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Integrated ESIA GreeceAnnex 8.1 - Air Dispersion Modeling

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Project Title: Trans Adriatic Pipeline – TAP GPL00-ASP-642-Y-TAE-0071Rev.: 00 Document Title:

Integrated ESIA Greece Annex 8.1 - Air Dispersion Modelling

TABLE OF CONTENTS

1 AIR DISPERSION MODELLING 4

1.1 Study Overview 4

2 AIR QUALITY BASELINE 7

2.1 Greek Ambient Air Quality Standards 7

2.2 Ambient Air Quality Condition in the Study Areas 7

2.3 Modelling Areas and Potential Receptor Locations 9

3 MODELLING SETUP 13

3.1 Meteorology and characteristic weather types 13

3.2 The Dispersion modelling tool 18 3.2.1 Emission Scenarios 19

4 MODELLING RESULTS 21

4.1 Model Results Interpretation 21

4.2 Results 22 4.2.1 Results of Model Run for GCS00 (Kipoi) for 20 bcm/year 22 4.2.2 Results of Model Run for GCS00 (Kipoi) for 10 bcm/year 26 4.2.3 Results of Model Run for GCS01 (Serres) 28

4.3 Evaluation of Results 33 4.3.1 Comparison with Air Quality Limits 33 4.3.2 Contribution to the Ambient Air Concentrations 34 4.3.3 Impact on Residential Receptors 35 4.3.4 Impact on Natura 2000 Areas 35

5 CONCLUSIONS 37

LIST OF TABLES

Table 1-1 Model simulation scenarios 5 Table 2-1 EU and Greek Air Quality Standards for NOx and CO 7 Table 2-2 Geographical coordinates of Emission Sources for GCS00 (Kipoi) 10 Table 2-3 Geographical coordinates of Emission Sources for GCS01 (Serres) 10 Table 3-1 Characteristic weather types and their frequency within a year in the area of Kipoi

(GCS00) 14 Table 3-2 Characteristic weather types and their frequency within a year in the area of

Serres (GCS01) 14 Table 3-3 Typical meteorological conditions of the 7 characteristic weather types in the area

of Kipoi 14


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Table 3-4 Typical meteorological conditions of the 8 characteristic weather types in the area of Serres 15

Table 3-5 Kipoi (GCS00) Emission Source Parameters for each Turbine/Stack 19 Table 3-6 Kipoi (GCS00) Emission Rates and Composition 19 Table 3-7 Serres (GCS01) Emission Source Parameters for each Turbine/Stack 20 Table 3-8 Serres (GCS01) Emission Rates and Composition 20 Table 4-1 Maximum values of hourly average NO2 concentrations per weather type for

GCS00 23 Table 4-2 Calculated maximum ground-level concentrations for NO2 and CO and at the

residential receptors in the study area for Kipoi 23 Table 4-3 Maximum values of hourly average NOx concentrations per weather type

(operation 10 bcm/year) 27 Table 4-4 Calculated maximum ground level concentrations for NO2 and CO and the

residential receptors in the study area for Kipoi (operations 10 bcm/year) 27 Table 4-5 Maximum values of hourly average NO2 concentrations per weather type for 20

bcm/year 28 Table 4-6 Calculated maximum ground-level concentrations for NO2, CO and at the

residential receptors in the study area for Serres 28 Table 4-7 Comparison of the modeling for the maximal affected settlements with limit values35

LIST OF FIGURES

Figure 2-1 Ambient Air Sampling Locations near Kipoi 8 Figure 2-2 Ambient Air Sampling Locations near Serres 9 Figure 2-3 Topographical map of the Kipoi study area of size 30 30 km2, the settlements and

GCS00 (in the centre) 11 Figure 2-4 Topographical map of the Serres study area of size 30 30 km²,the settlements

and GCS01 (in the centre) 12 Figure 3-1 Wind rose diagram at the location of Kipoi (GCS00) 16 Figure 3-2 Wind rose diagram at the location of Serres (GCS01) 17 Figure 4-1 Maximum hourly ground-level concentrations of NO2 for the 7 weather types (WT)

in the case of GCS00 (Kipoi) 24 Figure 4-2 Total average annual NO2 concentration contours (in g/m3) for GCS00 (Kipoi) 25 Figure 4-3 Maximum hourly ground-level concentrations of CO for the 7 weather types (WT)

in the case of GCS00 (Kipoi) 26 Figure 4-4 Maximum hourly ground-level concentrations of NO2for the 8 weather types (WT)

in the case of GCS01 (Serres) 31 Figure 4-5 Total average annual NO2 concentration contours (in g/m3) for GCS01 (Serres) 32 Figure 4-6 Maximum hourly ground-level concentrations of CO for the 8 weather types (WT)

in the case of GCS01 (Serres) 33


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1 AIR DISPERSION MODELLING

1.1 Study Overview

The present air dispersion modelling study was carried out by the Environmental Research

Laboratory (EREL) of the National Centre for Scientific Research “Demokritos” for the purpose of

the Environmental and Social Impact Assessment of the Greek Section of the Trans -Adriatic

Pipeline (TAP).

The air dispersion modelling study quantifies and evaluates the ground-level concentrations of

gas pollutants, generated by the operation of the planned “Gas Compressor Station 00” and “Gas

Compressor Station 01”, referred to as “GCS00” and ”GCS01” here after.

Dedicated modelling was carried out for GCS00 and GCS01 for the operation phase of the

Project. During the operation phase, the Compressor Stations are the Project’s only sources of

atmospheric emissions. The modelling was performed for the gaseous pollutants Nitrogen Oxides

(NOX) and Carbon Monoxide (CO) being the sources’ relevant substances affecting the ambient

air quality given the combustion of natural gas. Emission of particulates or organic compounds is

not to be expected from natural gas combustion.

Both compressor stations are located in Greece. The GCS00 is located in the region of Eastern

Thrace and Macedonia, near the border with Turkey, approximately 3 km west of the town of

Kipoi.(see Figure 2-3) The GCS01 is located in the region of Central Macedonia 7km south of

Serres town.(see Figure 2-4).

A number of alternative locations and pipeline gas flow capacities have been investigated during

development of the TAP Project. Table 1-1 provides the finally selected options to which the

ESIA refers.


