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Numerical Modelling of PM10 Propagation in Rustavi City 

Atmosphere During the Southern Background Wind 
Natia Gigauri1, Aleksandre Surmava1,2 , Liana Intskirveli1*, Mikheil Pipia1,2 

Abstract 

According to observations, experimental measurements, and numerical modelling, the atmospheric pollution 

caused by microaerosols PM2.5 and PM10 in Rustavi city, one of Georgia's industrial centres, has been estimated. 

Analysed were the fluctuations in concentration of pollutants in the urban atmosphere on a monthly, daily, and 

hourly basis. The particle concentrations in the atmosphere of Rustavi City reach their highest levels at any hour 

of the day due to the combined influence of motor vehicle traffic and industrial facilities. The distribution of PM10 

particles in the atmosphere has been determined using numerical modelling for scenarios involving background 

light air, a mild breeze, and a fresh breeze. Calculations demonstrated that light air and mild breeze cause a rise 

in the concentration of microaerosols in the urban atmosphere, but fresh breeze facilitates the dissipation of the 

pollution cloud, albeit expanding its distribution area. 

Keywords: atmosphere, pollution, microaerosols, concentration, monitoring 

Introduction 

Atmospheric air pollution represents a significant environmental challenge globally, including 

Georgia, as humans constantly reside in this environment and are consistently exposed to polluted air. 

Microaerosols PM2.5 and PM10 are atmospheric pollutants that require particular attention. They are 

introduced into the atmosphere through both natural and human activities. These particles consist of 

microscopic solid substances or liquid droplets that are of such a small size that they can be consumed 

and lead to significant health issues. PM2.5 and PM10 refer to particulate matter that consists of solid 

and liquid particles with diameters ranging from 1 to 10 µm. They are composed of particles of organic 

pollutants, carbon particles, road tar, rubber from tyres, mineral salts, acids, and other solid or liquid 

particles. The maximum allowable values for PM2.5 are 10 µg/m3 (daily average) and 25 µg/m3 (one-

time maximum). For PM10, the maximum allowable concentrations are 20 µg/m3 (daily average) and 

50 µg/m3 (one-time maximum). 

PM2.5 and PM10 particles pose the greatest risk to human life as they can lead to significant 

deterioration in human health, often resulting in fatal consequences. Specifically, an immense number 

of individuals perish annually due to atmospheric pollution caused by microparticles [1]. According to 

the World Health Organisation, 3% of cardiovascular diseases and 5% of cancer diseases are attributed 

to the influence of these particles [1]. In addition, it is highly probable that viruses, like Covid-19, attach 

to dust microparticles and spread in the atmosphere. 

The objective outlined above is to investigate the dispersion patterns of PM2.5 and PM10 particles 

in densely populated urban areas, with a particular focus on the influence of various wind directions. 

Rustavi is a highly industrialised and densely populated metropolitan area. This area is home to cement 

and nitrogen facilities, along with a range of medium and small businesses. Consequently, a variety of 

particles, including PM10 particles, are released into the air. 

The present research examines the patterns of PM10 distribution in the atmosphere of Rustavi city 

through numerical simulations, taking into account the influence of a southerly wind. 

Methods and Materials 

Based on the analysis of routine observation data [2] the content and peculiarities of microaerosols 

(PM2,5 and PM10) distribution in the atmosphere of the Rustavi city, one of the industrial centres of 

Georgia are studied. Their maximum and minimum values are identified. Through analysis of the curve 

of concentration hourly variation there is estimated a period of maximum pollution during a day. It is 

 
1 Department of environmental pollution monitoring and forecasting / Institute of Hydrometeorology, GTU, 

Tbilisi, Georgia 
2 Department of Modeling the Sea and Atmosphere Dynamics / M. Nodia Institute of Geophysics, TSU, Tbilisi, 

Georgia 

* Corresponding author: intskirvelebi2@yahoo.com 



Gigauri et al. Georgian Geographical Journal 2023, Vol.3 (2) 

established that manifestation of maximum concentration is mainly related to the motor transport traffic 

intensity, industrial facilities operation mode and meteorological conditions.  

