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ALPCHECK2

ALPINE MOBILITY CHECK – STEP 2

AlpCheck2 A5.4.8.1 - Environmental impact assessment with ESI - final report

Date: November 2011

Main Authors: OMEGA consult Ltd.:

Cveto Gregorc, MSc Phys.

Robert Rupar, MSc Econ.

Miha Klun, BEcon.

Špela Železnikar, MSc Env. Mgt.

Nina Jurešič, BEng Geol.

Andreja Cundrič, Ph.D.

Contributions: OMEGA consult Ltd.:

Matjaž Oberžan, BEcon.

Elvis Testen, BSc (Eng.)Transp.

Vera Bjelica, BBA

Rado Osredkar, BPol.Sc.

Grega Boštjančič, BE Comp.Sc.

ALPCHECK2 CONSORTIUM Leader Partner: VENETO

Veneto Region (Regional Secretariat for Infrastructures - Logistics Unit)

Partner 1: RAVA

Regione Autonoma Valle d'Aosta - Direzione servizi antincendio e di soccorso

Partner 2: CARINZIA

Carinthia Regional Government Administration (Department 7 - Common Law and Infrastructure)

Partner 3: TCI

TCI Röhling Transport Consulting International

Partner 4: ERSAF

Ente Regionale per i Servizi all' Agricoltura e alle Foreste:Regione Lombardia

Partner 5: VPA

Venice Port Authority

Partner 6: MATTM

Ministry of Environment, Sea and Land Protection of Italy

Partner 7: OBB

Board of Building and Public Works within the Bavarian Ministry of the Interior

Partner 8: CETE MED

A Technical Study and Engineering Centre

Partner 9: MSLO

Republic of Slovenia, Ministry of Transport, Slovene Roads Agency

A5.4.8.1 - Environmental impact assessment with ESI - final report

TABLE OF CONTENTS

1 INTRODUCTION.............................................................................................................................1

2 ENVIRONMENTAL IMPACT ASSESSMENT WITH ENVIRONMENTAL SENSITIVITY INDEX (ESI) ...........................................................................................................2

2.1 ESUSTI - ENVIRONMENTAL SUSTAINABILITY INDEX..................................................................3 2.2 EVI – ENVIRONMENTAL VULNERABILITY INDEX.....................................................................4 2.3 ESI – ENVIRONMENTAL SENSITIVITY INDEX............................................................................6

2.3.1 Collection of data for the calculation of ESI ...............................................................................7 2.3.1.1 Identification of indicators........................................................................................................ 7 2.3.1.2 Dataset ...................................................................................................................................... 7 2.3.1.3 Spatial division ......................................................................................................................... 9

2.3.2 Methodology for the calculation of ESI .....................................................................................10 2.3.2.1 Identification of indicators...................................................................................................... 11 2.3.2.2 Weights for the common assessment ...................................................................................... 12 2.3.2.3 Calculation of the sensitivity index......................................................................................... 14 2.3.2.4 Conversion of the results into sensitivity classes .................................................................... 18 2.3.2.5 Road network intersection with ESI ....................................................................................... 22

3 LITERATURE ................................................................................................................................24


1

1 INTRODUCTION

AlpCheck2 is a continuation of the international project for the area of the Alpine region in the

framework of the INTERREG IIIB that finished in 2008. It is an international project with the

Slovenian participation. The main objectives of the project are modelling of traffic flows of heavy

goods vehicles in the Alpine region and impacts of these vehicles on the environment of the

Alpine region. Slovenia participates in both key stages.

Slovenian Roads Agency carries out activities of the following work packages:

• WP4 - transport system for decision support: preparation of the transport model for the

Alpine area, simulation of future scenarios of supply and demand, obtaining data for

future road network;

• WP5 - Environmental impact assessment: data acquisition and preparation, participation

in the implementation model for the assessment of environmental impacts.

In this report environmental impact assessment with environmental sensitivity index (ESI) (as

part of WP5) is presented.


2

2 ENVIRONMENTAL IMPACT ASSESSMENT WITH ENVIRONMENTAL SENSITIVITY INDEX (ESI)

Determination of environmental sensitivity index derives from the needs of the oil industry,

which in the sixties and seventies of the last century already expected higher oil spills and was

preparing for potential consequences. The calculation was originally developed especially for

coastal areas.

