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Earth and environmental sciences cover all planetary and Earth science aspects, including solid Earth processes, development of Earth, environmental issues, ecology, marine and freshwater systems, as well as the human interaction with these systems.
Earth and Environmental Sciences
The estimation of environmental risk caused by pollution with potentially toxic elements (PTE) is usually carried out using the (3+1) step sequential extraction procedure suggested in 1993 by the Community Bureau of Reference (BCR). In the 1st step the water-soluble, exchangeable and carbonate-bound element content is extracted with acetic acid. In 2002 a fractionation procedure based on the application of supercritical CO2, subcritical H2O and of a mixture of subcritical H2O/CO2 was proposed, which allowed the water-soluble and carbonatebound element contents to be extracted separately from sediment or soil samples weighed into the preparative column of a supercritical fluid extractor and diluted with quartz sand in a mass ratio of 1:20. The aim of the present study was to develop a new reduced-size column construction with which this dilution rate could be decreased to 1:2. A kinetic study was performed to determine the extraction time necessary for samples with different carbonate contents and the extracted element contents were compared to the results of the BCR sequential procedure on the same samples. It was established that fractionation using the reduced-size column may be a rapid way to obtain more reliable information on the easily mobilizable (watersoluble and carbonate-bound) PTE content of soils and sediments than was previously available to supplement BCR fractionation.
The size of the arable land is constantly decreasing all over the world due to severe anthropogenic disorders. Plant production therefore has to be adapted to changing environmental conditions along with the proper selection of crop varieties and the application of sustainable environmental technologies which also consider economic aspects. The investigations were carried out in the Westsik long-term fertilization experiment near Nyíregyháza, East Hungary, which was set up in 1929 (89 years ago). Alternative forms of nutrient supplies (A) (green manure, straw with and without fermentation, organic fertilizer with and without inorganic fertilizer supplements) were used in different crop rotations. The test plant was potato (Solanum tuberosum L.) and the soil type sand with a low humus content (Arenosols). A further long-term experiment is located on calcareous chernozem soil (Chernozems) in Debrecen (set up in 1983, 35 years ago). In one part of this experiment, organic farming (OF) has been carried out with a pea, winter wheat and maize crop rotation for over 15 years with no inorganic fertilization. In another block in this experiment, changes in soil properties as a result of the medium and high doses of fertilizers applied in intensive farming (I) were evaluated with a maize (Zea mays L.) monoculture as the test plant.
The results obtained with alternative nutrient supplies (green manure, fermented and unfermented straw, farmyard manure, fertilization) proved that the soil organic carbon content increased to varying degrees in humus-poor, acidic sand soil. The organic matter content of the soils increased in response to the treatments, contributing to a significant enhancement in soil microbial parameters (MBC, saccharase, dehydrogenase and phosphatase enzyme activities).
The carbon dioxide production and saccharase enzyme activity in organic plots (OF) were significantly lower than in intensively farmed (I) soils. At the same time, in the case of organic farming (OF) the microbial biomass carbon, phosphatase and dehydrogenase activity were significantly higher in OF plots than in I plots. Compared to the control soil, MBC was 7-8 times higher in organic plots and 1.3-3.8 times higher in intensive plots.
Organic farming on chernozem soil generally resulted in higher microbial activity (MBC, phosphatase, saccharase and dehydrogenase enzyme activity) than in either intensively farmed chernozem or in the case of alternative farming (A) on sandy soil.