Rustavi city atmospheric air quality measurements are made by means of only one automatic 

background monitoring station and 7 quarterly indicating measurement. Based on the results of current 

monitoring it is impossible to see a complete picture of city atmospheric air quality, that is why for its 

estimation we have used three-year (2020-2022) observation data of automated station and results of 

our experimental measurement, which means measuring the concentration of PM10 particles (µg/m3) 

using indicators such as air temperature and atmospheric pressure, as well as wind speed and direction. 

One of the indicators was the number of vehicles.  

Dust dissipation in the free atmosphere and surface layer of the atmosphere is modelled through 

numerical integration [3], using respective initial and boundary conditions. 

It is assumed that the atmosphere is polluted by a dust originated at city mains and streets due to 

motor transport traffic. Its quantity changes in time and is determined according to assessment of 

continuous surveillance materials and transport traffic intensity.  

Results 

Analysis of everyday values of microparticle concentrations showed that very high indices are 

recorded in a majority of days over the month. As the example, in fig. 1 there is shown the microaerosols 

concentration change in Rustavi city atmosphere in February 2022. It is seen from the figure, that over 

the period taken PM 2,5 and PM10 concentrations exceed two and more times their respective MPC 

values.  

 

 

Figure 1. Hourly variation of PM2.5 and PM10 concentrations in Rustavi city in February 2022 

Hourly variation of PM particles concentration in Rustavi atmosphere is analyzed (Fig. 2). As the 

example, there is given the course of data in the interval from 20 to 26 February, 2022, from where it 

is almost impossible to draw any conclusion, since concentration maximums are recorded in different 

time intervals of a day, in contradistinction from Tbilisi city [4], where the maximums have been always 

reached in the second half of a day, after 8PM, that is associated with motor transport traffic intensity 

in rush hour period. In case of Rustavi, the dust from industrial facilities is added to motor transport 

emission, therefore concentration increase depends both on motor transport traffic intensity and on 

plants operation intensity.      

0

20

40

60

80

100

120

140

160

180

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

PM2.5

PM10

Linear

(PM2.5)

Linear

(PM10)

μg /m3



Gigauri et al. Georgian Geographical Journal 2023, Vol.3 (2) 

 

Figure 2. Hourly variation of PM2.5 and PM10 concentration in Rustavi city in February, 2022 

Experimental measurement results 

Experimental measurements cover Tbilisi-Rustavi main highway, central areas of the city and 

territories adjacent to the industrial facilities. Mobile apparatus “TROTEC PC220” has been used for 

experimental measurements. Expeditions have been made three times in different meteorological 

situations. In Fig. 3 there are shown the results of expedition taken on 9th of April, 2022, and we see 

that PM particles concentrations given in item 7 (territory adjacent to Heidelberg Cement) 8 times 

exceed the data taken in other observation points. There was a windy weather (approx. 9 m/sec), and a 

windstorm perceptible to the eye during measurements that has had an impact on the graph.   

It may be said that PM2,5 particle concentrations in Rustavi city atmosphere, as a rule, are less than 

PM10 concentrations, but the nature of their change curve is almost identical. Their maximum values 

almost always surpass the corresponding maximum permissible concentrations. Experimental 

observations showed that PM particles concentration increase in Rustavi city is induced both by motor 

transport and by emissions of available plants and meteorological conditions.  

 

Figure 3. PM2.5 and PM10 concentrations in different points of Rustavi city, 9th of April, 2022 

 

Distribution of PM10 particles dissipated in the atmosphere of Rustavi city and its adjacent territories 

during light air, gentle and fresh breeze is studied. Modeling is implemented at 1189131 numerical 

grid with 1000 m horizontal steps and 1/31 dimensionless vertical steps. In the atmospheric boundary 

layer and in the free atmosphere a vertical step approximately equals to 300 m. In the 100 m thick lower 

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10

PM2.5

PM10

ზდკ
PM2.5

μg /m3



Gigauri et al. Georgian Geographical Journal 2023, Vol.3 (2) 

surface layer of the atmosphere 17 vertical grid points are selected, while step varies from 0.5 m to 15 

m. It has been assumed during modeling that PM10 concentration at the territory of Rustavi city is 

constant in time, maximal and equals to 50 µg/m3. The adjacent territories of Rustavi city have a rugged 

relief, and altitude varies there from 370 to 1400 m. Numerical calculations have been made within 

three-day interval. Calculations showed that polluting ingredients are propagated quasi-periodically 

with 24 h period.  