Together with the development of geographical information systems it has become possible to

make spatial data analyses and vulnerability mapping, which first began to emerge in the U.S.

Later, the practice to produce such sensitivity maps was spread to other countries with coastal

areas. In addition to environmental sensitivity index, similar environmental sustainability

and environmental vulnerability indices were also calculated for a number of countries in the

world. Determination of environmental sensitivity with an index was later extended and spread

from coastal areas to the whole territory of each country.

The issue of environmental sensitivity is defined in national legislation. For example, the

Slovenian Law on Environmental Protection (Official Journal of the RS, no. 39/2006, 70/2008,

108/2009) stipulates that the government should set the criteria of sensitivity, vulnerability or

burdening of the environment, upon which parts of the environment or individual areas can be

classified into different classes or levels. In these parts or specific areas of the environment new

operations affecting the environment are permitted only, if they do not worsen the classification

of the areas within a certain class or level.

In following chapters firstly environmental sustainability index and environmental vulnerability

index for the countries of the Alpine region are summarised. Then the methodology for the

calculation of ESI and ESI calculation for Slovenia are presented.


3

2.1 ESUSTI - ENVIRONMENTAL SUSTAINABILITY INDEX

National concern for the environment in individual countries is reflected by the Environmental

sustainability index. The method of calculation ESustI was designed by Yale and Columbia

Universities in collaboration with the World Economic Forum and United Research Centre of

the European Union. Environmental sustainability index is calculated as a linear combination of

76 parameters grouped into 21 indicators that describe five environment-related areas:

• environmental systems,

• reduction of environmental burdens,

• reduction of human vulnerability to environmental burdening,

• social and institutional capability to react to environmental challenges and

• global concern for the environment.

The ESI score quantifies the likelihood that a country will be able to preserve valuable

environmental resources effectively over the period of several decades. Put another way, it

evaluates a country’s potential to avoid major environmental deterioration. However, because the

different dimensions of environmental sustainability do not always correlate with one another,

the ESI score taken by itself does not identify the relative contribution of the different indicators

to the overall assessment of a country’s medium-term prospects, nor what particular types of

challenges are most likely to pose acute problems.

Figure 2.1: Global environmental sustainability index (Source: 2005 Environmental Sustainability Index; Yale University, Columbia University; 2005)


4

According to the estimates from 2005, Switzerland has the highest score among the Alpine countries, therefore it is assumed it should be more likely to provide its citizens with high levels of environmental quality and services into the foreseeable future. Slovenia is in the 29th place among 146 countries.

Table 2.1: Environmental sustainability index for the countries of the Alpine region

Country ESustI Order (of 146 countries)

A – Austria 62,7 10

D – Germany 56,9 31 F – France 55,2 36 I – Italy 50,1 69

SI – Slovenia 57,2 29 CH – Switzerland 63,7 7

(Source: 2005 Environmental Sustainability Index; Yale University, Columbia University; 2005)

2.2 EVI – ENVIRONMENTAL VULNERABILITY INDEX

In a similar way as the sustainable environmental index, the vulnerability index also describes the

state of the environment. Index of vulnerability of the natural environment has been produced in

collaboration with the South Pacific Applied Geosciences Commission (SOPAC) and the United

Nations Environment Programme (UNEP) and their partners. Among the European partners

that participated in the development Italy, Ireland, Norway and the University of Malta can be

mentioned.

EVI index is composed of 50 indicators; of which 32 describe the risks, eight indicators shows

resistance of the environment and 10 indicators measure environmental damage. The indicators

are combined into following groups:

• Climate Change

• Exposure to natural disasters,

• Biodiversity,

• Desertification,

• Water,

• Agriculture / Fisheries and

• Human health.


5

In combination with the economic and social vulnerability of specific countries environmental

vulnerability index provides an insight into the processes that may adversely affect sustainable

development. In 2005, sample indicators were determined also for the Alpine countries.