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Table 1-1 Model simulation scenarios Scenario Emission sources Overall power and pipeline

capacity

GCS00 (Kipoi) 2 x 15 MW(ISO class) Gas Turbines

30 MW; 10 bcm/year

GCS00 (Kipoi) 5 x 15 MW(ISO class) Gas Turbines

75 MW; 20 bcm/year

GCS01(Serres) 4 x 25 MW(ISO class) Gas Turbines

100 MW; 20 bcm/year

Source: Demokritos(2013)

A natural gas flow of 20 bcm/year is the pipelines full capacity in which case all turbines will

operate at full load. For GCS00 also a scenario with 10 bcm/year gas flow was modelled which

represents half load.

For each station one additional turbine will be installed as backup. Since this turbine operates

only alternatively, the backup turbine had not to be considered in the modelling which was based

on the maximum overall power of the stations.

Parameters of the sources and stacks are provided in the tables following Table 3-5(i.e. stack

height and diameter, flue gas temperature and velocity.

The GCS00 and GCS01 atmospheric emissions will be generated by gas turbines fuelled with

natural gas according to EASEE (European Association for the Streamlining of Energy

Exchange-gas) standard. For such gas, emission of particulates or SO2 is negligible. Hence,

according to the European IPPC Bureau Best Available Technologies Reference document

(BREF) on large combustion plants, CO and NOx are the only air quality pollutants emitted and

consequently considered in the modelling studies provided herewith. Ground-level concentrations

of NOx, (conservatively considered to entirely being NO2), and CO have been modelled over a

30 x 30 km2study area, centred on each gas compressor station location for the modelling study.

The air dispersion simulations have been performed with the MM5-HYSPLIT modelling system.

Specifically, the prognostic meteorological model ΜΜ51was used for the calculation of the 3-

dimensional meteorological data in the area of interest. The HYSPLIT2 Model developed by the

1MM5 - Mesoscale Model 5 developed by Pennsylvania State University, National Centre for Atmospheric Research, USA, v. 3.7.2 2HYSPLIT - Hybrid Single Particle Lagrangian Integrated Trajectory model; NOAA Air Resources Laboratory http://www.arl.noaa.gov/HYSPLIT_info.php


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US National Oceanic and Atmospheric Administration (NOAA) was used for the dispersion

calculation.

The following sections contain a detailed description of the environmental baseline, the modelling

system used, simulation settings, meteorological and emission data input, and the modelling

results. The ground-level concentrations obtained from the modelling, including consideration of

ambient background levels and potential receivers (populated places, Natura 2000 areas), are

compared against European air quality standards (2008/50/EC3), which are adopted by Greek

legislation.

3 Directive 2008/50/EC on ambient air quality and cleaner air for Europe, European Parliament and Council, 21 May 2008


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2 AIR QUALITY BASELINE

2.1 Greek Ambient Air Quality Standards

Greece as an EU Member State has adopted the EU Directive 2008/50/EC on ambient air quality

by the Joint Ministerial Decision (JMD) 14122/549/E.103/2011 (Gov. Gaz. 488/B/30.03.11). This

legislation sets forth air quality limit values for NOX, SO2, PM10, PM2.5, Benzene, Pb, O3, and CO.

As mentioned before, only emissions of NOx and CO are relevant as pollutants emitted from the

Project’s sources. The air quality standards for the air pollutants considered in this study,

therefore, are those for NOx (as NO2) and CO which entered into force on January 1, 2010.They

are presented in Table 2-1.

Table 2-1 EU and Greek Air Quality Standards for NOx and CO Pollutant Averaging Period Limit value

Nitrogen dioxide (NO2) One hour 200 μg/m3 for the protection of human health, not to be exceeded more than 18 times in a calendar year

Calendar year 40 μg/m3for the protection of human health Oxides of Nitrogen (NOx) Calendar year 30 µg/m³ for the protection of vegetation Carbon Monoxide (CO) (1) maximum daily 8-hour mean 10 mg/m³ (10,000 µg/m³)for the protection of

human health (1) Footnote in 2008/50/EC: The maximum daily 8-hour mean concentration will be selected by examining eight hour running averages, calculated from hourly data and updated each hour. Each eight hour average so calculated will be assigned to the day on which it ends i.e. the first calculation period for any one day will be the period from 17:00 on the previous day to 01:00 on that day; the last calculation period for any one day will be the period from 16:00 to 24:00 on that day.

2.2 Ambient Air Quality Condition in the Study Areas

At the two areas of interest in this study, measurements of average NOx concentrations (mainly

NO2) were available for assessing the air quality background. Concentration values of CO were

not measured. As indication of the ambient CO concentration levels for the areas of eastern

Thraki and Macedonia could be taken from reanalysis of ECMWF model monthly mean data4.

Those data showed monthly mean CO values between 0.14 mg/m3 and 0.23 mg/m3 and annual

means of approximately 0.18 mg/m3 (reference year 2007).

4http://gems.ecmwf.int/d/summary/gems/gems/integrated/reanalysis/gems_monthly_fields!Carbon%20monoxide!Europe!Surface!gem

s!od!enfo!gems_monthly_fields!200711!interval_date/.


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Kipoi

Field survey

According to Annex 6.6.5 of the Environmental and Social Impact Assessment, field survey

campaigns were carried out in the area of Kipoi, at 1.5 km radius from the position of GCS00

during two periods in November-December 2012 and February 2013 (Figure 2-1). The scope was

to establish the ambient air quality conditions in the area. A map with sampling point locations is

provided in Section 6 – 6.2.6 and in the relevant Annex 6.6.5. The NOx measurements revealed

that at Kipoi GCS00 the average NOx values (during the sampling period) were 7.5±2.5 μg/m3.

These concentration values for NOx are characterizing a rural background without indication for

an impact from major sources and are considered to be very low.

Figure 2-1 Ambient Air Sampling Locations near Kipoi

Source: Demokritos (2013)

Serres

Field survey

Similarly, a sampling campaign was carried out during November-December 2012 in the area of

Serres, at 2.0 km radius from the position of GCS01 (see map in Section/ Annex 6.6.5). In the

area of Serres, the average NOx values (during the sampling period) were measured to be

15.1±5.1 μg/m3. The report has deduced that levels for NOx are low in the sampling area,


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indicating a lack of major emission sources like intense vehicle circulation or industries in the

local area. The air quality in the area is considered to be good. According to Directive

2008/50/EC and the Greek Legislation, the NO2 and NOx limits were not exceeded. Details of the

exact location of the sampling points can be found in Annex 6.6.5.

Figure 2-2 Ambient Air Sampling Locations near Serres


2.3 Modelling Areas and Potential Receptor Locations

The geographical coordinates of the emission sources of the compressor stations GCS00 and

GCS01 are shown in Table 2-2 and Table 2-3 respectively.