A small-plot long-term field fertilization experiment was set up in 2011 with willow (Salix triandra x Salix viminalis ’Inger’) grown as an energy crop in Nyíregyháza, Hungary. The brown forest soil was treated three times (in June 2011, May 2013, May 2016) with municipal biocompost (MBC), municipal sewage sludge compost (MSSC) or willow ash (WA), and twice (June 2011, May 2013) with rhyolite tuff (RT). In late May – early June 2016 urea (U) and sulphuric urea (SU) fertilizers were also applied to the soil as top-dressing (TD). These fertilizers and amendments were also applied to the soil in 2016 in the combinations; MBC+SU, RT+SU, WA+SU and MSSC+WA. All the treatments were repeated four times. In July 2016 the highest nitrogen concentrations in willow leaves were measured in the U (3.47 m/m%) and SU (3.01 m/m%) treatments, and these values were significantly higher than the control (2.46 m/m%). An excess of nitrogen considerably reduced the Zn uptake of the leaves, with values of 39.5 μg g-1 in the U treatment, 53.4 μg g-1 in the SU treatment, and 63.5 μg g-1 in the control. All other amendments or TDs, except for WA, enhanced the specific potassium concentrations in willow leaves compared to the control. No significant quantities of toxic elements (As, Ba, Cd, Pb) were transported from soil amendments or TDs to the willow leaves. In July 2016 the most intensive leaf chlorophyll fluorescence was observed in the MSSC and MSSC+WA treatments.
The Mecsekalja Zone is a strike-slip fault zone that plays an essential role in the structural framework of South Transdanubia. The metamorphic and deformation history of the crystalline basement of the Mecsekalja Zone has been determined thus far based exclusively on a few surface outcrops and near-surface samples. The Szentlőrinc-1 (Sztl-1) well penetrated the shear zone at a depth of approximately 2 km and brought drilling chips from a 220-m-long section of the basement to the surface. The aim of this study is to reconstruct the metamorphic and deformation history of the Mecsekalja Zone along the Sztl-1 well using these tiny samples. These drilling chips consist of single mineral and rock pieces that are dominated by quartz grains. This study concentrates on the detailed analysis of quartz grains utilizing the physical conditions of metamorphic evolution as well as ductile and brittle deformation to determine the chemical composition and rheology of quartz. The evolution of the studied area can be determined by evaluating analytical data measured by Raman spectroscopy, LA-ICP-MS, and FTIR spectroscopy. These data suggest that the maximum temperature of the early regional metamorphism was 500–575 °C, the temperature of the subsequent ductile deformation was below 500 °C including recrystallization occurred between 400 and 475 °C. During the structural evolution of the study area, two independent, single deformation events occurred. The earlier ductile deformation event was followed by a brittle event through the reactivation of the former ductile shear zone. Our model is in accordance with previous results concerning the evolution of the Mecsekalja Zone, thus, the shear zone, with an identical evolution, can be extended toward the southwest at least to the Sztl-1 well.
The Late Valanginian–Early Hauterivian iron ore deposit and related formations at Zengővárkony (Mecsek Mts., South Hungary) provided a relatively rich microfauna of foraminifera, crustacean microcoprolites, and sponge spicules. Benthic foraminifera are recognized in decreasing abundance: Glomospira cf. gordialis (Jones and Parker 1860), Lenticulina sp., Spirillina sp., Nodosaria sp., Epistomina sp., and Trocholina sp. A Hedbergella sp. indicates the presence of planktonic foraminifera around the ore deposit. Besides this microfauna, sponge spicules (diactine-type criccorhabds and anactine-type rhax forms) are first recorded from this environment. Rock-forming quantities of various ichnospecies of crustacean microcoprolites are recorded. Favreina hexaochetarius, Palaxius tetraochetarius, and Palaxius decaochetarius isp. provided statistically evaluated quantities in thin sections, which point to a complete crustacean ichnofauna from juveniles to adults. Four different microfossil assemblages are recognized from the Apátvarasd Limestone Fm: (a) Glomospira-dominated foraminifer assemblage, (b) diverse crustacean microcoprolite assemblage dominated by Palaxius, (c) monotypic Favreina assemblage, and (d) diverse sponge-dominated assemblage. These assemblages are similar to that of the Recent Aegean Sea hydrothermal field communities. The remains of an undetermined crinoid from dissolved rock sample may indicate a vivid sea-bottom environment.
