POSUDZOVANIE VPLYVU AUTOMOBILOVEJ DOPRAVY NA ZNEČISTENIE OVZDUŠIA ASSESMENT OF THE IMPACT OF ROAD TRAFFIC ON AIR POLLUTION POSUDZOVANIE VPLYVU AUTOMOBILOVEJ DOPRAVY NA ZNEČISTENIE OVZDUŠIA ASSESMENT OF THE IMPACT OF ROAD TRAFFIC ON AIR POLLUTION

5 K O M U N I K Á C I E / C O M M U N I C A T I O N S 1 / 2 0 0 3 ● Negatívny vplyv dopravy na znečistenie ovzdušia je všeobecne známy. Automobilová doprava má veľký podiel na znečisťovaní prízemnej vrstvy atmosféry, v ktorej sa rozvíja život, špeciálne imisií, t. j. koncentrácie emitovaných znečisťujúcich látok. Dôvodom je emisia hlavných znečisťujúcich látok z automobilovej dopravy tesne nad povrchom zeme (CO – oxid uhličitý, NOx – suma oxidov dusíka a VOC – prchavé organické zlúčeniny).

Doprava a dopravný priemysel v Európe spotrebováva 20 % celkovej energie, z tohto množstva až 83 % spotrebováva cestná The negative impact of traffic on air pollution is a generally known fact. Automobile traffic has a great share in polluting the ground layer of the atmosphere where life develops and this applies especially to emissions, i. e. concentrations of polluting substances being emitted. This is the result of emissions of the main polluting substances produced by automobile traffic (CO -carbon monoxide, NO x -sum of nitrogen oxides and VOC -volatile organic compounds) just above the surface of the earth.
The article deals with the influence of automobile traffic on air pollution using the methodology of calculating the volume of generated pollutants applied for this purpose.

Introduction
The problem of air pollution caused by traffic cannot be solved by increasing the volumes of air polluting substances release as it is solved in industrial sectors, where permitted emission limits are secured by specifying the minimum chimney height. To reduce the impact of automobile traffic on pollution of the ground layer of the atmosphere, it means to reduce the emissions of pollutants coming from vehicles by means of technical enhancement of the combustion process, by means of interception or transformation of the polluting substances with catalysts. Another solution can be to deflect or redirect traffic from the areas with the most polluted air.

Impact of Traffic on Air Pollution
The burden laid on the environment by human activity -by the traffic -is the result of bringing chemical, physical, and biological components into the environment. It is important not to exceed the rate of sustainability of a territory and not damage it. The traffic has had a bad impact on the environment already when new roads are constructed and exploited, mostly due to noise and emissions. Nowadays, technological methods and technical equipment have been developed that can ensure that the specified hygienic limits will not be exceeded.
Traffic and traffic industry in Europe consumes up 20 % of the overall energy, and 83 % out of this amount is consumed by road  Na znečisťovaní ovzdušia v okolí cestných komunikácií sa podieľajú hlavne škodliviny z výfukových plynov vozidiel a zvýšená prašnosť spôsobená vírením usadených častíc na povrchu vozovky a v jej blízkosti.
Emissions of basic polluting substances coming Table 1 from mobile sources in [1995][1996][1997][1998][1999] Air pollution in the vicinity of roads is the result of pollutants coming from vehicle exhaust gases and the increased amount of dust caused by whirling of sedimentary particles on the surface of pavements and around the pavements.

Possibilities of Minimizing the Impact of Traffic on the Environment
Further traffic development is inseparably connected with the issue of life style values, living conditions and the level of economy. The framework defined by the public interest within which traffic concepts can be developed, depends on changing the attitude of the society towards these issues. A traffic policy must therefore consider global and regional conditions. Such strategies that involve changes in traffic systems and some reduction of ineffective traffic seem to be perspective. Harmful effects of the traffic on the environment must be reduced by implementation of faster, safer and more comfortable public traffic service, as well as by limitation of individual traffic, in large cities in particular.