The study areas for the atmospheric modelling were defined in such way that the compressor

stations were situated in the centre of the study area. Figure 2-1 depicts the domain of Kipoi, with

GCS00. Figure 2-2 shows the domain of Serres with GCS01. The areal extent of the study area

was set to 30 km 30 km in order to include all the neighbouring settlements and protected

areas. The original topographical data used was of 100 m resolution. The topography of the


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areas revealed a rather smooth terrain around the stations in both cases, Kipoi and Serres

respectively.

Table 2-2 Geographical coordinates of Emission Sources for GCS00 (Kipoi) Source X (GGR 587) Y (GGR587) Longitude (deg.)(λ) Latitude (deg.)(φ)

Stack 1 – 15 MW ISO-class

692402.65 4535803 26.27304127840 40.97109991400

Stack 2 - 15 MW ISO- class

692450.4053 4535787 26.27364895630 40.97095961430

Stack 3 -15- MW ISO- class

692472.97 4535780 26.27388733240 40.97089805900

Stack 4- 15 MW ISO- class

692517.10 4535764 26.27449500670 40.97075775470


692542.78 4535758 26.27474516680 40.97070528000


692593.74 4535742 26.27535283760 40.97056497120


Table 2-3 Geographical coordinates of Emission Sources for GCS01 (Serres) Source X (GGR 587) Y (GGR 587) Longitude (deg.) λ) Latitude (deg.)( φ)

Stack 1 – 25 MW ISO-class (large)

463420.03 4541716.50 23.56488051540 41.02583794870

Stack 2 - 25 MW ISO- class (large)

463442.24 4541717.49 23.56514463790 41.02584786360


463496.21 4541718.80 23.56578651710 41.02586208420


463518.95 4541719.46 23.56605696350 41.02586904810


463572.79 4541720.45 23.56669731580 41.02588037530


Potential sensitive receptors, i.e. populated places and protected areas, in the airshed of the

compressor stations were identified for evaluation of the modelled ground-level concentrations at

receptor locations. Towns and villages contained within a radius of approximately 15 km from the

compressor station locations were identified. Within the GCS00 and GCS01 modelling study

areas18 and 50 settlements were identified, respectively (cf. Figure 2-3 and Figure 2-4). For

GCS00, five of the settlements are located in Turkey which have been included in order to enable

evaluation of potential transboundary impacts.


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It must be mentioned that as it is presented in the Table 4-2 the GCS00 is not anticipated to

cause any adverse impact in the Natura 2000 area because the distance between this area

(Dasos Dadias – Soufli) and the GSC00 is approximately 3.6 km.

Figure 2-3 Topographical map of the Kipoi study area of size 30 30 km2, the settlements and GCS00 (in the centre)



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Figure 2-4 Topographical map of the Serres study area of size 30 30 km²,the settlements and GCS01 (in the centre)



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3 MODELLING SETUP

3.1 Meteorology and characteristic weather types

Atmospheric dispersion models use as input data meteorological variables such as wind speed

and direction, temperature, category of atmospheric stability, mixing layer height etc. The more

complex models (like HYSPLIT, the model used in this study) use 3-dimensional meteorological

fields as input. For the current study, meteorological data (vertical distribution of wind speed and

direction, temperature, mixing layer height, humidity, precipitation, cloud cover etc) were

extracted from the US National Centre’s for Environmental Prediction (NCEP / USA) Global

Forecasting System (GFS) available on a 6-hour temporal resolution from a planetary model of 1

degree horizontal resolution.

To calculate the average levels and the maximum values of the pollutant concentrations in the

atmosphere on an annual, daily and hourly basis, the procedure of identifying the characteristic

weather types in the area of interest was followed. The prevailing meteorological conditions, or in

other words characteristic weather types, were obtained by applying the methodology of Sfetsos

et al. (2005)5. The specific methodology was applied to the large scale GFS meteorological data

referenced above, covering a two year period (2010-2011). The analysis revealed the prevailing

weather conditions in the study areas of Kipoi and Serres and the corresponding frequency of

occurrence (in percentage) per year. Each such typical weather condition was assigned a

characteristic or else typical day (24-hour).

The analysis showed that the study area f or Kipoi could be characterised by in total seven (7)

typical weather types (Table 3-1), while it were eight (8) for Serres (Table 3-2). Table 3-3 and

Table 3-4 summarise the meteorological conditions from the planetary scale model characterizing

the weather of a typical day in the two regions. Data for specific humidity and mixing layer height

are only available for noon (12:00).

5Sfetsos, D. Vlachogiannis, N. Gounaris, and A. K. Stubos, (2005). On the identification of representative samples from large data sets with application to synoptic climatology, Theor. Appl. Climatol. 82, 177–182.


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Table 3-1 Characteristic weather types and their frequency within a year in the area of Kipoi (GCS00)

Typical weather type ID Frequency of occurrence in a year (%) Number of days in a year

1 10.4 38

2 11.5 42

3 11 40

4 9.9 36

5 19.8 72

6 15.4 56

7 22 80 Source: Demokritos (2013)

Table 3-2 Characteristic weather types and their frequency within a year in the area of Serres (GCS01)

Typical weather type ID Frequency of occurrence in a year (%) Number of days in a year

1 10.5 38

2 25.8 94

3 8.9 32

4 8.7 32

5 17.6 64

6 4.9 18

7 18.1 66

8 5.5 20 Source: Demokritos (2013)

Table 3-3 Typical meteorological conditions of the 7 characteristic weather types in the area of Kipoi

Kipoi (GCS00) Typical weather type

Temperature (°C)

(at 2 m agl)6

Wind speed (m/s)

(at 10 m agl)

Wind direction (deg.)

(at 10 m agl)

Specific humidity (g/kg7)

(at 2 m agl)

Mixing layer

(height agl) (06:00)

1 18 4.7 21 n.a. (not available) n.a.

2 104 1.8 20 n.a. n.a.

3 7 6.3 21 n.a. n.a.

4 9 6.2 21 n.a. n.a.

5 11 1.3 203 n.a. n.a.

6 2 3.0 211 n.a. n.a.

7 0 6.8 21 n.a. n.a.