Each indicator can take up values between 1 and 7. The total EVI represents the average of all

considered indicators. Assessment of vulnerability of individual country is determined by the

following scheme in Table 2.2:

Table 2.2: Environmental vulnerability determination according to EVI

Extremely vulnerable 365+

Highly vulnerable 315+ Vulnerable 265+

At risk 215+ Resilient <215

(Source: The Environmental Vulnerability Index; UNEP & SOPAC; 2005)

Individual indicators for specific countries are missing or are not relevant, that is why next to the

total index also the proportion of data used is stated. The total index is the average of all

indicators and is shown in the following table 2.3 for the countries of the Alpine area.

Table 2.3: EVI for the countries of the Alpine area

Country EVI Availability and relevance

of data used (%) Vulnerability estimate

A – Austria 369 84 Extremely vulnerable

D – Germany 357 98 Highly vulnerable

F – France 361 98 Highly vulnerable

I – Italy 386 98 Extremely vulnerable SI – Slovenia 362 90 Highly vulnerable CH – Switzerland 348 88 Highly vulnerable

(Source: The Environmental Vulnerability Index; UNEP & SOPAC; 2005)

Countries of the Alpine area have similar assessments of the environmental vulnerability index.

Austria and Italy are estimeted as extremely vulnerable, while other Alpine countries are

determined as highly vulnerable, according to EVI.

According to EVI, Slovenia as a whole is highly vulnerable. Micro analysis of different areas in

Slovenia, regarding four indicators (population density, proportion of children and elderly, water

bodies and protected areas) is presented in following chapter.


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2.3 ESI – ENVIRONMENTAL SENSITIVITY INDEX

Protection against oil spills requires accurately determining priorities in the implementation of

measures according to the sensitivity of protected resources. Results such as ESI are part of

electronic databases for the management of natural resources. In conjunction with protection

against oil spills particularly the following is analyzed:

• data on the type of coast according to the sensitivity, resistance to oil pollution and ease

of cleaning,

• biological resources, particularly sensitive animal and plant species and their habitats and

impacts on humans, particularly the impact on public health and sensitivity of this area

due to human use.

Determination of environmental sensitivity with an index was later extended and spread from

coastal areas to the whole territory of each country. In 2003, a model of environmental sensitivity

for the U.S. state of North Carolina was created. The authors created a spatial representation of

sensitivity in the form of maps with the help of GIS tools. They focused on the demographic

indicators such as: population density and proportion of young people and elderly, the presence

of water bodies and the presence of protected areas. A square grid of cells with the side length of

1 mile served as base.

The general formula for calculating the sensitivity of each cell is:

(1) jjbbaa

ji

aiiiN WFWFWFWFG +++==∑

=

=

L

Calculation for the »affected« area of more cells:

(2) ∑=

=

+++==nN

NnNT GGGGG

121 L

with:

- GN ... environmental sensitivity index (ESI) for the cell GN,

- Fi ... sensitivity factor of indicator i,

- Wi ... weight of indicator i,

- j ... number of used indicators,


7

- GT ... common ESI of the affected area,

- n ... number of cells that are covering the affected area

2.3.1 Collection of data for the calculation of ESI

The required input data for calculating ESI are:

• indicators from which the index will be calculated,

• graphic layers with the relevant content, with which the indicator values for all the cells of

the area can be identified and

• relevant division of the observed area to room in a fully covered.

Below are detailed input data.

2.3.1.1 Identification of indicators

Indicators:

• Demographic indicators;

- population density

- proportion of children under 5 years and elderly over 65 years of age

• Water status;

- proportion of surface water in the cell,

- proportion of groundwater in the cell,

• Protected areas and biodiversity;

- proportion of protected areas in the cell (Natura 2000, protected areas).

2.3.1.2 Dataset

In accordance to the selected indicators to determine ESI we will provide the relevant graphic

(geo-referenced) data base, which will enable the elaboration of spatial data analyses. As example

we reference some of the already gained geo-referenced data layers (Figures 2.2 and 2.3).


