Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement.

Beekeeping is an exceptionally weather-sensitive agricultural field. Honey production and pollination services depend on the complex interaction of plants and bees, both of which are impacted by short-term weather changes. In this review, classical and recent research is collected to provide an overview on short-term atmospheric factors influencing honey production, and the optimal and critical weather conditions for bee activity. Bee flight can be directly obstructed by precipitation, wind, extreme temperatures and also air pollution. Bees generally fly within a temperature range of 10–40 °C, with optimal foraging efficiency occurring between 20 and 30 °C. Wind speeds exceeding 1.6–6.7 m/s can reduce foraging efficiency. Additionally, bee activity is significantly correlated with temperature, relative humidity and solar radiation, factors which influence nectar production. Optimal conditions for nectar collection typically occur in the morning and early afternoon hours with mild and moist weather. The diurnal nectar collection habit of bees adjusts to the nectar production of individual plant species. Extreme weather occurring in the sensitive hours is noticeable both in the nectar production of plants and in the activity of bees, thus in the honey yield. Understanding the impact of weather on honey bees is crucial in the management and planning of honey production. This review highlights the importance of studying these interactions to better adapt beekeeping practices to changing environmental conditions. Graphical Abstract

Long-range simulation of the dispersion of air pollutants in the atmosphere is one of the most challenging tasks in geosciences. Application of precise and fast numerical models in risk management and decision support can save human lives and can diminish consequences of an accidental release. Disaster at Fukushima Daiichi nuclear power plant has been the most serious event in the nuclear technology and industry in the recent years. We present and discuss the results of the numerical simulations on dispersion of Fukushima-derived particulate ¹³¹I and ¹³⁷Cs using a global scale Lagrangian particle model. We compare concentrations and arrival times, using two emission scenarios, with the measured data obtained from 182 monitoring stations located all over the Northern Hemisphere. We also investigate the homogenization of isotopes in the atmosphere. Peak concentrations were predicted with typical accuracy of one order of magnitude showing a general underestimation in the case of ¹³¹I but not for ¹³⁷Cs. Tropical and Arctic plumes, as well as the early detections in American and European midlatitudes were generally well predicted, however, the later regional-scale mixing could not be captured by the model. Our investigation highlights the importance of the parameterization of free atmospheric turbulence.

Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of ¹³¹I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of ¹³¹I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors.