AREA SELECTION

SOCIAL

ENVIRONMENT

ECONÓMICAL

PLANNING

INFRASTRUCTURES

PHASE 2: EVALUATION / SELECTION OF SUITABLE AREAS

INFRASTRUCTURES, SERVICES AND URBAN ISSUES

PHYSICAL-ENVIRONMENT

PHASE 3: EVALUATION OF SPECIFIC AREAS

MICROCLIMATE

NATURAL RESOURCES AND LOCAL INFRASTRUCTURES

COSTS

Fig. 2. Hierarchical structure of the variables’ system.

infrastructures, services and urban issued (Fig. 4). The aim is to determine if a zone has the infrastructures necessary for the operation of a new industrial area, besides the services that guarantee a good quality of life to the population that is close to the industrial

this problem, it is necessary to know the environmental quality and to make a good planning of the resources use [33]. Once the capacity of the environment to support the industrial activity has been analyzed, the location model evaluates the

Social

Demography Academic formation Work occupation Economic activity

Economical

Costs

Climate Environment

Environmental management Environmental improvement practices Restrictions

Geographic area selection Legal frame of soil planning Planning

City-planning management Transport Energy Water

Infrastructures

Recovery, reusability and recycling installations Waste treatment managers and installations Garbage dumps Communication and information technologies

Fig. 3. Categories and subcategories of Phase 1.

Legislative and rules

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Atmosphere Physicalenvironment

Soil Water

Evaluation / selection of suitable areas

Infrastructures Infrastructures, services and urban issues

Restrictions Legislative and rules

Services Urban issues

Risks

Fig. 4. Categories and subcategories of Phase 2.

area. The existence of infrastructures and suitable services is essential for the development of new productive activities, besides to guarantee a good quality of life [31,32]. Moreover, some aspects of urbanism are analyzed, since the model of existing urban development can favour the development of an industrial area and increase its future viability [31]. As in Phase 1 of the model, once the indicators included in this phase have been evaluated, the next step is the application of restrictions. This restrictions reduce the zones where is possible to locate a new industrial park. The restrictions of this phase include the existence of protected zones, servitudes and protection of historical patrimony. These restrictions also evaluate some risks as risks derived from fluvial processes (flood, pollution of aquifers), risks derived from gravitational processes (slides) and other risks (seismic, volcanic .) (Fig. 4). The next stage once the possibilities of different zones inside a municipality have been analyzed is Phase 3 of the model. This phase specifies the plots where the new industrial area will be constructed. This phase is necessary since inside a zone some plots could be more suitable than others for the industrial development, because they have basic infrastructures or better climatic conditions. 3.1.3. Phase 3: evaluation of specific zones This phase of the model includes three categories: microclimate, resources and infrastructures and costs (Fig. 5). The area of application of this phase is a specific plot. This phase evaluates very specific aspects of the plot that could affect the emplacement of the new industrial park. For example, the existence of certain physical

Microclimate

Microclimatic comfort Water Soil

Evaluation of specific areas

Natural resources and local infrastructures

Electrical energy

3.2. Evaluation functions and weighting The final aim of the location model is to obtain a score for a specific emplacement that helps to decide the best industrial location. This score represents the degree of fulfilment of the proposed criteria. The proposed criteria are based on legislation and new demands of the society, so it is necessary for a continuous feedback of the model. For this reason, it is necessary to redefine the influential factors and criteria which have to be fulfilled according to the scientist–technical and legal advance in territory arrangement and sustainability because they change with the time. An evaluation function, which establishes the thresholds and specific criteria of evaluation, has been developed for every indicator in order to obtain this score, since each indicator is expressed on its specific units. All evaluation functions give a punctuation that is between 0 and 1. The final result of the model application is a final punctuation that is between 0 and 1. This punctuation helps to select the zones which are the most suitable for the industrial location. These evaluation functions are based on the fuzzy logic. The fuzzy logic is an extension of the classic logic, which recognizes more than real and false values [36]. Therefore, a proposition can be represented by different degrees of veracity, which permit a mathematical formalization in order to handle and analyze information, whose interpretation needs subjective and imprecise concepts, so the fuzzy logic is very useful to treat phenomenon of the real world that is characterized by its complexity and uncertainty [37]. The principal functions in the fuzzy logic are (Fig. 6):

Natural gas Waste Communication and information technologies

Specific costs Costs

barriers could change the climatic conditions [34]. These variations are evaluated because they can affect the design and orientation of the new industrial park [35]. The available capacity of the infrastructures is evaluated too. However, this time the available capacity is refereed to the specific needs of the new industrial area. These needs are estimated from the plot surface. Finally the associated costs with the development of a new industrial park in a plot are evaluated.

Additional costs

Fig. 5. Categories and subcategories of Phase 3.

Linear functions: these functions express their belonging to the set by means of a function of degree one. They are used in evaluation models to evaluate distances, percentages, etc. The triangular and trapezoidal functions are an extension of the linear functions. These functions are used to define intervals of temperature, distance, etc. The triangular function is defined by the lower limit a, the modal value m and the top limit b. The trapezoidal functions have the top limit d, the lower limit a, and the support limits b and c. Gamma functions: these functions have a rapid growth from a. This growth will be bigger if the value of k increases.

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92

0, x ≤ a

0, x ≤ a

A( X ) =

A( X ) =

{(x − a ) / (m − a ) }, x ∈ (a, m ) 1, x ≥ m

{(x − a ) / (m − a )}, x ∈ (a, m] − {(x − b ) / (b − m )}, x ∈ (m, b ) 1, x ≥ b

Triangular function

Linear function 0, x ≤ a

A( X ) =

{(x − a ) / (b − a )}, x ∈ (a, b ] 1, x ∈ (b, c ] {− (x − d ) / (d − c )}, x ∈ (c, d )

A( x) =

0, x ≤ a

1−e−k(x−a)

2

,x > a

0, x ≥ d

Gamma function Trapezium function

A( x) =

{

0, x ≤ a

2 (x − a ) /(b − a)} , x ∈ (a, m]

A( x) = e−k(x−m)

2

{

1 − 2 ( x − b ) /(b − a)} , x ∈ (m, b) 1, x ≥ b 2

Gaussian function

S function

A( x ) =

2

1 1 + k ( x − m) 2

Pseudo-exponential function

Fig. 6. Kinds of fuzzy functions.

S functions: these functions are defined by its lower and top limits a and b, respectively, and by its inflection point m. Gaussian functions: the average value m and the value k (k > 0) define these functions. It is the Gauss bell. If k increases the bell will be narrower. Pseudo-exponential functions: these functions are defined by its average value m and the value k, k > 1. As the Gaussian function, if k increases the bell will be narrower. The evaluation functions that have been used in the model (Fig. 7) are linear, triangular, trapezoidal and variations of these.

Once the hierarchy and the evaluation functions have been defined the following stage is the prioritization to obtain the relative importance of the elements in each level of the hierarchy. Some of these elements that influence the decision problem are basic, since they evaluate primary needs for the industrial area development. Nevertheless, other indicators do more appeal a zone, but they are not strictly necessary. The prioritization, for example in Phase 1 of the model, begins with the variable that represents the goal (geographic area selection). Then the method establishes a comparison two-by-two of the variables through an absolute scale (Table 1). This comparison

1

1

1 M

a b L2. Negative linear function

a b L1. Positive linear function

a b c L3. Positive linear function with slope change

1

1 M

a b c L4. Negative linear function with slope change

a b c d T1. Trapezium function

Fig. 7. Evaluation functions used: L1 – positive linear function; L2 – negative linear function; L3 – positive linear function with slope change; L4 – negative linear function with slope change; and T1 – trapezium function.

´ndez, M.C. Ruiz / Journal of Cleaner Production 17 (2009) 87–100 I. Ferna Table 2 Comparison two-by-two of the variables: demography, academic formation and work occupation

Demography Academic formation Work occupation

Demography

Academic formation

Work occupation

1 2 3

1/3 1 3

1/3 1/3 1

analyzes the importance of each one of the factors that constitute the goal variable: social, economic, environment, planning and infrastructures. Secondly, the method go down in the structure of the model, so now the goal variable is ‘social factors’ that depends on: demography, academic formation and work occupation. A comparison two-by-two of the variables (demography, academic formation and work occupation) is established, as in the top level. The objective is to determine the relative importance of each one of them in the goal variable Table 2. The comparison two-by-two establishes which variable has more weight in the level that is immediately before. The comparison two-by-two goes down to the last level of the hierarchical structure. The comparisons two-by-two of the variables give a matrix (Fig. 8) that is raised to the square. After the elements that form each one of the rows are added and the obtained values are normalized. The normalized values that have been obtained are the weights. These stages are applied to all nodes of the location model in order to obtain the weights of all variables that affect the decision problem. 3.2.1. Phase 1: geographic area selection This section explains the type of evaluation functions that have been applied and the calculated weights for each of the categories of Phase 1 of the model. The evaluation functions that have been used for the social factors are linear and trapezoidal. Table 3 shows that the work occupation is the most important factor when the social situation of a specific area is evaluated. The type of evaluation function that is used and the value of the corresponding parameters are in the second column of Table 3. The evaluation functions which have been used for the economic factors are linear (Table 4). The economic activity of the region is the most relevant aspect and inside this one the industrial zones is the variable that posses the major weight. They are the most important because they give meaningful information about the need to locate new industrial areas (Table 4). The evaluation functions that have been used for the environmental factors are linear and variations of linear and trapezoidal functions (Table 5). The climate is the aspect that has the minor weight in the set of the environmental factors. The environmental management and the environmental improvement practices are the key aspects since they offer a clear vision of the existence of a good planning system in the use of resources. The existence of this planning system contributes to the participation of communities in the promotion of a sustainable development.

1

1/3 1/3

2

1

1/3

3

3

1

2

=

Table 3 Evaluation functions and weights of social factors Indicator

Evaluation function Type

Social Demography Population evolution (increase–decrease) Birth rate (%) Death rate (%) Migratory balance ( persons) Current structure Academic formation Schooling rate (%) Percentage of illiterate population Percentage of persons without education Percentage of persons with primary education Percentage of persons with secondary education Percentage of persons with university education Work occupation Unemployed rate (%) Unemployed rate male/female sex

Weight

Parameters

L1

a ¼ 0 (decrease); b ¼ 1 (increase)

0.286 0.157 0.281

L1 L1 L1

a ¼ 0 (decrease); b ¼ 1 (increase) a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (decrease); b ¼ 1 (increase)

0.179 0.082 0.314

L1

a ¼ 0 (ageing); b ¼ 1 (rejuvenation)

0.144

L1 L2

a ¼ 90; b ¼ 100 a ¼ 0; b ¼ 5

0.249 0.201 0.130

L2

a ¼ 0; b ¼ 11

0.113

L2

a ¼ 10; b ¼ 100

0.144

T1

a ¼ 0; b ¼ 23; c ¼ 60; d ¼ 100

0.253

T1

a ¼ 0; b ¼ 21; c ¼ 30; d ¼ 100

0.159

L1 L1

a ¼ 2; b ¼ 5 a ¼ 0 (unacceptable); b ¼ 1 (acceptable)

0.594 0.750 0.250

Table 6 shows the evaluation functions used for the planning factors. In this group of indicators the city-planning management is the aspect that has the major weight because it represents the speed of creation of suitable soil for the development of urban and industrial activities. Finally Table 7 reflects the evaluation functions and the weights applied to the infrastructures factors. The transport, water supplying and wastewater clearing infrastructures are the most important, followed by the energy and telecommunications infrastructures. 3.2.2. Phase 2: evaluation and selection of suitable areas The weights and the evaluation functions applied to the physical-environment factors are gathered in Table 8. The water is the most important factor, its weight with regard to atmosphere and soil, which have similar weights, represents more than 50 %. Table 9 gathers the evaluation functions and the weights of infrastructures, services and urbanism factors. The availability and quality of infrastructures have the major weight in this group of factors. 3.2.3. Phase 3: evaluation of specific zones The weights and the functions evaluation of the third phase are gathered in Table 10. The availability of resources and infrastructures that are necessary for the operation of an industrial

3

2

5/6

35/6

5

3

4/3

28/3

3

45/2

12 15/2

93

Normalization

Fig. 8. Weights obtaining of the variables: demography, academic formation and work occupation.

0.157 0.249 0.594

94

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Table 4 Evaluation functions and weights of economical factors Indicator

Evaluation function Type

Economical Economic activity Efficiency of economic sectors Efficiency of primary sector (%) Efficiency of secondary sector (%) Efficiency of tertiary sector (%) Industrial sector Industrial diversification Existence of feed industry Existence of textile industry Existence of wood industry Existence of paper industry Existence of metallurgical industry Existence of transport material industry Existence of electronic industry Existence of chemical industry Existence of no-metallic minerals industry Existence of transport industry Existence of energy industry Enterprise size Existence of economic incentives Industrial areas Industrial areas occupation (%) Existence of consolidated industrial areas Costs Soil cost (V/m2) Labour cost (V/labourer/month) Resources cost Water cost (V/m3) Gas cost (V/m2) Electric energy cost (V/kWh) Liquid fuels cost (V/m2) Waste deposit cost (V/ton) Housing cost variation (%)

Weight Parameters

L2 L2 L2

a ¼ 0.7; b ¼ 1.3 a ¼ 0.7; b ¼ 1.3 a ¼ 0.7; b ¼ 1.3

L1 L1 L1 L1 L1 L1 L1 L1 L1 L1 L1 L1 L1

a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (small); b ¼ 1 (big) a ¼ 0 (no); b ¼ 1 ( yes)

L1 L1

a ¼ 50; b ¼ 100 a ¼ 0 (no); b ¼ 1 ( yes)

L2 L2

a ¼ 24.3; b ¼ 106.9 a ¼ 1296.9; b ¼ 1297

L2 L1 L1 L2 L1 L2

a ¼ 0.49; b ¼ 1.67 a ¼ 0 ( greater than official price) ; b ¼ 1 (equal ) a ¼ 0 ( greater than official price); b ¼ 1 (equal ) a ¼ 0.919; b ¼ 0.999 a ¼ 0 ( greater than official price); b ¼ 1 (equal ) a ¼ 0; b ¼ 15.75

0.354 0.667 0.196 0.249 0.594 0.157 0.311 0.558 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.091 0.122 0.320 0.493 0.750 0.250 0.333 0.114 0.383 0.249 0.097 0.217 0.452 0.235 0.160 0.093

Table 5 Evaluation functions and weights of environment factors Indicator

Evaluation function Type

Environment Climate Heating degree days (degree days) Cooling degree days (degree days) Environmental management Functional structure of municipal environment Existence of developing and implementation of Agenda 21 Existence of plans of environmental awareness Existence of mechanisms of access to environmental information Environmental regulations to environment Existence of energy regulation Existence of water regulation Existence of soil regulation Existence of waste regulation Existence of air regulation Existence of noise regulation Existence of other regulations Environment entities Existence of public entities Existence of private entities Implantation of environmental management systems Sustainable management in public entities (%) Sustainable management in SMEs (%) Sustainable management in great enterprises (%) Environmental improvement practices Efficiency in resources consumption Efficiency in water consumption Water consumption per inhabitant (increase–decrease)

L4 L4

Weight Parameters

a ¼ 0; b ¼ 300; c ¼ 450 a ¼ 0; b ¼ 300; c ¼ 450

0.088 0.143 0.500 0.500

L1 L1 L1

a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes)