8

Figure 2.2: Water protection zones in Slovenia

(Source: ARSO, 2007)

Water protection zones

MAP OF WATER PROTECTION ZONES

state border

3 – influential zone

2 – outer zone

1 – inner zone


9

Figure 2.3: Natura 2000 areas in Slovenia

(Source: ARSO, 2007)

2.3.1.3 Spatial division

In order to determine ESI, a full coverage of space needs to be insured. The most efficient

geometrical form for this purpose is the correct hexagon. In comparison with the equilateral

triangle and square, at least six hexagons are necessary to ensure complete coverage of the area. It

is also true that the difference in distance between points on the periphery and the centre of the

hexagon is smaller than that of a triangle or square. Other regular polygons do not guarantee

whole area (country) coverage.

Therefore, cells in the shape of a regular hexagon with a side length of 1 km were used for the

determination of ESI (Figure 2.4).

State border

NATURA 2000 AREAS IN SLOVENIA


10

Figure 2.4: Coverage of Slovenia with hexagons for determining ESI

(Source: OMEGA consult, 2011)

2.3.2 Methodology for the calculation of ESI

The model is a mental, formal and material structure, which, according to the objectives of the

study explains, manages, summarizes the essential characteristics and thereby simplifies or

predicts the actual subject, which is being studied.

Based on the model of environmental sensitivity, produced by the U.S. state of North Carolina in

2003, spatial representation of sensitivity in Slovenia was developed, with minor corrections and

using appropriate GIS tools. The methodology used focuses on various indicators, namely

indicators of population density and proportion of young and elderly people, the presence of

water bodies and the presence of protected areas. As basis for coverage of the entire territory of

Slovenia, a network of hexagons with the side length 1 km and a maximum area of 2,59 km2 has

been used.


11

Index of environmental sensitivity was calculated as the sum of individual indices. The results

were classified into five classes with natural division and cartographically displayed. Subsequently,

a spatial intersection of the road network and an intersection of the layer of ESI were made.

Through this intersection assessments of individual categories of roads within a particular class of

environmental sensitivity were collected.

Figure 2.5: Methodology for determining ESI

(Source: Global Institute for Energy and Environmental Systems. UNC Charlotte)

2.3.2.1 Identification of indicators

Indicators for determining ESI should be selected and set in such a way, as to provide all the

influential factors of the model calculation. Demographic indicators are gaining more and more

importance when considering environmental sensitivity:

Indicators:

• Demographic indicators;

- population density - layer of the total population in Slovenia,

- proportion of children under 5 and elderly over 65 years of age – two specific age

groups are covered by this layer

• Water bodies;

- the proportion of surface water within one cell (one hexagon)

- the share of underground water in the cell (hexagon).


12

Surface running and still water, as well as ground water are united in a common layer "water

bodies".

• Protected areas and biodiversity;

- the proportion of protected areas;

- protected areas.

Within protected areas are all areas that fall within the area Natura 2000 and all protected areas.

After the set of spatial indicators has been prepared, data is ready for further calculation and

analysis.

Figure 2.6: Group of chosen indicators for the calculation of ESI


2.3.2.2 Weights for the common assessment

Selection of weights to balance the weight and importance of a particular indicator, which are

part of the structure of the model, is of key importance for the model. After determining the

indicators for each area it is necessary to also determine the importance of each indicator. The

allocation of a certain weight indicator consequently enhances or reduces its importance, but this

is a subjective assessment.

To select the correct combination of weights, four different variants were analyzed and

combination of weights, which has made the most representative results, has been selected.


13

In order for the assumed combinations of weighting factors with the total sum of 1 to be more

sensible, correlation coefficients were also calculated, especially between the factors, which are

assumed to be interdependent and interrelated. The correlation coefficient was calculated

between the index of the total population and the index of the population of a certain age group

and proved to be highly positive with the value of 0,9, which indicates a strong correlation

between these two indicators. Also, the correlation coefficient was calculated between the index

of water bodies and index of protected areas. The value of -0.2 returned a negative correlation

and indicated an inverse relationship between the studied indicators. Based on the calculated

correlations, the following combinations of weighting factors were proposed:

Variant 1:

- Population density: 0,3

- Proportion of children under 5 and older than 65 years of age: 0,4

- Water bodies: 0,2

- Protected Areas: 0,1

Variant 2:



- Water bodies: 0,3


Variant 3

- Population density: 0


- Water bodies: 0,3


Variant 4



- Water bodies: 0,3



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2.3.2.3 Calculation of the sensitivity index

In order to calculate the index of environmental sensitivity, it was initially necessary to calculate

the index of each indicator or influential factor, taking into account various weight factors.