The emission of particulate matter from agricultural sources is a worldwide environmental issue due to health concerns.
The main factors influencing PM10 emission from crop production are the origin of particles, the physical and chemical properties of soils, meteorological conditions, and the mechanical impacts of farm operations. Several studies have been made to determine PM10 emission factors for tillage operations, but these emission factors varied depending on soil properties, especially soil texture and water content, and environmental conditions (e.g. relative humidity, and variability in wind speed and direction). This is why the use of a single emission factor for a given tillage operation is inadequate.
To estimate the yearly amount of PM10 emitted from agricultural soils and crop production, emissions originating from different sources at different temporal division must be summarized. Because 56 % of the total territory of Hungary is cropland, relatively high PM10 emission occurs from crop production and agricultural soils. If this is to be reduced, research should focus on the identification of soil and environmental properties related to PM10 emission on characteristic Hungarian soils.
Climate change is expected to have a vigorous impact on soils and ecosystems due to elevated temperature and changes in precipitation (amount and frequency), thereby altering biogeochemical and hydrological cycles. Several phenomena associated with climate change and anthropogenic activity affect soils indirectly via ecosystem functioning (such as higher atmospheric CO2 concentration and N deposition). Continuous interactions between climate and soils determine the transformation and transport processes. Long-term gradual changes in abiotic environmental factors alter naturally occurring soil forming processes by modifying the soil water regime, mineral composition evolution, and the rate of organic matter formation and degradation. The resulting physical and chemical soil properties play a fundamental role in the productivity and environmental quality of cultivated land, so it is crucial to evaluate the potential outcomes of climate change and soil interactions. This paper attempts to review the underlying long-term processes influenced by different aspects of climate change. When considering major soil forming factors (climate, parent material, living organisms, topography), especially climate, we put special attention to soil physical properties (soil structure and texture, and consequential changes in soil hydrothermal regime), soil chemical properties (e.g. cation exchange capacity, soil organic matter content as influenced by changes in environmental conditions) and soil degradation as a result of longterm soil physicochemical transformations. The temperate region, specifically the Carpathian Basin as a heterogeneous territory consisting of different climatic and soil zones from continental to mountainous, is used as an example to present potential changes and to assess the effect of climate change on soils. The altered physicochemical and biological properties of soils require accentuated scientific attention, particularly with respect to significant feedback processes to climate and soil services such as food security.
The traditional Hungarian method for determining soil phosphorus (P) status is ammonium-lactate acetic acid (AL) extraction. AL is an acidic solution (buffered at pH 3.75), which is also able to dissolve P reserves, so there is a need for extraction methods that also characterize the mobile P pool.
0.01 M CaCl2-P is considered to directly describe available P forms, because the dilute salt solution has more or less the same ionic strength as the average salt concentration in many soil solutions.
The amount of AL-P may be two orders of magnitude greater than that of CaCl2-P. Previous studies suggested that the relationship between AL-P and CaCl2-P was influenced by soil parameters. Regression analysis between AL-P and CaCl2-P showed medium or strong correlations when using soils with homogeneous soil properties, while there was a weak correlation between them for soils with heterogeneous properties.
The objective of this study was to increase the accuracy of the conversion between AL-P and CaCl2-P, by constructing universal equations that also take soil properties into consideration.
The AL-P and CaCl2-P contents were measured in arable soils (n=622) originating from the Hungarian Soil Information and Monitoring System (SIMS). These soils covered a wide range of soil properties.
A weak correlation was found between AL-P and CaCl2-P in SIMS soils. The amounts and ratio of AL-P and CaCl2-P depended on soil properties such as CaCO3 content and texture. The ratio of AL-P to CaCl2-P changed from 37 in noncalcareous soils to 141 on highly calcareous soils. CaCl2-P decreased as a function of KA (plasticity index according to Arany), which is related to the clay content, while the highest AL-P content was found on loam soils, probably due to the fact that a high proportion of them were calcareous.