(12:00)

1 18 1.5 4.8 9.8 291

2 16 3.2 218 7.3 1356

3 9 3.7 18 6.1 170

4 15 3.6 18 6.6 1406

5 14 7.8 211 7.4 664

6 7 1.4 232 4.4 508

6agl - above ground level 7Specific humidity provided as gram water per kilogram of air


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Kipoi (GCS00) Typical weather type

Temperature (°C)

(at 2 m agl)6

Wind speed (m/s)

(at 10 m agl)


(at 10 m agl)


(at 2 m agl)

Mixing layer

(height agl) 7 5 4.6 20 3.6 523

(18:00)


2 11 1.7 289 n.a. n.a.

3 8 5.3 6.5 n.a. n.a.

4 9 5.2 6.2 n.a. n.a.

5 12 4.2 229 n.a. n.a.

6 3 2.1 331 n.a. n.a.

7 1 5.9 8.6 n.a. n.a.

(24:00)

1 22 4.9 9.3 n.a. (not available) n.a.

2 14 2.2 355 n.a. n.a.

3 10 6.3 12 n.a. n.a.

4 11 6.3 12 n.a. n.a.

5 14 1.4 246 n.a. n.a.

6 4 3.3 3.6 n.a. n.a.

7 1 6.9 13 n.a. n.a.


Table 3-4 Typical meteorological conditions of the 8 characteristic weather types in the area of Serres

Serres (GCS01)

Typical weather type

Temperature (°C)

(at 2 magl)8

Wind speed (m/s)

(at 10 magl)


(at 10 magl)


(at 2m agl)

Mixing layer

(height agl)

(06:00)


2 2 0.5 180 n.a. n.a.

3 9 0.9 101 n.a. n.a.

4 21 2.5 247 n.a. n.a.

5 11 0.2 210 n.a. n.a.

6 9 0.7 329 n.a. n.a.

7 0 0.7 300 n.a. n.a.

8 9 8.0 313 n.a. n.a.

(12:00)

1 17 1.0 46 5.7 1852

2 16 0.7 280 3.6 580

3 14 2.5 276 6.7 712

4 19 0.5 213 11.6 19

5 19 2.6 91 7.7 1232

6 18 3.6 120 8.3 449

7 7 0.6 252 3.4 597

8agl - above ground level

9 Specific humidity provided as gram water per kilogram of air


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Serres (GCS01)

Typical weather type

Temperature (°C)

(at 2 magl)8

Wind speed (m/s)

(at 10 magl)


(at 10 magl)


(at 2m agl)

Mixing layer

(height agl)

8 15 7.4 331 4.3 1852

(18:00)


2 8 1.6 269 n.a. n.a.

3 11 4.1 319 n.a. n.a.

4 21 2.0 274 n.a. n.a.

5 12 3.6 103 n.a. n.a.

6 14 3.6 122 n.a. n.a.

7 1 0.8 99 n.a. n.a.

8 8 3.6 293 n.a. n.a.

(24:00)


2 2 0.8 135 n.a. n.a.

3 7 3.6 325 n.a. n.a.

4 28 2.1 102 n.a. n.a.

5 8 0.9 293 n.a. n.a.

6 14 3.9 127 n.a. n.a.

7 0 0.4 276 n.a. n.a.

8 4 1.9 308 n.a. n.a. Source: Demokritos(2013)

Figure 3-1 Wind rose diagram at the location of Kipoi (GCS00)

Note: 1 knot = 0.51444 m/s



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Figure 3-2 Wind rose diagram at the location of Serres (GCS01)

Note: 1 knot = 0.51444 m/s


The 3-dimensional meteorological fields required as input to the Hysplit dispersion model were

produced for the typical days by means of the PSU/NCAR mesoscale model, known as MM5.

MM5 is a limited-area, non-hydrostatic, terrain-following sigma-coordinate model designed to

simulate or predict mesoscale atmospheric circulation. The model is supported by several pre-

and post-processing programs and has been used extensively in meteorological prognosis and

research studies. The vegetation / land use data for use with MM5 were updated using recent

information for the compressor station regions. The MM5 model runs were performed with the

Grell option (simple cloud scheme), the Rapid Radiative Transfer Model (RRTM) longwave

scheme and the Five-Layer Soil model option. In the vertical, the MM5 domain was based on 29

full levels to the top at 100 mb10.

10 References: D. Vlachogiannis, A. Sfetsos, N. Gounaris and A. Papadopoulos, Computational study of the effects of photovoltaic panels on meteorological patterns during a hot weather event in an urban environment, International Journal of Environment and Pollution, Vol. 50, 460-468, 2012. D. Vlachogiannis, A. Sfetsos, N. Gounaris and A. Papadopoulos, Computational study of the effects of induced land use changes on meteorological patterns during hot weather events in an urban environment, 14th International conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, KOS Island (Greece) 2-6 October 2011. S. Andronopoulos, A. Sfetsos, D. Vlachogiannis, A. Yiotis and N. Gounaris, Application of adjoint CMAQ chemical transport model in the Athens Greater Area: sensitivities study on ozone concentrations, accepted in IJEP (International Journal of Environmental Pollution), 47, Nos. 1/2/3/4, pp. 193-206, 2011. D. Vlachogiannis, a. Sfetsos, A. Papadopoulos and N. Gounaris, The impact of land-use modification scenarios on the air-quality of an urban region during ozone episodes using the MM5-CMAQ modelling system, 13TH International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Paris, France, June 1-4, 2010.


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The MM5 model calculated the 3-dimensional meteorological fields of the region of interest, in a

horizontal and temporal resolution of 3 km × 3 km and 1-hour, respectively. Figure 3-1 and Figure

3-2, depict the wind rose diagrams calculated at the locations of the two compressor stations.

The predominant wind directions at the position of GCS00 are N and N-NE. The winds from

these directions are light to strong, as wind speeds can reach values higher than 11.3 m/s (22

knots). Light to strong winds from the SW and S-SW directions occur in the area but less

frequently. Calm winds are rare and amount to 1.3%.

For Serres (GCS01), the winds from W to NW as well as from the E and E-SE are predominant.

The winds are light to moderate from these directions. Stronger winds occur from the NW and N-

NW directions. The percentage of calms is approximately 10% in the area.

3.2 The Dispersion modelling tool

As already mentioned, the dispersion calculations were performed with the Hysplit (Hybrid Single

Particle Lagrangian Integrated Trajectory) Model. The HYSPLIT model11 is the newest version of

a complete system for computing simple air parcel trajectories to complex dispersion and

deposition simulations. The model calculation method is a hybrid between the Lagrangian

approach, which uses a moving frame of reference as the air parcels move from their initial

location, and the Eulerian approach, which uses a fixed three-dimensional grid as a frame of

reference. In the model, advection and diffusion calculations are made in a Lagrangian

framework following the transport of the air parcel, while pollutant concentrations are calculated

on a fixed grid.