Influence of Layout on Emissions Dispersion
The quality and cleanness of the atmosphere has become a serious problem in traffic network planning in and outside cities, in traffic organization and regional planning. Traffic collapses in cities lead to higher concentration of pollutants.
The position of the road is permanent after it is constructed, so it is necessary to pay attention to the design of communication systems. According to [3], dispersion of pollutants dependent on the vertical alignment position (in the cut, in the field, on the embankment) was monitored and the results show that this dependence is seen only when the wind velocity is under 3 m/s, and in this case the formation level seems to be more suitable for emission dispersion. NO x concentrations monitored near a road on the embankment were twice lower than the concentrations near a road located at the ground level. Figures 1 and 2 show comparative data calculated for a 1 km long road section with the same directional orientation with the wideness category of MS 21.5 for urban driving mode, which corresponds to a local distributor road and R22.5 for rural (fluent) driving mode on an expressway (R) . The assumed number of passenger cars was 10,000 / 24 hours, trucks 1,000 / 24 hours, the peak traffic in half an hour was assumed to be 5% out of the total all-day long 24 hours traffic.

Road Greenery
Effective usage of the road greenery can considerably reduce the negative impact of automobile traffic. In the past, the effect of greenery was not utilized sufficiently. Nowadays, the protection and creation of the environment and its enhancement is associated with the problem of balance between the civilization and biological aspects of a man. One of the various functions of the greenery is filtration, so greenery is planted along roads.
However, not every form of planting results in improved situation. Depth of the planting and its filtering efficiency are very important. The greenery can capture dust and equally disperse gaseous emissions.
Regulation of wind velocity by dense planting increases the volume of dust in the vicinity of the road. The species that allow the wind to blow through are more effective.
V intraviláne miest je citlivo vnímaný aj hluk od dopravy. Zeleň popri komunikácii tlmí hluk od dopravy v závislosti od A bushy, dense deciduous greenery with the width of 5 m (see Fig. 3) reduces the dispersion of the pollutants to the surrounding by approximately 20 %. The greenery with the width of 10 m (see Fig. 4) reduces the dispersion of the pollutants by up to 60 % in the summer. The most proper is the combination of deciduous and coniferous species. There is no oscillation in the efficiency of the planting between summer and winter (see Fig. 5) [3].
The effect of capturing the dust by oxygen production and carbon dioxide consumption can be seen in deciduous and coniferous trees. Considering gaseous pollutants, greenery is effective only in case of low concentrations, otherwise coniferous trees in particular dry up.
It can be seen from the presented comparisons that the question of the impact of traffic on air pollution in urban agglomerations should be solved already at the stage of land planning documentation, where the location of the roads is determined. The need of the balance between civilization and biological aspects of man is manifested especially in urban agglomerations, where automobile traffic makes the environment worse.
The noise from the traffic is felt as a sensitive issue in urban agglomerations. The greenery mutes this noise depending on the width of the green belt. More significant muting
can be seen starting from the width of 15 -20 m. In the green belt it is appropriate to combine trees and bushes, so that as little noise passes through as possible. It is recommended to combine deciduous and coniferous species, because the deciduous species have no effect on noise protection during their vegetative standstill. The reduction of noise energy is the result of the large amount of noise reflected on the leaves, branches and needles, not of absorption.

Noise Barriers
Construction of noise barriers has got positive influence also on the emission dispersion. A wall makes a barrier that affects the concentration of gaseous substances near the road, however, if it is properly situated, it reduces this value in the area behind the wall. Therefore, if footpaths are constructed behind noise barriers, the concentrations in the air are lower.
It can be seen from the presented comparisons that it is necessary to solve the impact of the traffic on air pollution already at the stage of land planning documentation, where the location of the roads is determined.

Possibilities of the Influencing the Production of Emissions
To reduce sources of pollutants means to influence traffic intensity by changing traffic flows, reducing the number of trucks, limiting speed, which can be achieved by road signs and synchronization of the traffic mode in terms of the communication system (green waves). Figures 9 and 10 show comparative data calculated for a 1 km long road section with the same directional orientation with the wideness category of MS 21.5 for urban driving mode, which corresponds to a local distributor road (MS) and a R22.5 expressway for rural (fluent) driving mode. The assumed number of passenger cars was 10,000/24 hours, trucks 1,000/24 hours, the peak traffic in half an hour was assumed to be 5 % from the total all-day 24 hours traffic. The calculation was done according to the SAV (Slovak Science Academy) methodology. [4] Obr. 7 Vplyv protihlukovej steny na redukciu imisií (rýchlosť vetra Ͼ 2m.s Ϫ1 ) Fig. 7 Effect of the noise barrier on the emission reduction (wind velocity Ͼ 2m.s Ϫ1 ) Obr. 8 Porovnanie účinku zelene, protihlukovej steny a zemného valu [3] (š -šírka, h -výška) Fig. 8 Comparison of the effect of greenery, noise wall and embankment [3] C