Light air 

In Fig. 4 there are shown the fields of wind velocity and PM10 concentrations in the surface and 

boundary layers of the atmosphere, in case of background southern light air. Background wind velocity 

changes from 1 m/sec (at 100 m height from the earth surface) to 20 m/sec (in tropopause). It is seen 

from fig. 4 that terrain effect and change in diurnal thermal regime cause formation of local wind, which 

partly differs from the background one. In particular, at Kvemo Kartli plain, along the Mtkvari River 

valley and in the northern-western part of the region the south-western wind is formed. In the northern 

and southern parts of the region there is a southern wind. Wind direction slightly changes with altitude 

and time.   

Spatial distribution of microparticles is less altered, as well. Resulting from dominant influence of 

formed local wind, microparticles are transferred to the north-west direction and form pollution cloud 

of elongated ellipse-like shape. The cloud width reaches 50 km, while length substantially surpasses it.   

 

 

Figure 4.  Wind velocity and PM10 concentration distribution at z = 2, 100 and 600 m height during background southern 

light air, when t = 12 and 24 h 

Gentle breeze 

In Fig. 5 there are shown the fields of wind velocity and PM10 concentration in the surface and 

boundary layers of the atmosphere, obtained during background southern gentle breeze. It is seen from 

Fig. 5 that when t = 12 and 24 h, the spatial distribution of wind velocity obtained via modeling is 

qualitatively similar to the wind velocity field received during light air. PM10 concentration spatial 

distribution is qualitatively similar, as well. Microparticles available in the city air move north-

westward along the formed local wind, first along the Kartli plain and then along Mtkvari River valley. 

Therefore, a cloud polluting atmosphere with microparticles is oriented to the north-west, its shape is 

uniform in the surface and boundary layers of the atmosphere, while its width slightly rises with altitude 

increase.    

 

t  =  1 2  h ,  z  =  2   m . t  =  1 2  h ,   z  =  1 0 0  m . t  =  1 2  h ,  z  =  6 0 0   m .

t  =  2 4  h ,  z  =  2   m . t  =  2 4  h ,  z  =  1 0 0   m . t  =  2 4  h ,  z  =  6 0 0   m .

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

0 . 0 0 0 1

0 . 0 0 1

0 . 0 1

1

5

2 5

5 0

1 0 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0



Gigauri et al. Georgian Geographical Journal 2023, Vol.3 (2) 

 

Figure 5. Wind velocity and PM10 concentration distribution at z = 2, 100 and 600 m height during background southern 

gentle breeze, when t = 12 and 24 h  

Fresh breeze 

During background southern fresh breeze, the impact of orography on local wind formation prevails 

the influence caused by diurnal variation of temperature. As a result, a local south-eastern wind, which 

slightly changes during a day is formed at Kartli plain and Mtkvari River valley (Fig. 6). Microaerosols 

propagation process is quasi-stationary, as well. Microaerosol cloud has a shape of cigar plume directed 

from south to the north-west, and its width slightly increases from surface layer to boundary layer of 

the atmosphere.   

 

 

Figure 6. Wind velocity and PM10 concentration distribution at z = 2, 100 and 600 m height during background southern 

fresh breeze, when t = 12 and 24 h 

Conclusion 

According on the analysis of data from the NEA, we can make the following conclusions:  

Typically, the levels of PM2.5 particles in the atmosphere of Rustavi city are lower than the levels 

of PM10 particles, while the pattern of their change is comparable. On nearly a daily basis, their 

maximum values exceed the associated maximum permissible concentrations (MPC).   

The hourly variation trend of PM particle concentration reveals that the highest concentrations occur 

at various times throughout the day. This is due to the combination of dust emissions from industrial 

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

2 0

4 0

6 0

8 0

t  =  1 2  h ,  z  =  2   m . t  =  1 2  h ,   z  =  1 0 0  m . t  =  1 2  h ,  z  =  6 0 0   m .

t  =  2 4  h ,  z  =  2   m . t  =  2 4  h ,  z  =  1 0 0   m . t  =  2 4  h ,  z  =  6 0 0   m .