Indicators were calculated by the formulas listed below:

a) Calculation of the index of the population

Gp = Popi/Poptotal * Wp * Pmax/Pi

Gp – index of the population

Popi – number of inhabitants within a specific hexagon

Poptotal – number of total population in Slovenia: 2.046.946 inhabitants

Wp – weights, considered for the calculation of the population index (Variant 1 – 0,3, Variant 2 –

0,1, Variant 3 – 0, Variant 4 – 0,4)

Pmax – maximum area covered by a hexagon: 2,59 [km2]

Pi – observed area covered by hexagons [km2]

The formula used for the calculation of Gp:

Gp = ([nr. of inhab.]/2.046.946)*Wp*(2,59/ [area km2])


15

b) Calculation of the index of the specific age group (proportion of population under 5

and over 65 years of age)

Ga = Popa/Poptotal * Wa * Pmax/Pi

Ga – age group index

Popa – population structure of a certain age (younger than 5 and older than 65 years of age)

within the brackets of the specific hexagon

Poptotal – number of total population in Slovenia: 2.046.946 inhabitants

Wa – weights, considered for the calculation of the age group index (Variant 1 – 0,4, Variant 2 –

0,4, Variant 3 – 0,5, Variant 4 – 0,1)



The formula used for the calculation of Gs:

Ga= ([nr. of inhab.]/2.046.946)*Wa*(2,59/ [area km2])


16

c) Calculation of the water bodies index

Gwb = Pwi / Pwtotal * Ww * Pmax/Pi

Gwb– water bodies index

Pwbi – area of a specific water body within a considered hexagon [m2]

Pwbtotal – total water bodies area in Slovenia: 2.648 [km2]

Wwb - weights, considered for the calculation of the water bodies index (Variant 1 – 0,2, Variant 2

– 0,3, Variant 3 – 0,3, Variant 4 – 0,3)



The formula used for the calculation of Gwb:

Gwb= ([area km2]/2.648)*Wwb*(2,59/ [area km2])


17

d) Calculation of the protected areas index

Gpa = Ppai / Ppa total * Wpa * Pmax/Pi

Gpa –protected areas index

Ppa i – protected area within a specific hexagon [km2]

Ppa total – total protected areas in Slovenia: 7.728 [km2]

Wpa – weights, considered for the calculation of the protected areas index (Variant 1 – 0,1,

Variant 2 – 0,2, Variant 3 – 0,2, Variant 4 – 0,2)



The formula used for the calculation of Gpa:

Gpa= ([area km2]/7.728)*Wpa*(2,59/[area km2])

e) Calculation of the index of environmental sensitivity

GESI = Gp + Ga + Gwb + Gpa

Environmental sensitivity index was calculated as the sum of individual indices, for which

subsequently also cartographic comparisons with each other were made. The results represent

four different spatial representations of sensitivity in Slovenia, depending on the choice of

different weights.


18

2.3.2.4 Conversion of the results into sensitivity classes

After calculating the index of environmental sensitivity for all four variants of weights, the results

were classified into five categories / classes, according to natural boundaries. For each of the

variants, a cartographic presentation was produced, which indicates the choice of weights and the

classification method of environmental sensitivity index. Variants are shown in Figures 2.7 - 2.10.

Figure 2.7: ESI calculation – Variant 1


The choice of weights for variant 1 is somewhat more demographically oriented as the two

demographic indicators represent 70 percent of the total weight. In the allocation of weight

attributes utmost importance to residents, while environmental aspects are (perhaps too)

neglected.

Demographic factors attribute more weight to age structure of the population, while

environmental indicators attribute greater importance to water bodies.


19



In variant 2 the weight of demographic factors is relieved by 20 percent, and consequently the

weight of environmental factors increases for this percentage.


20



In this variant the demographic indicators represent half of the total weight. The indicator of

population density is null, while the indicator of age structure is 0,5. The distribution of weights

between demographic and environmental indicators in this case is the same (50% - 50%).


21



Variant 4 - the weight of demographic indicators in this case again takes up 50 percent, but it

differs from variant 2: in this case more weight is attributed to the population density indicator.

The relationship between environmental indicators remains the same.

After the comparison and review of all four variants, the fourth variant is suggested for

further analysis. The chosen solution weighs demographic and environmental indicators

equally. It is presumed that it is more appropriate to focus on population density, rather

than on age structure. In selecting indicators with a focus on age structure irregularities

of evaluation might occur in high population density areas, which have a minimal

proportion of elderly people and children


22

2.3.2.5 Road network intersection with ESI

The selected variant 4 of ESI calculation was covered with the road network that is considered

for the project AlpCheck2. We analyzed how much of the network is located in each sensitivity

class and which road categories are presented in each class. Environmental sensitivity index was

classified into five classes of sensitivity with a normal distribution.

Table 2.4: Length of the road network within a specific sensitivity class of ESI

Sensitivity class Length [km]*

1 resilient area 706,69

2 less sensitive area 1.242,07 3 sensitive area 995,02

4 very sensitive area 173,94 5 extremely sensitive area 12,97 Total: 3.130,70

*motorway data are giver for both directions

Analysis showed that most of the total of 3.130 km of the road network is located within less

sensitive areas (Tables 2.4 and 2.5). 31 percent of roads fall within the sensitive areas and only 0,4

percent of roads are located in the most sensitive area.

Table 2.5: Length of road network within a certain sensitivity class of ESI by type of road

Sensitivity class Type of road Length [km]

motorway 146,78

primary 179,45

secondary 203,43 1 resilient area

trunk 30,26

total: 559,92

motorway 163,76

primary 394,97

secondary 474 2 less sensitive area

trunk 49,86

total: 1.082,59

motorway 212,93

primary 298,62

secondary 225,63 3 sensitive area

trunk 44,91

total: 782,09


23

Sensitivity class Type of road Length [km]

motorway 27,79

primary 57,41

secondary 39,59 4 very sensitive area

trunk 21,36

total: 146,15

motorway 0,22

primary 5,17 5 extremely sensitive

area trunk 7,36

total: 12,75

Total: 2.583,50

In table 2.5 the length of the entire road network is classified by types of roads within the classes

of environmental sensitivity. Motorways are mostly represented in the sensitive area, while most

trunk roads are within environmentally less sensitive areas. Primary and secondary roads are also

represented in this class in the fullest extent. A very small part of the considered road network

fall into the most sensitive classes (4 and 5) that are located near major cities. Graphic

presentation of table 2.5 is given in figure 2.11. For the definition of roads by type see Figure 2.4.

* *motorway data are giver for both directions

Figure 2.11: Classification of the road network according to sensitivity classes



24

3 LITERATURE

1. Inyang H.I., Fisher G.F., Mbamalu G.E., (2003). A quantitative methodology for

indexing environmental sensitivity and pollution potential; GIEES, University of North Carolina, Charlotte, North Carolina, USA; 2003.

2. Environmental Vulnerability Index (EVI), (2004). Project; Final report; SOPAC &

UNEP.

3. Environmental Sensitivity Index Guidelines, Version 3.0. (2002). National Oceanic and Atmospheric Administration; Seattle, Washington.

4. Bae, S., Inyang, H.I. (2006): Overview of what the Visual Grid can do for

visualization in our area. A Quantitative Methodology for Indexing Environmental Sensitivity and Pollution Potential for NC. Global Institute for Energy and Environmental Systems. UNC Charlotte.

5. Zakon o varstvu okolja (ZVO-1). Ur.l. RS, št. 41/2004. Spremembe: Ur.l. RS, št.

17/2006, 20/2006, 28/2006 Skl.US: U-I-51/06-5, 39/2006-UPB1, 49/2006-ZMetD, 66/2006 Odl.US: U-I-51/06-10, 112/2006 Odl.US: U-I-40/06-10, 33/2007-ZPNačrt, 57/2008-ZFO-1A, 70/2008, 108/2009.

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