The model is designed to support a wide range of simulations related to the atmospheric

transport and dispersion of pollutants, including their deposition onto the Earth’s surface.

11HYSPLIT, http://ready.arl.noaa.gov/HYSPLIT.php.


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3.2.1 Emission Scenarios

The modelling scenarios for GCS00 and GCS01 have been summarised in Table 1-1.The station

GCS00 in Kipoi will be equipped with a total of 5+1 gas turbines (5 of 6 in operation) each with an

installed power of 15 MW (ISO-class). This configuration represents the case when the

compressor station will be operating at full load (20 bcm/year). In the case of half load, i.e at 10

bcm/year, the configuration set up will include 2+1 turbines. Each turbine will be equipped with an

own stack.

Table 3-5 provides stack dimension and flue gas information for the emission sources of GCS00.

The operation of the station is set at 8,760 hours per year in the modelling.

Table 3-5 Kipoi (GCS00) Emission Source Parameters for each Turbine/Stack Source Gas Turbine

Type Stack

Height [m] Stack

Diameter [m] Flue Gas Temp.

[°C] Flue Gas

Velocity [m/s]

5 + 1 GCS01 – Gas Turbine

15 MW – ISO Class

30 3 505 15.9

Note: Operation of more than one15 MW ISO class gas turbines results in a thermal input exceeding the 50 MW threshold for large combustion plants. Therefore, the compressor station complex will fall under the EU Directive on Industrial Emissions (Pollution Prevention and Control) (2010/75/EC). Source: Demokritos (2013)

Table 3-6 presents GCS00 atmospheric emissions rates and composition used as input in the air

dispersion modelling studies. The shown data are representing a single stack.

Table 3-6 Kipoi (GCS00) Emission Rates and Composition Source Normalised Flow Rate

(Dry - 15% O2) [Nm³/h] Concentration [mg/Nm3] Emission rate [kg/h]

NOx CO NOx CO

Gas turbine 15 MW 149,172 50 100 7.1 14.2

The NOx and CO emission concentrations meet the requirements of 2010/75/EC for gas turbines (Annex V, Part 2, No 6) Source: Demokritos (2013)

In Serres, in the case of GCS01, there will be 4+1 gas turbines (4 of 5 in operation) each with an

installed power of 25 MW (ISO-class) when the compressor station will be operating at full load

i.e. 20 bcm/yr. Table 3-7 provides the stack dimension and flue gas information for the emissions

sources of GCS01.


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Table 3-7 Serres (GCS01) Emission Source Parameters for each Turbine/Stack Source Gas Turbine

Type Stack

Height [m] Stack

Diameter [m] Flue Gas Temp.

[C] Flue Gas

Velocity [m/s]

4 + 1 GCS01 – Gas Turbine

25 MW – ISO Class

30 3.8 543 15.9

Note: Operation of more than one15 MW ISO class gas turbines results in a thermal input exceeding the 50 MW threshold for large combustion plants. Therefore, the compressor station complex will fall under the EU Directive on Industrial Emissions (Pollution Prevention and Control) (2010/75/EC). Source: Demokritos (2013)

Table 3-8 presents GCS01 atmospheric emissions rates and composition used as input in the air

dispersion modelling studies. The shown data are representing a single stack.

Table 3-8 Serres (GCS01) Emission Rates and Composition Source Normalised Flow Rate

(Dry - 15% O2) [Nm³/h] Concentration [mg/Nm3] Emission rate [kg/h]

NOx CO NOx CO

Gas turbine 25 MW 239,803 50 100 11.4 22.8

The NOx and CO concentrations meet the requirements of 2010/75/EC for gas turbines (Annex V, Part 2, No 6) Source: Demokritos (2013)


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4 MODELLING RESULTS

4.1 Model Results Interpretation

The air dispersion modelling generated results for the surface concentrations of NO2 and CO due

to the emissions from the compressor stations GCS00 and GCS01 in the areas of Kipoi (at two

alternative positions) and Serres, respectively. It was assumed that the stations operate

continuously throughout the entire year without a standstill. Therefore, the results represent the

maximum case scenario of concentration values in the study areas.

The concentrations of NO2 were calculated for hourly and annual averages to allow for

comparison of the modelled results with the respective air quality limits as set forth by the

legislation (MD 14122/549/E.103/2011 “Measures to improve air quality in compliance with the

provisions of Directive 2008/50/EC "on the air quality and cleaner air for Europe" by the

European Parliament and Council of the European Union of 21 May 2008”). According to this

regulation, the air quality limit for NO2 for averaging period of 1 hour is set at 200 μg/m3 not to be

exceeded more than 18 times in any calendar year. For the annual average, the respective limit

is 40 μg/m3 defined for protection of human health. For protection of vegetation the annual

average for NOx is 30 µg/m³, which includes besides NO2 also NO. The CO values were

calculated as maximum daily 8 hour running mean concentrations for comparison with the

respective air quality limit of 10 mg/m3.

For the interpretation of the results the following aspects of the modelling approach should be

noted:

The modelling has assumed continuous operation during a whole simulation year;

The air dispersion simulation was performed without the inclusion of photochemical

reactions, which could potentially reduce the concentrations of NO2 and CO in the

atmosphere, to ensure that the maximum possible values in the study area were

determined;

The simulated concentration values were calculated for NOx emissions taken as NO2

instead of a mixture of NO2 with NO. Thus, the results can be compared with NO2and NOx

concentration limits set by the European Directive 2008/50 and respective Greek

legislation. But in reality only a part of NOx is emitted as NO2 or converts to NO2 during

dispersion which is depending on different factors (e.g. solar radiation, air temperature,


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atmospheric concentration of ozone and hydrocarbons). By taking all NOx emissions as

being NO2, the simulated NO2 concentrations have been overestimated.

The background air quality concentrations of the region have not been included in the modelling

study; therefore, the modelled concentration values of the pollutants refer only to those

contributed by the compressor stations. The existing ambient background levels were reported in

a previous section and are considered in the conclusions section below.