L1 L1 L1 L1 L1 L1 L1

a¼0 a¼0 a¼0 a¼0 a¼0 a¼0 a¼0

L1 L1

a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes)

L3 L3 L3

a ¼ 20; b ¼ 50; c ¼ 100 a ¼ 20; b ¼ 50; c ¼ 100 a ¼ 20; b ¼ 50; c ¼ 100

0.429 0.333 0.140 0.163 0.114 0.303 0.143 0.143 0.143 0.143 0.143 0.143 0.143 0.280 0.667 0.333 0.667 0.400 0.200 0.400

a ¼ 0 (increase); b ¼ 1 (decrease)

0.429 0.240 0.487 0.250

L1

(no); (no); (no); (no); (no); (no); (no);

b¼1 b¼1 b¼1 b¼1 b¼1 b¼1 b¼1

( yes) ( yes) ( yes) ( yes) ( yes) ( yes) ( yes)

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Table 5 (continued ) Indicator

Water consumption per business sector Primary sector (increase–decrease) Secondary sector (increase–decrease) Tertiary sector (increase–decrease) Efficiency in energy consumption Electrical energy consumption per sectors Primary sector (% decrease) Secondary sector (% decrease) Tertiary sector (% decrease) Energy consumption per kind of energy Electrical energy consumption (increase–decrease) Gas natural consumption (increase–decrease) Liquid fuels consumption Petrol consumption (increase–decrease) Diesel oil consumption (increase–decrease) Fuel–oil consumption (increase–decrease) Existence of companies that possess ecological label (%) Existence of current and future plans and projects Reduction of residual streams Municipal solid waste production (increase–decrease) Industrial waste production (% decrease) Wastewater production Wastewater production per inhabitant (increase–decrease) Wastewater production per business sector Primary sector (increase–decrease) Secondary sector (increase–decrease) Tertiary sector (increase–decrease) Reusability, recovery and recycling Reuse of wastewater treated (%) Industrial wastes recycling (%) Municipal solid waste recycling (%) Existence of current and future plans and projects Waste and by-products interchange Existence of by-products networks Matter and energy interchange networks (m) Existence of current and future plans and projects Use of renewable energies Installed solar energy (MWp) Installed windy energy (MW ) Installed hydroelectric energy (MW ) Others renewable energies (increase–decrease) Existence of current and future plans and projects Mobility and urban transport Mobility Displacement in private transportation (%) Displacement in public transportation (%) Displacement on foot or by bicycle (%) Tendency of automobile dependency (increase–decrease) Tendency of auto accident victims Alternative transport to the car Existence of car-sharing Tendency of bicycle path (increase–stabilization) Tendency of pedestrian path (increase–stabilization) Existence of current and future plans and projects City-planning management Tendency of population density (increase–decrease) Sustainable land-use (%) Planned urbanized area (%) Minimum free territory (%) Green areas (m2/inhab) Existence of open spaces recovery Existence of industrial areas rehabilitation Existence of building rehabilitation

area is the most important aspect in order to delimit the specific areas where the location of a new industrial park is suitable.

4. Conclusions The selection of industrial park location is a fundamental decision that determines the future balance of the industrial activity

Evaluation function

Weight

Type

Parameters

L1 L1 L1

a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease)

L3 L3 L3

a ¼ 0.5; b ¼ 3; c ¼ 7.1 a ¼ 0.5; b ¼ 2; c ¼ 4.8 a ¼ 3; b ¼ 8; c ¼ 15

L1 L1

a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease)

L1 L1 L1 L3 L1

a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 25; b ¼ 50; c ¼ 100 a ¼ 0 (no); b ¼ 1 ( yes)

L1 L3

a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0; b ¼ 5; c ¼ 15

L1

a ¼ 0 (increase); b ¼ 1 (decrease)

L1 L1 L1

a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease)

L3 L3 L3 L1

a ¼ 5; b ¼ 15; c ¼ 50 a ¼ 5; b ¼ 15; c ¼ 50 a ¼ 5; b ¼ 15; c ¼ 50 a ¼ 0 (no); b ¼ 1 ( yes)

L1 L2 L1

a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 500; b ¼ 2000 a ¼ 0 (no); b ¼ 1 ( yes)

L3 L3 L3 L1 L1

a ¼ 5; b ¼ 15; c ¼ 50 a ¼ 5; b ¼ 15; c ¼ 50 a ¼ 5; b ¼ 15; c ¼ 50 a ¼ 0 (stabilization); b ¼ 1 (increase) a ¼ 0 (no); b ¼ 1 ( yes)

L4 L3 L3 L1 L1

a ¼ 37; b ¼ 51; c ¼ 59 a ¼ 32; b ¼ 35; c ¼ 39 a ¼ 9; b ¼ 19; c ¼ 24 a ¼ 0 (increase); b ¼ 1 (decrease) a ¼ 0 (increase); b ¼ 1 (decrease)

L1 L1 L1 L1

a¼0 a¼0 a¼0 a¼0

L1 L3 L3 L4 L3 L1 L1 L1

a ¼ 0 (decrease); b ¼ 1 (increase) a ¼ 45; b ¼ 50; c ¼ 60 a ¼ 40; b ¼ 70; c ¼ 100 a ¼ 55; b ¼ 65; c ¼ 70 a ¼ 2; b ¼ 4; c ¼ 9 a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes)