Effect of Traffic Regulation on Emission Production
When enhancing the environment in urban agglomerations, preventive approach to problem solving plays a significant role. Traffic is a problem of every city nowadays. One of the examples how to solve this problem in terms of air pollution caused by traffic is a large study of the Technical University of Graz. [5] Research workers from the TU Graz worked out a study based on testing the traffic in previously selected parts of the town, where they evaluated fuel consumption and emissions coming from traffic in an uncontrolled zone, when the speed was limited to 30 km/h and 50 km/h within the same zone.
Emissions of NO x nitrogen oxides, carbon monoxide CO, production of non-combusted hydrocarbons C x H x (or HC), fuel consumption and traveling speed were monitored. These factors were calculated per passenger car unit (PCU), which is based on the traffic flow composition, where 67 % are the vehicles with gasoline engines (petrol engine) without catalyst, 21 % the gasoline engines with catalyst and 12 % are the vehicles with diesel engine (oil engine).
Production of the carbon monoxide emissions strongly depends on the traveling speed, production of hydrocarbons depends on the speed, too, however, the driving speed is not significant for the production of nitrogen oxides.

Mathematical Modeling of Air Pollution
In the first approximation, a street may be taken as a linear source of pollutants, where the produced pollutants are distributed equally. There are several principally different methods of mathematical modeling of air pollution caused by traffic [4,9,10]. The analytical model will be described briefly.

Analytical Model -Linear Source
The easiest model of the air pollution caused by traffic is based on the elementary semi-empirical Gauss relationship for pollutant distribution in a smoke tow coming from a linear source. The following will apply for the ground concentration of a pollutant: where q is emission from the linear source (mg.m Ϫ1 .s Ϫ1 ), U is wind velocity (m.s Ϫ1 ), is the angle between the wind direction and the road axis, z is the empirical parameter characterizing vertical dispersion of the pollutants. The E(y 1 , y 2 ) function expresses the effect of the linear source finality on the distribution of the pollutants near the ends of the road.
The presented model is a simple and reliable one and is used to compute air pollution caused by traffic over large areas. A detailed description of this model is in [6].

Description of the Program for the Emission Production Modeling
Mathematical modeling is done on the basis of a traffic prognosis. Horizontal alignment of the road must be placed into a system of coordinates. The studied area around the road or the object is fit into the grid of the size of 10 or 100 meters between the points, according to the size of the area, for which the emission production and nitrogen oxides concentration are calculated.

Assumptions and Indefinite Aspects of the Model Calculation
q Estimated average speed of the traffic flow, q Specific emissions are considered for general composition of the traffic flow, for the current traffic volume and the prospective for the next years, q Windy conditions related to the dominant wind direction are based on the average data from long-term monitoring of SHMU (Slovak Institute of Hydro-Meteorology), the average wind velocity is determined from all the measurements, including doldrums, q The most unfavorable air stability is assumed, when there are the highest demands on the breathing zone.

Modeling Input Data
In a numerical model for modeling the emissions coming from mobile sources, the following is considered: -Emission factors for the current and future fleet, -Traffic volume and its composition according to a vehicle type, -Longitudinal gradient of the road, -Urban or rural traffic mode (driving fluency, buildings along the road), -Period of the evaluation of emission production, -Driving speed, -Meteorological conditions (direction and velocity of the wind), -Climatic conditions (according to Pasquill-Gifford categories of stability).

Modeling Output Data
q Calculation of the overall production of the pollutants into the atmosphere (kg/day), q Calculation of the concentration of the pollutants in the atmosphere (g.m Ϫ3 ).
The most significant input data for any mathematical model of air pollution is the source of an emission. For example, in formula (1) the concentration of the pollutant is directly proportional to the source of the emission. Emission of the road cannot be measured directly as it is in the case of a stationary source. The calculation is based on knowing the emissions coming from the vehicles running through the road according to the following relationship: I keď vieme stanoviť PO, PN s vysokou presnosťou, je prakticky nemožné stanoviť presne emisné faktory EMO a EMN. Môžeme predpokladať, že prakticky každé vozidlo má inú emisiu znečisťujúcich látok i v prípade, ak ide o ten istý typ vozidla. Vozidlá sa môžu navzájom líšiť zaťaženosťou, technikou jazdy, rýchlosťou a nastavením motora. V slovenskej výpočtovej metodike sú všetky osobné a nákladné vozidlá charakterizované jediným priemerným emisným faktorom EMO a EMN.
Študované územie komunikačného systému mesta bolo rozdelené na sieť bodov so vzájomnou vzdialenosťou 100 m, pre ktoré boli modelované koncentrácie oxidov dusíka. Although we can determine the PO and PN with high accuracy, it is practically impossible to determine the exact emission factors for EMO and EMN. We can assume that every vehicle has got different emissions of pollutants, even if these are the vehicles of the same type. Vehicles can differ in load, driving technique, speed and engine setting. In the Slovak calculation methodology, every passenger car and every truck is characterized by the only one average emission factor EMO and EMN.

Utilisation of the Model in Practice
As an example, the modeling of the air pollution caused by the traffic in the city of Žilina is presented.
The area of Žilina is 8,652 ha and the city has got 88,000 inhabitants [2]. Road density of the Žilina district is 0.378 km/h 2 , or 2 km/1000 inhabitants according to the data from the Slovak Road Administration -the Road Databank.
The basic road network of the city is a radial-circular one. It is made of 3 urban circles; the radials are the I. and II. class roads and urban communications.
Mathematical modeling is done on the basis of a traffic prognosis for the monitored area. The prognosis of the present state is based on the national traffic census from 1995 and 2000. Further data on traffic volume are taken from traffic-engineering materials, which have been processed for the project of the D1 and D18 highway around Žilina. The values for traffic volume for 2015 are derived from the conversion of the values obtained in the national traffic census using the prognosis coefficients.
The communication system of the city was fitted to a grid with the point interval of 100 m, where concentrations of nitrogen oxides were modeled.

Assumptions and Indefinite Aspects of the Model Calculation
q Average speed of the traffic flow in the town was considered to be 50 km/h, q Considered specific vehicle emissions are given in Table 2, q Average frequency of wind direction was used from long term monitoring in the Dolný Hričov airport, average wind velocity is estimated from all the measurements, including doldrums and it is presented in Table 3.
Average frequency of wind direction in one year [%] Table 3 Expected Effects of the Traffic in the City In the air pollution modeling, the amounts of the total production of pollutants into the air (t/year) were evaluated as based on the all-day long 24-hour traffic, and concentrations of nitrogen oxides NO x (g/m Ϫ3 ) at the sections with the highest traffic volumes that originate from the average daily traffic were compared and these were compared to the permitted daily concentration of NOx, which is 100 g/m Ϫ3 .
Based on the mathematical modeling [8] for 2000 and 2015, it was found out that in the city of Žilina the traffic produced 660.01 kg of NO x per day in 2000, equal to 240 t/year. Out of this volume 132.9 t/year (55 %) was produced by individual traffic. In 2015 it is expected that vehicles will produce 575.45 kg of NO x per day, what equals to 210 t/year. Out of this volume 107 t/year (51 %) will be produced by individual traffic. Maximal assumed daily concentration of NO x in 2015 after the planned communications are constructed should not exceed 15 g/m Ϫ3 .

Conclusion
The demonstration of the results obtained through the mathematical model is meant to indicate a wide range of its utilization. The length of the article does not allow us to present the whole scope of the data acquired from alternative model solutions.
Methods of mathematical modeling, in accordance with traffic prognoses, are a very effective tool in this process and in the process of evaluation of the effects on the environment.
An emission study should therefore form a part not only of a road project documentation at the level of variant decision-making about choosing a suitable location for road routes, but it should also be an inseparable part of a decision-making processes at the level of finding regional solution for problems with traffic. In order to achieve this aim, the study should comprise a model of emission production coming from automobile traffic to such extent that it would be possible to compare various alternatives to the solution and to evaluate the benefits or the risks brought about into the region.