4.2 Results

In this section, the detailed modelling results for the full load operation (20 bcm/year) and the

selected locations for GCS00 and GCS01 are provided. The paragraphs of the various runs

hereafter have a common structure as follows:

A table showing the maximum hourly levels for NO2 for the various typical weather types;

A table showing the overall maximum levels for NO2 and CO in the entire study area and

at the residential areas;

Figures showing the maps for the above parameters

Additionally, tables of the modelling results for GCS00 at 10 bcm/year operation are also

provided.

4.2.1 Results of Model Run for GCS00 (Kipoi) for 20 bcm/year

Table 4-1 provides the hourly maximum of the calculated NO2 concentration per weather type of

the study area (as mentioned before, the calculations were performed for NOx and conservatively

is interpreted as NO2). Table 4-3 shows the maximum average concentration values of NO2 and

CO over the domain. The table also summarises the average NO2 maximum hourly and annual

concentrations and the CO maximum 8-hour mean values calculated for the residential receptors

in the area

Figure 4-1 and


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Figure 4-2 show maps of the maximum hourly and the annual average concentrations of NO2,

calculated by HYSPLIT from the 7 identified weather types. Figure 4-3 depicts the 8-hour

maximum CO concentrations.

Table 4-1 Maximum values of hourly average NO2 concentrations per weather type for GCS00

GCS00 KIPOI

Weather type Maximum hourly NO2 concentration (μg/m3)

1 51.0

2 42.0

3 48.4

4 49.7

5 41.3

6 89.0

7 49.5 Source: Demokritos (2013

Table 4-2 Calculated maximum ground-level concentrations for NO2 and CO and at the residential receptors in the study area for Kipoi

GCS00 KIPOI

Distance from GCO00 (km)

Maximum hourly NO2 concentration (μg/m3)

Annual average NΟ2 concentration (μg/m3)

Maximum 8-h mean CO concentration (μg/m3)

Legal limit value 200 40 10,000

Overall Maximum 89 3.7 3.2

No. Place of residence

GREEK PART

1 FERES 13.3 16.25 0.60 0.00

2 GEMISTI 3.83 0.69 0.00 0.00

3 KIPOI 2.68 0.54 0.00 0.01

4 LAGINA 12.15 33.28 1.86 0.15

5 LEFKIMI 9.40 3.52 0.02 0.00

6 LIRA 10.70 8.62 0.12 0.10

7 PEPLOS 2.81 10.10 0.62

8 PILEA 15.62 8.15 0.24 0.14

9 PROVATONAS 6.42 0.64 0.01 0.21

10 TAVRI 2.97 18.87 0.25 0.08

11 THYMARIA 3.04 7.76 0.13 0.01

12 TIHERON 5.94 16.44 0.75 0.82

13 TRIFILI 6.70 29.51 0.72 0.00

TURKISH PART

1 AHIR 11.33 0.44 0.00 0.00

2 BALABANCIK 11.96 6.62 0.07 0.06

3 IPSALA 9.89 0.00 0.00 0.32


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GCS00 KIPOI

Distance from GCO00 (km)

Maximum hourly NO2 concentration (μg/m3)

Annual average NΟ2 concentration (μg/m3)

Maximum 8-h mean CO concentration (μg/m3)

Legal limit value 200 40 10,000

Overall Maximum 89 3.7 3.2

No. Place of residence

4 SARICAALI 8.09 0.64 0.00 0.12

5 TURPCULAR 13.06 0.16 0.00 0.00 Source: Demokritos (2013)

Figure 4-1 Maximum hourly ground-level concentrations of NO2 for the 7 weather types (WT) in the case of GCS00 (Kipoi)

Black dots indicate residential areas Source: Demokritos (2013)


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Figure 4-2 Total average annual NO2 concentration contours (in g/m3) for GCS00 (Kipoi)



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Figure 4-3 Maximum hourly ground-level concentrations of CO for the 7 weather types (WT) in the case of GCS00 (Kipoi)


4.2.2 Results of Model Run for GCS00 (Kipoi) for 10 bcm/year

In analogy to Table 4-1 and Table 4-2, Table 4-3 and Table 4-4 summarize the modelling results

for the GSC00 for the 10 bcm/year case. This means that only two (2) gas turbines will be in

operation. The topographic shapes in the figures are similar to those provided for the 20

bcm/year only with reduced concentration levels.


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Table 4-3 Maximum values of hourly average NOx concentrations per weather type (operation 10 bcm/year)

GCS00 KIPOI

Weather types Maximum hourly) NO2 concentration (μg/m3) 1 21.07

2 20.93

3 26.34

4 24.93

5 19.77

6 49.33

7 24.13

Source: Demokritos Table 4-4 Calculated maximum ground level concentrations for NO2 and CO and the

residential receptors in the study area for Kipoi (operations 10 bcm/year) GCS00 KIPOI

Distance from GCS00

(km)

Maximum hourly (mean)

NO2concentration (μg/m3)

Annual average NΟ2 concentration

(μg/m3)

Maximum 8-h mean CO concentration

(μg/m3)

Nu. Legal Limit Value

(limit 200 μg/m3)

(limit 40 μg/m3)

(limit 10000 μg/m3)

Overall Maximum

49.33 1.63 1.58

Place of residence

GREEK PART

1 FERES 13.29 9.54 0.20 0.33

2 GEMISTI 3.83 0.28 0.00 0.00

3 KIPOI 2.68 0.00 0.00 0.00

4 LAGINA 12.15 4.70 0.09 0.06

5 LEFKIMI 9.40 1.78 0.01 0.00

6 LIRA 10.70 2.29 0.04 0.02

7 PEPLOS 2.81 16.21 0.77 0.69

8 PILEA 15.62 4.37 0.14 0.07

9 PROVATONAS 6.24 1.13 0.02 0.02

10 TAVRI 2.97 14.49 0.12 0.04

11 THYMARIA 3.04 2.12 0.03 0.02

12 TIHERON 5.94 8.01 0.25 0.16

13 TRIFILI 6.70 11.40 0.25 0.28

TURKISH PART

1 AHIR 11.33 0.12 0.00 0.00

2 BALABANCIK 11.96 2.70 0.03 0.04

3 IPSALA 9.89 0.00 0.00 0.00

4 SARICAALI 8.09 0.26 0.00 0.00

5 TURPCULAR 13.06 0.00 0.00 0.00

Source: Demokritos


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4.2.3 Results of Model Run for GCS01 (Serres)

Table 4-5 provides the hourly maximum of the calculated NO2 concentration per weather type of

the study area (as mentioned before, the calculations were performed for NOx and conservatively

is interpreted as NO2). Table 4-7 shows the maximum average concentration values of NO2 and

CO over the entire study area. The table also summarises the average NO2 maximum hourly and

annual concentrations and the CO maximum 8-hour mean values calculated for the residential

receptors in the area. Figure 4-4 and Figure 4-5 show maps of the maximum hourly and the

annual average concentrations of NO2, calculated by HYSPLIT from the 8 identified weather

types. Figure 4-6 depicts the 8-hour maximum CO concentrations.