(no); b ¼ 1 (yes) (decrease); b ¼ 1 (stabilization) (decrease); b ¼ 1 (stabilization) (no); b ¼ 1 ( yes)

0.750 0.333 0.333 0.333 0.276 0.500 0.333 0.333 0.333 0.500 0.417 0.121 0.462 0.346 0.456 0.199 0.118 0.118 0.132 0.140 0.333 0.528 0.250 0.750 0.333 0.333 0.333 0.108 0.286 0.286 0.286 0.143 0.073 0.311 0.493 0.196 0.161 0.259 0.166 0.405 0.096 0.074 0.089 0.500 0.209 0.141 0.096 0.209 0.344 0.500 0.444 0.122 0.122 0.312 0.197 0.062 0.188 0.137 0.144 0.067 0.107 0.232 0.063

with the environment. For a long time, industrial location models have only considered the existence of basic infrastructures, proximity to raw materials or markets. The need of a new development model more sustainable demands to incorporate new factors in the industrial location models. The incorporation of these factors integrates economic, social and environmental development in order to guarantee its viability.

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Table 6 Evaluation functions and weights of planning factors Indicator

Evaluation function Type

Planning Legal frame of soil planning Territorial planning Existence of Regional Plan of Territorial Arrangement Existence of regional city-planning rules Existence of Singular Projects of industrial development Existence of city-planning City-planning management Urban soil consumption (%) Urbanization intensity (%)

Weight

Parameters

L1

a ¼ 0 (no); b ¼ 1 (yes)

0.088 0.333 0.667 0.210

L1

a ¼ 0 (no); b ¼ 1 ( yes)

0.240

L1

a ¼ 0 (no); b ¼ 1 ( yes)

0.550

L1

a ¼ 0 (no); b ¼ 1 ( yes)

L3 L3

a ¼ 65; b ¼ 80; c ¼ 100 a ¼ 35; b ¼ 65; c ¼ 100

0.333 0.667 0.500 0.500

This work explains the followed methodology to create a new decision-making tool. The fundamental stage is the obtaining of the relevant factors and the criteria that have to be fulfilled. These factors are grouped in a hierarchical structure that is divided into three levels. Each of these levels represents a different geographical scale of application. At the first level, the need to implant a new industrial area in a specific zone is evaluated, so this level includes socio-economic factors. This level also includes environment factors, planning and existence of basic infrastructures that give a major value-added to the zones evaluated favourably. Once the geographical area has been delimited, the second level of the location model evaluates the most suitable emplacement in a local

scale. Firstly, this level evaluates the availability and quality of natural resources. Secondly, it evaluates the availability and quality of the infrastructures and services that are necessary for the development of industrial activity and a good quality of life. Finally, the third phase of the model delimits the specific zones that are the most suitable to locate an industrial area. This phase analyzes microclimate, availability of natural resources and local infrastructures and costs associated with the industrial area development. The proposed criteria try to plane an industrial area which must be integrated into the urban development and it should take the business opportunities which are generated by the new model of social–environmental–economic development into the Spanish frame. On the one hand, the existence and quality of necessary resources and infrastructures to develop any industrial activity generating negative minimal impacts are evaluated positively. On the other hand, the environmental behaviour nearby the area is analyzed as an opportunity to plan a model of park that includes new value-added activities and optimization of the resources utilization. Once the factors that constitute the hierarchical structure of the model and criteria to fulfil has been defined, the next step is the application of evaluation functions to all indicators, because the final aim of this tool is to obtain a score that is between 0 and 1. The last stage of the tool development is the weighting that has been done using the Analytic Hierarchy Process, AHP, since the importance of the indicators is different. It is important to emphasize that a suitable planning implies a continuous feedback of the model. For this reason, it is necessary to redefine the influential factors and criteria which have to be

Table 7 Evaluation functions and weights of infrastructures factors Indicator

Evaluation function Type

Infrastructures Transport Land transport Motorways and dual carriageway (m) State highway (m) Rail transport (m) Sea transport (m) Air transport (m) Energy Electrical energy (m) Natural gas (m) Liquid fuels (m) Drinking water supplying and wastewater clearing Drinking water supplying (m) Wastewater clearing Wastewater clearing network (m) Nearby purifying stations (m) Facilities of reusability, recovery and recycling Existence of metals recovery facilities (m) Existence of glass recovery facilities (m) Existence of tires recovery facilities (m) Waste management Management of municipal solid waste (m) Management of no hazardous waste (m) Management of hazardous waste (m) Dumps Municipal solid waste dumps (m) Inert waste dumps (m) No hazardous waste dumps (m) Hazardous waste dumps (m) Communication and information technologies Mobile telephony (m) Internet (m)

Weight Parameters

L4 L4 L4 L4 L4

a ¼ 5000; b ¼ 20,000; c ¼ 30,000 a ¼ 5000; b ¼ 20,000; c ¼ 30,000 a ¼ 15,000; b ¼ 50,000; c ¼ 70,000 a ¼ 20,000; b ¼ 60,000; c ¼ 80,000 a ¼ 25,000; b ¼ 75,000; c ¼ 100,000

