Dispersion Modeling of Pollutants

Dispersion models for air quality are mathematical tools that enable the assessment of the impact of individual emission sources or groups of sources on air quality. They make it possible to predict how air quality will change as a result of changes in emissions – for example, increased traffic volume, the introduction of emission control measures, or the application of new technologies.

These models are particularly useful for supplementing data from automatic air quality monitoring stations, as their spatial coverage is often limited.

• Dispersion models are most often used for:
  • Preparing plans and programs for improving air quality;
  • Assessing air quality in areas without sufficient monitoring data;
  • Supporting the development Optimizing the number and location
  • of monitoring stations.of monitoring stations.

• Dispersion models describe the relationship between emissions and the concentrations of pollutants in the air, taking into account key factors that influence the movement and transformation of pollutants:
  • Meteorological conditions (wind, temperature, humidity, atmospheric stability);
  • Terrain configuration;
  • Characteristics of the emission source (stack height and diameter, temperature and flow rate, emission composition, etc.);
  • Topographic features and land use type.

In accordance with European Union legislation, the use of dispersion models is a standard method for assessing air quality, including analyzing future scenarios and developing emission reduction strategies.

Using local dispersion models within the framework of a Twinning Project for air quality, the Ministry prepared a Study on modeling the impact of emissions from point sources and traffic on air quality in the territory of the City of Skopje.

The study assessed the impact on air quality in Skopje from the main emission sources. Although the input data used in this study involved a certain degree of uncertainty, it nevertheless provided important information about air quality levels in different parts of Skopje.

According to the calculations, it was concluded that traffic in Skopje contributes the most to the increase in NO₂ concentrations, with the highest concentrations occurring along main roads and major intersections, while stationary sources contribute the most to SO₂ concentrations.

According to the modeling results, limit values and critical levels were not exceeded in any case. However, the measured concentrations in Skopje were higher than the modeled SO₂ concentrations, indicating that the modeling did not take into account all emissions in the territory of Skopje.

The modeling results carry a degree of uncertainty due to the unreliability of the meteorological data used and the limited availability of good-quality input data for emissions from stationary and mobile pollution sources.