László Makra

The history and impacts of airborne Ambrosia (Asteraceae) pollen in Hungary

Ambrosia arrived in Hungary from northern Mediterranean in the 1920s, and by the end of the 20th century it has become widely distributed. In Southern Hungary (northern part of Serbia‐Montenegro included), Ambrosia pollen concentrations during the peak season are about one order of magnitude higher than the counts in the rest of Europe. The aim of the study is to survey the history of Ambrosia in the Carpathian Basin and analyse some Ambrosia pollen characteristics (season start, duration, average diurnal count and total count) focusing on a medium‐sized city, Szeged, Southern Hungary. The data consists of daily Ambrosia pollen counts for the 15‐year period between 1989 and 2003. Although Ambrosia pollen counts fluctuate considerably, no significant trends can be detected in their temporal course. According to the Makra‐test, the highest pollen counts in Szeged are detected between 20 August and 11 September. This period is in good correspondence with both days comprising over 50 pollen grains per m3, and the main pollination period (MPP).

A unifying framework for metrics for aggregating the climate effect of different emissions

Multi-gas approaches to climate change policies require a metric establishing ?equivalences? among emissions of various species. Climate scientists and economists have proposed four classes of such metrics and debated their relative merits. We present a unifying framework that clarifies the relationships among them. We show that the Global Warming Potential, used in international law to compare greenhouse gases, is a special case of the Global Damage Potential, assuming (1) a finite time horizon, (2) a zero discount rate, (3) constant atmospheric concentrations, and (4) impacts that are proportional to radiative forcing. We show that the Global Temperature change Potential is a special case of the Global Cost Potential, assuming (1) no induced technological change, and (2) a short-lived capital stock. We also show that the Global Cost Potential is a special case of the Global Damage Potential, assuming (1) zero damages below a threshold and (2) infinite damage after a threshold. The UN Framework Convention on Climate Change uses the Global Warming Potential, a simplified cost-benefit concept, even though the UNFCCC frames climate policy as a cost-effectiveness problem and should therefore use the Global Cost Potential or its simplification, the Global Temperature Potential.

Modelling the introduction and spread of non-native species: international trade and climate change drive ragweed invasion

Biological invasions are a major driver of global change, for which models can attribute causes, assess impacts and guide management. However, invasion models typically focus on spread from known introduction points or non-native distributions and ignore the transport processes by which species arrive. Here, we developed a simulation model to understand and describe plant invasion at a continental scale, integrating repeated transport through trade pathways, unintentional release events and the population dynamics and local anthropogenic dispersal that drive subsequent spread. We used the model to simulate the invasion of Europe by common ragweed (Ambrosia artemisiifolia), a globally invasive plant that causes serious harm as an aeroallergen and crop weed. Simulations starting in 1950 accurately reproduced ragweeds current distribution, including the presence of records in climatically unsuitable areas as a result of repeated introduction. Furthermore, the model outputs were strongly correlated with spatial and temporal patterns of ragweed pollen concentrations, which are fully independent of the calibration data. The model suggests that recent trends for warmer summers and increased volumes of international trade have accelerated the ragweed invasion. For the latter, long distance dispersal because of trade within the invaded continent is highlighted as a key invasion process, in addition to import from the native range. Biosecurity simulations, whereby transport through trade pathways is halted, showed that effective control is only achieved by early action targeting all relevant pathways. We conclude that invasion models would benefit from integrating introduction processes (transport and release) with spread dynamics, to better represent propagule pressure from native sources as well as mechanisms for long-distance dispersal within invaded continents. Ultimately, such integration may facilitate better prediction of spatial and temporal variation in invasion risk and provide useful guidance for management strategies to reduce the impacts of invasion.