L2 L2 L4

a ¼ 1000; b ¼ 3000 a ¼ 1000; b ¼ 3000 a ¼ 50,000; b ¼ 80,000; c ¼ 100,000

L2

a ¼ 1000; b ¼ 3000

L2 L4

a ¼ 2000; b ¼ 4000 a ¼ 10,000; b ¼ 30,000; c ¼ 40,000

L4 L4 L4

a ¼ 50,000; b ¼ 80,000; c ¼ 100,000 a ¼ 50,000; b ¼ 80,000; c ¼ 100,000 a ¼ 50,000; b ¼ 80,000; c ¼ 100,000

L4 L4 L4

a ¼ 50,000; b ¼ 80,000; c ¼ 100,000 a ¼ 50,000; b ¼ 80,000; c ¼ 100,000 a ¼ 50,000; b ¼ 80,000; c ¼ 100,000

L4 L4 L4 L4

a ¼ 50,000; a ¼ 50,000; a ¼ 50,000; a ¼ 50,000;

L4 L2

a ¼ 1000; b ¼ 7000; c ¼ 10,000 a ¼ 1000; b ¼ 3000

b ¼ 80,000; b ¼ 80,000; b ¼ 80,000; b ¼ 80,000;

c ¼ 100,000 c ¼ 100,000 c ¼ 100,000 c ¼ 100,000

0.202 0.290 0.448 0.750 0.250 0.283 0.164 0.106 0.170 0.594 0.249 0.157 0.216 0.667 0.333 0.667 0.333 0.068 0.594 0.249 0.157 0.068 0.140 0.333 0.528 0.068 0.094 0.165 0.308 0.433 0.120 0.500 0.500

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Table 8 Evaluation functions and weights of physical-environment factors Indicator

Evaluation function Type

Physical-environment Atmosphere Air Zones of atmospheric safety (m) Ambient air quality (times) Fixed sources of pollution (m) Noise (dB) Soil Construction specifications Urbanization capacity (soil type) Slope (%) Productive uses ( potential use) Soil quality (legal levels) Water Superficial water Existence of superficial water Existence of brooks (m) Existence of reservoirs (m) Existence of rivers (m) Existence of fountains (m) Availability of superficial water Water availability in brooks (%) Water availability in reservoirs (%) Water availability in rivers (%) Water availability in fountains (%) Quality of superficial water Water quality in brooks (water type) Water quality in reservoirs (water type) Water quality in rivers (water type) Water quality in fountains (water type) Underground water Existence of underground water Existence of aquifers (m) Existence of others underground water (m) Availability of underground water Water availability in aquifers (%) Water availability in others underground water (%) Quality of underground water Water quality in aquifers (water type) Water quality in others underground water (water type) Existence of hydrographic river basins

Weight Parameters

L1 L4 L1 L4

a ¼ 500; b ¼ 1000 a ¼ 30; b ¼ 60; c ¼ 100 a ¼ 500; b ¼ 1000 a ¼ 35; b ¼ 50; c ¼ 65

L3 L2 L1 L1

a ¼ 0 (clay); b ¼ 0.5 (lime); c ¼ 1 (silica) a ¼ 5; b ¼ 10 a ¼ 0 (agricultural, forest or mining); b ¼ 1 (none) a ¼ 0 (unsuitable); b ¼ 1 (suitable)

T1 T1 T1 T1

a ¼ 250; a ¼ 250; a ¼ 250; a ¼ 250;

L3 L3 L3 L3

a ¼ 10; a ¼ 10; a ¼ 10; a ¼ 10;

L1 L1 L1 L1

a¼0 a¼0 a¼0 a¼0

T1 T1

a ¼ 250; b ¼ 500; c ¼ 1000; d ¼ 1250 a ¼ 250; b ¼ 500; c ¼ 1000; d ¼ 1250

L3 L3

a ¼ 10; b ¼ 40; c ¼ 100 a ¼ 10; b ¼ 40; c ¼ 100

L1 L1 L1

a ¼ 0 (Type B); b ¼ 1 (Type A1) a ¼ 0 (Type B); b ¼ 1 (Type A1) a ¼ 0 ( yes); b ¼ 1 (no)

b ¼ 500; b ¼ 500; b ¼ 500; b ¼ 500;

b ¼ 40; b ¼ 40; b ¼ 40; b ¼ 40;

(Type (Type (Type (Type

B); B); B); B);

c ¼ 1000; c ¼ 1000; c ¼ 1000; c ¼ 1000;

d ¼ 1250 d ¼ 1250 d ¼ 1250 d ¼ 1250

c ¼ 100 c ¼ 100 c ¼ 100 c ¼ 100 b¼1 b¼1 b¼1 b¼1

(Type (Type (Type (Type

A1) A1) A1) A1)

0.500 0.240 0.750 0.140 0.333 0.528 0.250 0.210 0.493 0.167 0.833 0.196 0.311 0.550 0.550 0.333 0.121 0.457 0.339 0.083 0.333 0.107 0.501 0.317 0.075 0.333 0.107 0.501 0.317 0.075 0.210 0.333 0.833 0.167 0.333 0.833 0.167 0.333 0.833 0.167 0.240

