Vol. 120, No. 3 * Pages 267–351 * July - September 2016

Ground-level or tropospheric ozone (O₃) is an oxidant air pollutant that has harmful effect on human health and vegetation, however, it is a short-lived greenhouse gas. Ozone is a secondary pollutant; which means that it is not directly emitted in the ambient air, but also produced from the photochemical oxidation of non-methane volatile organic compounds (NMVOCs), methane (CH₄), or carbon monoxide (CO) in the presence of nitrogen oxides (NO_x). It is destroyed both photochemically and through deposition to the surface. Summarizing the chemistry of ozone is complex and non-linear. Background concentrations of ground-level ozone in Europe do not show a significant downward trend, but in Hungary essential reduction (–0.28 mg/m³) was observed at K-puszta station in the last decades. In the monthly distribution the amplitude decrease with increase in altitude, at K-puszta 45.1 mg/m³, while at Nyírjes 36.6 mg/m³ amplitudes were observed. Based on our data we found that the ozone gradient is about +1.4 mg/m³/m. Breathing ozone can result in a number of negative health effects that are observed in relevant segments of the population. Ozone also is known as the air pollutant most damaging to agricultural crops and other plants. This article gives a general overview of the ozone problem focusing on the Hungarian specialties.

This paper presents an urban climatological application of the urban monitoring systems – recently implemented in Szeged, Hungary and Novi Sad, Serbia – using the first set of data collected during the summer of 2014. In order to ensure a representative number and placement of stations, the selection of measurement sites was based on Local Climate Zone (LCZ) maps developed for both cities. Present paper concentrates only on the intra-urban temperature pattern characteristics expressed by the thermal reactions of the different LCZ classes in both cities. The daily temperature indices (e.g., summer days) have the highest values in the densely built up LCZs. The diurnal cycle of surplus temperatures by LCZ classes under anticyclonic weather conditions were found to be similar in the two cities with higher absolute values in the case of Novi Sad. During summer, the diurnal variation of conventional heat island intensity confirms the general knowledge that it remains positive with highest values at night, while negative values occur predominantly during the day.

Our aim was to study the effects of short-term weather fluctuations on the quality of oxbows, based on the physico-chemical parameters of the water. The present study explored the effect of precipitation, temperature, and the water level of the main river on the quality of oxbows. We assessed the quality of four oxbows in the Upper Tisza region (north Hungary) over a two-year period. Water samples were collected in the summer in 2011 and 2012, and 12 physico-chemical parameters were investigated.
We found positive correlations between the dissolved oxygen, water temperature, concentration of hydro carbonate, nitrate, pH, conductivity and the average temperature. Canonical discriminant analysis showed that the studied oxbows were similar in 2011 and 2012, based on physico-chemical parameters. Significant differences were found between the years, in terms of the water temperature, the content of suspended solids, and the concentrations of carbonate and chloride. Our results show that only short-term weather changes such as less precipitation and higher temperature cause the quality of oxbows to deteriorate.
Our results demonstrated that the water quality of oxbows is influenced by the River Tisza, because the decrease in the water level of the Tisza was also responsible for the differences between the years, based on the physical-chemical parameters of the water.

Snow is a very important component of the climate system which controls surface energy and water balances. Its high albedo, low thermal conductivity, and properties of surface water storage impact regional to global climate. The various properties characterizing snow are highly variable and thus have to be determined as dynamically active components of climate. However, on large spatial scales, the properties of snow are not easily quantified either from numerical modeling or observations. Thus, it is vital to estimate the model performance in comparison with consistent datasets of assimilated data. Snow water equivalent data simulated with four different model configurations of the RegCM climate model over Central Europe for a time window of 10 consecutive winters are compared with the objective analysis data from the high-resolution CARPATCLIM database on monthly and seasonal basis. The CARPATCLIM snow water equivalent data are also modeled, but based on the gridded daily observation of the temperature, precipitation, and relative humidity. The results reveal good commensurability over the bigger, mostly flat part of the domain, however, they show significant discrepancies, mainly overestimation, over the Carpathian Region.

The potential resurgence of malaria in the temperate areas of Europe due to climate change is an actual topic of epidemiology. Although several ecological forecasting models were built for the prediction of the potential re-emergence of malaria in the recently non-endemic areas of the world, the simulations are mainly based on the recent climatic thresholds of the tropical and subtropical vectors and Plasmodium parasites, mainly of Plasmodium falciparum. We aimed to reanalyze the primarily Plasmodium vivax caused autochthon malaria disease data of the past model period of 1927-1934 in Hungary to gain reliable knowledge about the climatic thresholds and the determinants of the malaria season for a temperate climate in a Central European country. Multivariable and simple linear correlation and regression was performed to analyze the malaria data of 96 months dividing the season a first and a second half parts of the year. Two models were built on the gained correlations using unstandardized and standardized correlation weights. It was found, that both in the first and second halves of the year, the ambient mean temperature was the most important predictor of the relative malaria incidence, while precipitation influenced the first half of the season. Summer sum of precipitation above 200 mm was found as one of the most important determinant of the absolute annual case number of benign tertian malaria. The unstandardized weights-based modeled malaria seasons returned well the observed autochthon malaria seasons.