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

0 . 0 0 0 1

0 . 0 0 1

0 . 0 1

1

5

2 5

5 0

1 0 0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

t  =  1 2  h ,  z  =  2   m . t  =  1 2  h ,   z  =  1 0 0  m . t  =  1 2  h ,  z  =  6 0 0   m .

t  =  2 4  h ,  z  =  2   m . t  =  2 4  h ,  z  =  1 0 0   m . t  =  2 4  h ,  z  =  6 0 0   m .

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

0 . 0 0 0 1

0 . 0 0 1

0 . 0 1

1

5

2 5

5 0

1 0 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

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1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0

1 0 3 0 5 0 7 0 9 0 1 1 0

1 0

3 0

5 0

7 0



Gigauri et al. Georgian Geographical Journal 2023, Vol.3 (2) 

facilities and motor vehicle exhaust. Therefore, the increase in concentration depends on both the 

intensity of motor vehicle traffic and the operation of industrial plants.  

A study was conducted in Rustavi city to numerically model the local propagation of microparticles 

in the presence of background light air, a soft and fresh breeze. The modelling results indicate that the 

presence of southern light air in Rustavi, together with the topography impact and changes in the daily 

temperature patterns, lead to the production of local winds that are partially distinct from the prevailing 

winds. Specifically, a south-northern wind is generated in the Kvemo Kartli plain, Mtkvari River valley, 

and the north-western portion of the region. A southerly wind is generated in the northern and southern 

regions. The wind direction undergoes small variations in relation to altitude and time. Due to the 

prevailing impact of local wind patterns, microparticles are transported in a north-west direction, 

resulting in the formation of a pollution cloud with an elongated, elliptical shape. The breadth of the 

cloud measures 50 kilometres, while its length significantly exceeds that measurement. The spatial 

distribution of wind velocity derived through modelling during a background southern gentle breeze is 

qualitatively comparable to the wind velocity field seen during light air. The regional distribution of 

PM10 concentration exhibits qualitative similarity. Amidst a gentle wind blowing from the south, the 

influence of the local terrain on the creation of winds is more significant than the impact of daily 

temperature changes. Consequently, a regional south-eastern breeze, which undergoes modest 

variations throughout the day, is generated in the vicinity of the Kartli plain and Mtkvari River valley. 

The microaerosol cloud takes the form of a cigar-shaped plume that extends from the south to the 

northwest. Its width gradually grows from the surface layer to the boundary layer of the atmosphere. 

Competing interests 

The authors declare that they have no competing interests. 

Authors’ contribution 

N.G. contributed to the execution of model calculations, analysis of the results, experimental 

measurements, and text revision for the article. A.S. conducted model computations, analysed the 

results, and oversaw the composition of the paper. L. I. was responsible for creating the monitoring 

database, actively contributed to the experimental measurement, conducted analysis on the obtained 

results, and reviewed the article manuscript. M.P. performed empirical measures and analysed the 

resulting data, participated in the evaluation of the manuscript. 

Acknowledgements 

The scientific research is funded and implemented within the grant project YS-21-132 of the Shota 

Rustaveli National Science Foundation. 

References 

[1] World Health Organization, WHO’s Agenda on Air Pollution and Health. www.who.int/airpollution/en/) 

[2] https://mepa.gov.ge/Ge/PublicInformation/27987  

[3] Aleksandre A Surmava, Leila V Gverdsiteli, Liana N Intskirveli, Natia G Gigauri. Numerical simulation of 

dust distribution in city tbilisi territory in the winter period, Journal of the Georgian Geophysical Society, 

v. 24(1), 2021, pp. 37-43 

[4] N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, M. Pipia. Spatial distribution of PM10 and PM2.5 

concentrations in Tbilisi city atmosphere according to routine observations and en-route measurement data, 

Collected works of the Institute of Hydrometeorology at the Georgian Technical University, vol. 131, 

2021, pp. 44-50. 

 

 

 

 