Table 9 Evaluation functions and weights of infrastructures, services and urban issues Indicator

Evaluation function Type

Infrastructures, services and urban issues Infrastructures Transport availability and accessibility Land transport Existence of land transport Existence of motorways and dual carriageways (m) Existence of state highway (m) Existence of regional highway (m) Land transport capacity Fluency of motorways and dual carriageways (intensity/capacity) Fluency of state highway (intensity/capacity) Fluency of regional highway (intensity/capacity) Rail transport Existence of rail transport (m) Rail transport capacity Capacity of rail line (line type) Capacity of station (station category) Sea transport Existence of port (m) Capacity of port ( port category) Air transport Existence of airport (m)

Weight Parameters

L4 L4 L4

a ¼ 2000; b ¼ 4000; c ¼ 5000 a ¼ 500; b ¼ 1500; c ¼ 2000 a ¼ 100; b ¼ 1000; c ¼ 2000

T1 T1 T1

a ¼ 0; b ¼ 0.01; c ¼ 0.5; d ¼ 0.9 a ¼ 0; b ¼ 0.01; c ¼ 0.5; d ¼ 0.8 a ¼ 0; b ¼ 0.01; c ¼ 0.5; d ¼ 0.7

L4

a ¼ 3000; b ¼ 10,000; c ¼ 15,000

L1 L1

a ¼ 0 (C1); b ¼ 1 (A1) a ¼ 0 (3); b ¼ 1 (1)

L4 L1

a ¼ 5000; b ¼ 15,000; c ¼ 20,000 a ¼ 0 (C ); b ¼ 1 (A)

L4

a ¼ 8000; b ¼ 18,000; c ¼ 25,000

0.500 0.594 0.290 0.535 0.500 0.614 0.268 0.117 0.500 0.683 0.200 0.117 0.270 0.500 0.500 0.500 0.500 0.120 0.500 0.500 0.075 0.500 (continued on next page)

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Table 9 (continued ) Indicator

Capacity of airport (airport category) Energy Electrical energy Existence of electrical energy facilities High tension lines (m) Middle tension lines (m) Availability of electrical power (%) Natural gas Existence of natural gas facilities (m) Availability of natural gas (%) Liquid fuels (m) Drinking water supplying and wastewater clearing Drinking water supplying Existence of drinking water supplying network (m) Capacity of drinking water supplying network (%) Wastewater clearing Existence of wastewater clearing facilities Existence of wastewater clearing network (m) Nearby purifying stations (m) Capacity of wastewater clearing facilities Capacity of wastewater clearing network (%) Capacity of purifying stations (%) Facilities of reusability, recovery and recycling Existence of facilities of reusability, recovery and recycling Existence of metals recovery facilities (m) Existence of glass recovery facilities (m) Existence of tires recovery facilities (m) Capacity of facilities of reusability, recovery and recycling Capacity of metals recovery facilities (%) Capacity of glass recovery facilities (%) Capacity of tires recovery facilities (%) Existence of waste management Existence of management of municipal solid waste (m) Existence of management of no hazardous waste (m) Existence of management of hazardous waste (m) Existence of dumps Existence of municipal solid waste dumps (m) Existence of inert waste dumps (m) Existence of no hazardous waste dumps (m) Existence of hazardous waste dumps (m) Communication and information technologies Existence of communication and information technologies facilities Existence of mobile telephony facilities (m) Existence of internet facilities (m) Capacity of communication and information technologies Capacity of mobile telephony facilities (%) Capacity of internet facilities (%) Services Education Existence of schools (m) Existence of state secondary schools (m) Existence of universities (m) Medical care Hospitals (m) Hospital beds (beds/1000 inhabitants) Existence of chemists Health centres (inhabitants/centre) Culture and leisure Existence of sport facilities Existence of cultural centres Existence of museums Technical attendance and commercial services Commercial services (m) Technical attendance services (m) Urban issues Planning and management Soil classification Existence of development Plan Urban and interurban transport Public transport (m) Bicycle path (m) Pedestrian path (m)

Evaluation function

Weight

Type

Parameters

L1

a ¼ 0 (third ); b ¼ 1 (first)

L4 L4 L3

a ¼ 100; b ¼ 500; c ¼ 1000 a ¼ 50; b ¼ 200; c ¼ 300 a ¼ 50; b ¼ 70; c ¼ 100

L4 L3 L4

a ¼ 100; b ¼ 500; c ¼ 1000 a ¼ 50; b ¼ 70; c ¼ 100 a ¼ 10,000; b ¼ 20,000; c ¼ 50,000

L4 L3

a ¼ 100; b ¼ 700; c ¼ 1000 a ¼ 50; b ¼ 70; c ¼ 100

L4 L4

a ¼ 500; b ¼ 1500; c ¼ 2000 a ¼ 1000; b ¼ 7000; c ¼ 10,000

L3 L3

a ¼ 50; b ¼ 70; c ¼ 100 a ¼ 50; b ¼ 70; c ¼ 100

L4 L4 L4

a ¼ 10,000; b ¼ 20,000; c ¼ 50,000 a ¼ 10,000; b ¼ 20,000; c ¼ 50,000 a ¼ 10,000; b ¼ 20,000; c ¼ 50,000

L3 L3 L3

a ¼ 50; b ¼ 70; c ¼ 100 a ¼ 50; b ¼ 70; c ¼ 100 a ¼ 50; b ¼ 70; c ¼ 100

L4 L4 L4

a ¼ 10,000; b ¼ 20,000; c ¼ 50,000 a ¼ 10,000; b ¼ 20,000; c ¼ 50,000 a ¼ 10,000; b ¼ 20,000; c ¼ 50,000

L4 L4 L4 L4

a ¼ 10,000; a ¼ 10,000; a ¼ 10,000; a ¼ 10,000;

L4 L4

a ¼ 250; b ¼ 750; c ¼ 1000 a ¼ 100; b ¼ 700; c ¼ 1000

L3 L3

a ¼ 50; b ¼ 70; c ¼ 100 a ¼ 50; b ¼ 70; c ¼ 100

b ¼ 20,000; b ¼ 20,000; b ¼ 20,000; b ¼ 20,000;

c ¼ 50,000 c ¼ 50,000 c ¼ 50,000 c ¼ 50,000

L2 L4 L4

a ¼ 1000; b ¼ 2000 a ¼ 1000; b ¼ 5000; c ¼ 8000 a ¼ 20,000; b ¼ 40,000; c ¼ 50,000

L4 L1 L1 L2

a ¼ 75,000; b ¼ 110,000; c ¼ 120,000 a ¼ 3.6; b ¼ 9.1 a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 10,000; b ¼ 5000

L1 L1 L1

a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes) a ¼ 0 (no); b ¼ 1 ( yes)

L4 L4

a ¼ 5000; b ¼ 8000; c ¼ 10,000 a ¼ 5000; b ¼ 8000; c ¼ 10,000

L1 L1

a ¼ 0 (rustic); b ¼ 1 (urban) a ¼ 0 (no); b ¼ 1 ( yes)

L4 L4 L4

a ¼ 50; b ¼ 500; c ¼ 1000 a ¼ 50; b ¼ 500; c ¼ 1000 a ¼ 50; b ¼ 500; c ¼ 1000

0.500 0.170 0.709 0.500 0.750 0.250 0.500 0.179 0.500 0.500 0.113 0.216 0.667 0.500 0.500 0.333 0.500 0.667 0.333 0.500 0.500 0.500 0.068 0.500 0.550 0.210 0.240 0.500 0.550 0.210 0.240 0.068 0.196 0.493 0.311 0.068 0.124 0.188 0.299 0.389 0.120 0.500 0.500 0.500 0.500 0.500 0.500 0.249 0.317 0.594 0.249 0.157 0.389 0.490 0.231 0.116 0.163 0.122 0.143 0.429 0.429 0.172 0.500 0.500 0.157 0.667 0.750 0.250 0.333 0.709 0.113 0.179

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Table 10 Evaluation functions and weights of specific areas factors Indicator

Specific areas factors Microclimate Natural resources and local infrastructures Water Superficial water availability (%) Underground water availability (%) Soil Implemented use (%) Soil property (owner number) Electrical energy Electrical power availability (%) Capacity of natural gas supplying network (%) Capacity of drinking water supplying (%) Capacity of wastewater clearing (%) Waste Capacity of metals recovery facilities (%) Capacity of glass recovery facilities (%) Capacity of tires recovery facilities (%) Communication and information technologies Capacity of mobile telephony (%) Capacity of internet (%) Costs Specific costs (V/m2) Additional costs Existence of electrical needs costs Existence of drinking water supplying costs Existence of wastewater clearing costs Existence of lands movement costs Existence of communication and information technologies costs Existence of special works costs Existence of administrative costs Existence of soil regeneration costs

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Evaluation function

Weight

Type

Parameters

L1

a ¼ 0 (worse); b ¼ 1 (equal )

L3 L3

a ¼ 10; b ¼ 40; c ¼ 100 a ¼ 10; b ¼ 40; c ¼ 100

L4 L4

a ¼ 25; b ¼ 50; c ¼ 75; a ¼ 1; b ¼ 3; c ¼ 5

L1 L1 L1 L1

a ¼ 0; a ¼ 0; a ¼ 0; a ¼ 0;

L1 L1 L1

a ¼ 0; b ¼ 100 a ¼ 0; b ¼ 100 a ¼ 0; b ¼ 100

L1 L1

a ¼ 0; b ¼ 100 a ¼ 0; b ¼ 100

L2

a ¼ 24.3; b ¼ 106.9

L1 L1 L1 L1 L1 L1 L1 L1

a¼0 a¼0 a¼0 a¼0 a¼0 a¼0 a¼0 a¼0

b ¼ 100 b ¼ 100 b ¼ 100 b ¼ 100

( yes); ( yes); ( yes); ( yes); ( yes); ( yes); ( yes); ( yes);

b¼1 b¼1 b¼1 b¼1 b¼1 b¼1 b¼1 b¼1

(no) (no) (no) (no) (no) (no) (no) (no)

0.089 0.089 0.559 0.246 0.750 0.250 0.170 0.333 0.667 0.150 0.750 0.250 0.218 0.070 0.053 0.540 0.297 0.163 0.093 0.667 0.333 0.352 0.667 0.333 0.205 0.230 0.121 0.160 0.072 0.063 0.094 0.055

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