Table 4-5 Maximum values of hourly average NO2 concentrations per weather type for 20 bcm/year

GCS01 SERRES

Weather types Maximum hourly NO2 concentration (μg/m3)

1 30

2 71.18

3 81.35

4 105.70

5 107.9

6 68.28

7 141.80

8 75.47 Source: Demokritos (2013)

Table 4-6 Calculated maximum ground-level concentrations for NO2, CO and at the residential receptors in the study area for Serres

GCS01 SERRES

Distance from GCO01

(km)

Maximum hourly NO2concentratio

n (μg/m3)


(μg/m3)

Maximum 8-h mean CO

concentration(μg/m3)

Legal limit value 200 40 10 000

Overall Maximum

156 8.4 3.3

Nu. Place of residence

1 SERRES 7.02 2.51 0.03 0.02

2 ADELFIKO 9.27 38.54 2.54 1.19

3 AG. ELENI 3.03 33.67 0.68 1.22

4 AG. PARASKEVI 12.64 7.17 0.09 0.07

5 AGIO PNEVMA 12.57 27.07 1.34 0.46

6 AMPELOI 15.54 7.84 0.39 0.21


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GCS01 SERRES

Distance from GCO01

(km)


n (μg/m3)


(μg/m3)

Maximum 8-h mean CO



Overall Maximum

156 8.4 3.3


7 ANO KAMILA 12.48 4.58 0.14 0.09

8 ANTHI 10.53 9.52 0.19 0.14

9 AXINOS 14.08 0.66 0.02 0.02

10 DIMITRITSIO 13.66 16.68 0.83 0.57

11 ELAIONAS 12.67 0.72 0.01 0.01

12 EM. PAPPAS 13.48 9.80 0.43 0.25

13 EPTAMYLOI 8.25 3.29 0.08 0.08

14 FLAMPOURO 10.76 2.05 0.11 0.05

15 KALA DENDRA 14.26 1.12 0.03 0.02

16 KATO KAMILA 7.13 28.71 1.06 0.56

17 KATO XRISTOS 13.51 1.48 0.03 0.03

18 KONSTANTINATO 2.32 64.44 7.80 2.46

19 KOYMARIA 11.27 22.37 1.25 0.56

20 KOYVOYKLIA 8.37 47.42 2.57 0.94

21 KRINOS 3.0 18.53 0.68 0.33

22 LEFKONAS 10.08 4.82 0.04 0.01

23 LIGARIA 12.22 12.86 0.38 0.39

24 MELENIKITSI 16.78 0.19 0.00 0.00

25 MESOKOMI 7.42 0.67 0.01 0.01

26 MITROUSIO 10.18 4.81 0.07 0.04

27 MONOKLISIA 14.41 7.13 0.15 0.12

28 MONOVRYSI 4.67 36.18 2.56 1.29

29 NEA TYROLOI 16.04 6.57 0.11 0.06

30 NEO SOYLI 9.74 38.60 2.36 1.34

31 NEOS SKOPOS 3.72 5.91 0.12 0.07

32 NEOXORI 2.78 48.02 1.90 0.76

33 NIKOKLEIA 15.73 2.28 0.04 0.05

34 OINOUSSA 9.51 7.52 0.26 0.16

35 PALAIOKASTRO 19.26 0.82 0.01 0.01

36 PARALIMNIO 9.86 0.88 0.01 0.01

37 PENTAPOLI 10.51 0.79 0.01 0.01

38 PEPONIA 6.04 29.49 0.97 0.31

39 PETHELINOS 14.33 0.50 0.00 0.01


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GCS01 SERRES

Distance from GCO01

(km)


n (μg/m3)


(μg/m3)

Maximum 8-h mean CO



Overall Maximum

156 8.4 3.3


40 PROVATAS 13.49 6.79 0.37 0.22

41 PSIXIKO 5.98 2.03 0.04 0.03

42 SISAMIA 14.40 21.66 0.27 0.48

43 SKOTOUSA 16.56 1.56 0.05 0.05

44 SKOYTARI 4.30 90.18 6.26 2.63

45 TERPNI 14.38 5.55 0.06 0.07

46 TOYMPA 11.79 1.40 0.01 0.01

47 VALTOTOPI 4.60 3.28 0.12 0.06

48 VAMVAKOYSA 7.38 53.98 4.16 1.54

49 VERGI 16.38 6.40 0.17 0.18

50 XRISO 7.81 3.82 0.25 0.13 Source: Demokritos (2013)


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Figure 4-4 Maximum hourly ground-level concentrations of NO2for the 8 weather types (WT) in the case of GCS01 (Serres)



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Figure 4-5 Total average annual NO2 concentration contours (in g/m3) for GCS01 (Serres)



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Figure 4-6 Maximum hourly ground-level concentrations of CO for the 8 weather types (WT) in the case of GCS01 (Serres)


4.3 Evaluation of Results

4.3.1 Comparison with Air Quality Limits

The above results show that the calculated ground-level concentrations generated from operation

of GCS00 and GCS01 will be below the European and Greek air quality limits. The modelled air

quality parameters are well below the normative threshold concentration values.

The overall maxima determined in the entire study area for GCS00 were 3.7 µg/m³ for the annual

average of NO2, 89 µg/m³ for the hourly maximum of NO2 and 3.2 µg/m³ for the 8-hr average of


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CO. These correspond to less than 10% compared to the legal limit for the annual NO2

concentration, about 45% of the hourly NO2limit, and less than 0.04%of the 8-hr limit for CO.

The overall maxima in the entire study area for GCS01were 8.4 µg/m³ for the annual average of

NO2, 156 µg/m³ for the hourly maximum of NO2, and 3.3 µg/m³ for the 8-hr average of CO, which

correspond to less than 22% compared to the annual NO2limit value, about 78% of the hourly

NO2limit, and less than 0.04% of the 8-hr limit for CO.

For the scenario with only 10 bcm/year at GCS00 the values were about half of the 20 bcm/year

operation. The respective percentages are: less than 5% for the annual NO2 concentration, about

25% for the hourly NO2concentration, and less than 0.02% for the CO 8-hr mean.

4.3.2 Contribution to the Ambient Air Concentrations

For the evaluation of the impact significance of a Project, also the background levels should be

taken into consideration and the future sum being evaluated.

For CO the concentrations in the region of eastern Thraki and Macedonia are reported to be

approximately 180 µg/m³ (0.18 mg/m3)for the annual mean and in the range between 140 and

230 µg/m³ (0.14 - 0.23 mg/m3) for the monthly mean values. In comparison, the modelled overall

maxima for GSC00 and GSC01 were only 3.2 and 1.6 µg/m³. Hence, the contribution of the

stations to the ambient CO concentrations will be very small.

The NO2the concentrations obtained in the baseline survey at various sampling locations around

Kipoi and Serres (cf. Section 2.2) were 7.5±2.5 μg/m³ (Kipoi) and 15.1±5.1 μg/m³ (Serres) as

averages of the three weeks sampling campaigns. Although the NO2 concentrations were

sampled for a shorter period, they can be regarded as indicative for the actual annual average

values.

With an overall maximum for the annual average of 3.7 µg/m³ in Kipoi (GSC00) the future

maximum levels in the area would range around 9 to 14 µg/m³ which is well below the legal

standards of 40 µg/m³ for protection of human health and 30 µg/m³ for protection of sensitive

vegetation.

For Serres (GSC01), the future maximum levels range around 18 to 28 µg/m³or the annual

average and will also meet the legal standards.


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4.3.3 Impact on Residential Receptors

In the previous section, the values at locations of maximum impact are discussed. The more

important aspect addresses the receptors that are affected by the Project. In Table 4-2 and in

Table 4-4 the modelled incremental concentrations are provided for each settlement in the study

area. In Table 4-7 the results for the maximal affected settlements are compiled for comparison

with the legal limit values. The results show that the limit values in these settlements are well

met. Moreover, most of the villages in the study areas are much less affected.

Table 4-7 Comparison of the modeling for the maximal affected settlements with limit values

GSC00 GSC01

Greece µg/m³

Turkey µg/m³

Greeceµg/m³

Maximum increment for NO2 annual average 1.86 0.07 7.8

Village Lagina Balabancik Konstantinato

Baseline range 5 - 10 5 - 10 10 - 20

Future concentration including the baseline 7 – 12 5 – 10 18 -28

Limit value 40 (human health)

Maximum increment for NO2 hourly maximum 33.28 6.62 90.18

Village Lagina Balabancik Skoytari

Future concentration including the baseline *) 38 - 43 *) 12 - 17 *) 100 - 110 *)

Limit value 200 (human health)

Maximum increment for CO 8-hr mean 0.8 0.3 2.63

Village Tiheron Ipsala Skoytari

Baseline range 140 - 230 140 - 230 140 - 230

Future concentration including the baseline 141 - 231 141 - 231 143 - 233

Limit value 10,000 (human health)

*) For consideration of the baseline in the hourly maximum it has to be considered that hourly concentration values are strongly depending on specific weather conditions and whether various emission sources may accumulate at a receptor location. Only in the case that other sources, with regard to the receptor location, would be located ‘in-line’ with the compressor stations, these could also affect the receptor within the short-term period of one hour. Since such a situation is an unlikely case, it is common practice to adopt the annual baseline value also as baseline for the hourly maximum.

4.3.4 Impact on Natura 2000 Areas

For sensitive vegetation, the applicable legal limit value is 30 µg/m³ for NOx. Since the modelling

was performed for NOx that was interpreted as being NO2 only, the modelled values can directly

be used for this evaluation.


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The modelled incremental concentrations at the Natura 2000 area in the northwest of GCS00

range between 0.01 and 0.3 µg/m³ which is very small against the limit value. Under

consideration of the baseline measurement results of 5 – 10 µg/m³, the impact from the station

will be negligibly low.

For the Natura 2000 area near GSC01 located to the northeast, the incremental concentrations

range from 0.04 to1.3 µg/m³ which also is very small against the limit value. Under consideration

of the baseline measurement results of 10 – 20 µg/m³, the impact from the station will be

negligibly or only a minor increase to the current baseline.


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5 CONCLUSIONS

The air dispersion study was performed by employing the HYSPLIT model in order to calculate

ground-level concentration values for NO2 and CO generated from the emissions of the gas

turbines that will be operated at the compressor stations GCS00 (Kipoi) and GCS01 (Serres) in

the eastern section of the TAP. The modelling study included the determination of characteristic

weather types representing the meteorological conditions in the two study areas. Each study area

of 30x30 km2was centred at the location of the respective compressor station.

For the modelling continuous full load operation of the stations’ gas turbines throughout the year

was assumed which represents operation of the pipeline at 20bcm/year capacity. Furthermore,

the NO2 concentrations were modelled for emissions of NOx which besides NO2 also include NO.

While only a portion of NO transforms into NO2, the modelling assumed complete transformation.

In terms of air emissions this represents the so-called “worst case”, and thus results are

considered to be conservative, rather overestimating the future ground-level concentrations.

The results of the air dispersion modelling only revealed very low to low incremental ground-level

concentrations forNO2 and CO in the study area. The calculated short-term concentrations in

most of the study area were low. At some locations, for meteorologically disadvantageous hours,

elevated levels were obtained which, however, did meet the legal limits.

The concentrations of NO2 and CO calculated for GCS00 at the settlements in Turkey were very

low indicating that the effect of GCS00 on the ambient air quality in Turkey will be almost

negligible.

For operation of the pipeline at10 bcm/year, the increments would be about half compared to

20 bcm/year.

The comparison of future concentrations, calculated from the sum of measured baseline data and

the modelled increments, with the Greek legal limits (Joint Ministerial Decision (JMD)

14122/549/E.103/2011- Gov. Gaz. 488/B/30.03.11; which is similar to EU Directive 2008/50/EC)

revealed that the contribution of the compressor stations’ emissions to the measured low current

baseline concentrations will not cause exceedance of a legal limit.


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In conclusion, the operation of compressor stations GCS00 and GCS01 is not anticipated to

cause adverse effects on the ambient air quality at relevant receptors, i.e. the settlements in the

study areas for the compressor stations and the Natura 2000 areas.

Date 06/2013

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Athens GreeceAthens, GreecePhone.: + 30 210 7454613

Fax: + 30 210 7454300

[email protected]

ced at the disposal of third parties without prior consent of TAP AG.abase.