Forecasting of traffic origin NO and NO2 concentrations by Support Vector Machines and neural networks using Principal Component Analysis

Abstract The main aim of this paper is to predict NO and NO 2 concentrations four days in advance comparing two artificial intelligence learning methods, namely, Multi-Layer Perceptron and Support Vector Machines on two kinds of spatial embedding of the temporal time series. Hourly values of NO and NO 2 concentrations, as well as meteorological variables were recorded in a cross-road monitoring station with heavy traffic in Szeged in order to build a model for predicting NO and NO 2 concentrations several hours in advance. The prediction of NO and NO 2 concentrations was performed partly on the basis of their past values, and partly on the basis of temperature, humidity and wind speed data. Since NO can be predicted more accurately, its values were considered primarily when forecasting NO 2 . Time series prediction can be interpreted in a way that is suitable for artificial intelligence learning. Two effective learning methods, namely, Multi-Layer Perceptron and Support Vector Regression are used to provide efficient non-linear models for NO and NO 2 times series predictions. Multi-Layer Perceptron is widely used to predict these time series, but Support Vector Regression has not yet been applied for predicting NO and NO 2 concentrations. Grid search is applied to select the best parameters for the learners. To get rid of the curse of dimensionality of the spatial embedding of the time series Principal Component Analysis is taken to reduce the dimension of the embedded data. Three commonly used linear algorithms were considered as references: one-day persistence, average of several-day persistence and linear regression. Based on the good results of the average of several-day persistence, a prediction scheme was introduced, which forms weighted averages instead of simple ones. The optimization of these weights was performed with linear regression in linear case and with the learning methods mentioned in non-linear case. Concerning the NO predictions, the non-linear learning methods give significantly better predictions than the reference linear methods. In the case of NO 2 the improvement of the prediction is considerable; however, it is less notable than for NO.

Enrichment of desert soil elements in Takla Makan dust aerosol

During a Hungarian expedition in 1994 to arid regions of north-western China, atmospheric aerosol samples were collected in the Takla Makan Desert and on some sites in mountains surrounding the Tarim Basin. PIXE data obtained for the composition and enrichment factors of the regional aerosol clearly reflected that a heavy accumulation of salts has been formed in the closed inland basin. When compared to the regional soil composition data published by other authors, it turned out that S and Cl, showing high enrichment relative to average crust composition, are of soil origin.

Air stress and air quality indices

Against the background of the growing demand for indices suited to assess the integral air quality that is not restricted to a single air pollutant, formulations for statistical air stress indices and an impact-related air quality index (DAQx) are presented. Their sensitivity depending on emission and air mass exchange conditions is investigated by test calculations based on air pollution data from three different sites in southwest Germany characterised by different air pollution levels and one site (Szeged) in southern Hungary with a comparatively high air pollution level. The results can be explained by methodical characteristics of the indices and the local emission situation. Zusammenfassung

Selections from the history of environmental pollution, with special attention to air pollution. Part 1

Several comprehensive publications have been issued recently on the environmental pollution of past times (e.g. Tylecote, 1976; Nriagu, 1983a; Brimblecombe, 1987a; Goldstein, 1988; Healy, 1988; Brimblecombe and Pfister, 1990; Hughes, 1993; Markham, 1994; Brimblecombe, 1995; Karatzas, 2000, 2001; McNeill, 2001; Meszaros, 2001). The aim of this study is to give an overview of information on the subject – mainly related to ancient times.

Association of allergic asthma emergency room visits with the main biological and chemical air pollutants

Joint effect of biological (pollen) and chemical air pollutants on asthma emergency room (ER) visits was analyzed for Szeged region of Southern Hungary. Our database of a nine-year period (1999-2007) includes daily number of asthma emergency room (ER) visits, and daily mean concentrations of CO, PM(10), NO, NO(2), O(3) and SO(2), furthermore two pollen variables (Ambrosia and total pollen excluding Ambrosia), as well. The analysis was performed for ER visits of asthma bronchiale using two age groups (adults and the elderly) of males and females for three seasons. Factor analysis was performed in order to clarify the relative importance of the pollutant variables affecting asthma ER visits. Asthma ER visits denote notably stronger associations with the pollutants in adult male than in adult female patients both for the pollen season of Ambrosia and the pollen-free season. Furthermore, adults are substantially more sensitive to severe asthma attack than the elderly for the season of total pollen excluding Ambrosia pollen. The joint effect of the chemical and pollen variables is the highest for the asthma ER cases in the pollen season of Ambrosia, basically due to the extra impact of the total pollen excluding Ambrosia pollen and partly due to Ambrosia pollen. A nonparametric regression technique was applied to discriminate between events of ER visit-no ER visit using pollen and chemical pollutants as explaining variables. Based on multiple correlations, the strongest relationships between ER visits and pollutants are observed during the pollen-free season. The elderly group with asthma bronchiale is characterized by weaker relationships between ER visits and pollutants compared to adults. Ratio of the number of correct decisions on the events of ER visit-no ER visit is lowest for the season of total pollen excluding Ambrosia pollen. Otherwise, similar conclusions hold as those received by multiple correlations.

The effect of different transport modes on urban PM10 levels in two European cities

The aim of the study is to identify transport patterns that may have an important influence on PM10 levels in two European cities, namely Szeged in East-Central Europe and Bucharest in Eastern Europe. 4-Day, 6-hourly three-dimensional (3D) backward trajectories arriving at these locations at 1200 GMT are computed using the HYSPLIT model over a 5-year period from 2004 to 2008. A k-means clustering algorithm using the Mahalanobis metric is applied in order to develop trajectory types. Two statistical indices are used to evaluate and compare exceedances of critical daily PM10 levels corresponding to the trajectory clusters. For Bucharest, the major PM10 transport can be clearly associated with air masses arriving from Central and Southern Europe, as well as the Western Mediterranean. Occasional North African dust intrusions over Romania are also found. For Szeged, Southern Europe with North Africa, Central Europe and Eastern Europe with regions over the West Siberian Plain are the most important sources of PM10. The occasional appearance of North-African-origin dust over Hungary is also detected. A statistical procedure is developed in order to separate medium- and long-range PM10 transport for both cities. Considering the 500 m arrival height, long-range transport plays a higher role in the measured PM10 concentration both for non-rainy and rainy days for Bucharest and Szeged, respectively.

Long term climate deviations: An alternative approach and application on the Palmer drought severity index in Hungary

A new statistical test (Makra-test), applicable for long time series, is introduced to identify extended sub-periods, namely, ‘‘breaks’’, average of which is significantly higher or lower than the mean of the entire time series. In order to apply this test, normal distribution of the time series being examined is a sufficient condition. In another case, if the number of elements increases in the time series, its distribution is near normal and the test can be applied, as well (according to the Central Limit Theorem). The method is demonstrated on monthly Palmer drought severity index (PDSI) data sets, computed for five stations of East Hungary in 1901– 1999. Due to strongly recursive (auto-correlative) nature of PDSI every second month of the warm season (April, June, August and October) is analysed and treated as independent samples. Normality of the time series, which is a sufficient condition of the Makratest, is validated by Kolmogorov–Smirnov test and v 2 -test. Analysis of the PDSI time series indicates that separate treatment of the months is important not only to ensure the normality, but also to consider the existing slight seasonal differences in standard deviation and skewness of the index in the East-Hungarian region. The Makra-test delimits one or more (maximum 4) significant subperiods of the PDSI in every station and month (not considering the sub-intervals within the significant breaks, although most of them are also significant). Since the PDSI is based on monthly temperature and precipitation data that exhibit considerable inhomogeneities (Szentimry, 1999), the test is applied both for the original and the homogeneous time series. Effect of the inhomogeneity on long term variations of PDSI is strong: about the half of the significant breaks in the original time series disappear or become totally different from the time series based on homogenised data. All negative (dry) breaks of each month and station, however, occurred in more recent decades of the 20th century, according to both homogeneous and original series. � 2002 Elsevier Science Ltd. All rights reserved.