The relationships between AL-P, CaCl2-P and soil properties in the SIMS dataset were evaluated using multiple linear regression analysis. In order to select the best model the Akaike Information Criterion (AIC) was used to compare different models. The soil factors included in the models were pHKCl, humus and CaCO3 content to describe AL-P, and KA, CaCO3 content and pHKCl to describe CaCl2-P. AL-P was directly proportional to pHKCl, humus and CaCO3 content, while CaCl2-P was inversely proportional to KA, CaCO3 content and pHKCl. The explanatory power of the models increased when soil properties were included. The percentage of the explained variance in the AL-P and CaCl2-P regression models was 56 and 51%, so the accuracy of the conversion between the two extraction methods was still not satisfactory and it does not seem to be possible to prepare a universally applicable equation. Further research is needed to obtain different regression equations for soils with different soil properties, and CaCl2-P should also be calibrated in long-term P fertilization trials.
One option for adaptation to climate change is to grow a wider variety of plant species. Sorghum (Sorghum bicolor (L.) Moench) is known to tolerate unfavourable environmental conditions, so it may be feasible to grow it on areas with extreme conditions to replace other species such as maize. Nowadays, spatial decision supporting systems primarily support the crop production process rather than crop structure adjustment. In this study, potential sorghum production sites in the Great Hungarian Plain were selected based on soil characteristics including genetic soil type, parent material, physical soil type, clay composition, water management, pH, organic matter content, topsoil thickness and fertility, as well as climatic data, particularly precipitation. For all the parameters the aim was to find the extreme values at which sorghum, which is less sensitive than maize, may still give an acceptable yield. By combining map layers of soil characteristics, it could be concluded that although the soil is suitable for sorghum on 40.46% of the Great Hungarian Plain, maize is generally a better choice economically. On the other hand, the soil conditions on 0.65% of the land are still suitable for sorghum but unfavourable for maize. As regards the precipitation demand of sorghum, May is the critical period; on 698,968 ha the precipitation required for germination was only recorded once in the period 1991-2010, so these areas cannot be considererd for sorghum. As a consequence, in an alternative crop rotation system sorghum could be competitive with maize, but both the soil and climate conditions and the demands of the crop need to be assessed. The lack of precipitation in critical phenophases significantly decreases the area where maize can survive. Sorghum, however, may produce an acceptable yield, as it is a drought-resistant species.
Assessing the uncertainty in reservoir performance is a necessary step during the exploration phase. To examine the uncertainty in flow response, a large set of realizations must be processed. There are several stochastic geostatistical algorithms capable of simulating multiple equiprobable realizations. Although these can show us the possible realities highlighting the spatial uncertainty, their handling is time- and CPU-consuming during the later processes, such as flow simulations. Consequently, only a small number of realizations can be post-processed in industrial practice. The purpose of this work is to develop a method, which will reduce the huge number of realizations in a way that the remaining ones retain the spatial uncertainty of a reservoir’s flow behavior, as would be demonstrated by a larger set of realizations. To solve this problem, ranking methods can be applied. Traditional ranking techniques, such as probability selection, are highly dependent on the applied static properties. In this paper, an alternative selection method is parameterized for measuring the pairwise dissimilarity between geostatistical models, with a distance function based on the hydrodynamic properties of the hydrocarbon reservoirs. The effectivity of the method is highly dependent upon the selected criteria. Thus, the distance function refers to the flow responses and allows visualizing the space of uncertainty through multidimensional scaling. A kernel transformation of the MDS data set is required to obtain a feature space where the K-means algorithm can discover non-linear structures in the basic data set. The final step of the method is the selection of the Earth models closest to the cluster centers. This tool allows for the selection of a subset of representative realizations, containing similar properties to the larger set.
