From a temporal viewpoint, air pollution has significant daily patterns/cycles of behaviour. These cycles are conditioned by anthropogenic and natural phenomena. In both cases, a detailed observation and an understanding of the daily cycles rules or daily patterns of air pollution can be significant and at the same time can contribute to more effective measures to reduce the harmful impact of air pollution on human health. In this paper the new sunflower diagram is presented. The key advantage of the sunflower diagram is the ease of understanding the result and the ability to present information in the form of a graphic pattern, allowing the user to quickly understand the content. Using the sunflower diagram, we will present an analysis of the meteorological parameters that are important for understanding air pollution and air-pollution data for different locations in Slovenia.
COBISS.SI-ID: 31160359
In conditions of complex terrain, modelling of air pollutant dispersion still has a number of scientific challenges. Ideally, appropriate meteorological data should be available for modelling. Unfortunately, for many purposes, there is no time to carry out suitable measuring campaigns. Therefore the results of prognostic weather forecasts (NWP models) are being widely used. However, these models still have quite a few disadvantages when their results are used as input for dispersion models over complex terrain. This study presents the validation of the quality of the weather forecasts in the surroundings of the Nuclear Power Plant Krško in Slovenia, an area with highly complex terrain and the resulting complex meteorological characteristics. The forecast is available for a horizontal resolution of 2 km and half hour temporal interval and seven days in advance. The predicted meteorological parameters are validated using the measured meteorological parameters.
COBISS.SI-ID: 31160103