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Abstract

Modern technologies have helped us push the boundaries of geology and begin exploration of other planets. Great strides have been made in the study of Mars, which is slowly yielding up its secrets.
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Authors and Affiliations

Krzysztof Gaidzik
1
Justyna Ciesielczuk
1
Monika Fabiańska
1
Magdalena Misz-Kennan
1
Pádhraig S . Kennan
2

  1. University of Silesia in Katowice
  2. University College Dublin, Ireland
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Abstract

Dzięki współczesnym zdobyczom technologicznym przekraczamy granice niemożliwości, zaczęliśmy badać geologię innych planet. Ogromnym osiągnięciem jest eksploracja Marsa, który powoli odsłania przed ludzkością swoje tajemnice.
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Authors and Affiliations

Krzysztof Gaidzik
Justyna Ciesielczuk
Monika Fabiańska
Magdalena Misz-Kennan
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Abstract

The deepening and exploration of the loess-palaeosol section at the foot of the Kopasz Hill at Bodrogkeresztúr have been carried out to expand the existing knowledge of the Carpathian foothill palaeoenvironmental factors and their impact. The study deals with particle size analysis, organic matter and carbonate content. For the presentation of age-depth models, the OSL dates of Bodrogkeresztúr (BKT) and the 14C dates of Bodrogkeresztúr, brickyard 1 were used-, and the diagrams of the Accumulation Rates (AR) derived from them. These were compared with Mass Accumulation Rate (MAR) calculations based on OSL and 14C data from BKT and 14C data from Bodrogkeresztúr, brickyard 1. It became evident that there is a significant difference between the two sections, which may be due to the upland position, the overlap, or the wind tunnel effect. Sedimentological studies revealed coarser grain composition, however, the nearly complete absence of coarser sand fraction is also noticeable in the case of BKT. Also, the entire section is characterized by increased carbonate content due to post-sedimentation processes, recarbonization and leaching. The AR and MAR results show the difference between the suitability of different chronometric methods, indicating that the top of both sections may have been redeposited or eroded.
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Bibliography

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Authors and Affiliations

László Makó
1 2
Dávid Molnár
1 2
Péter Cseh
1 2
Pál Sümegi
1 2

  1. Department of Geology and Paleontology, University of Szeged, H-6722 Szeged, Egyetem u. 2-6, Hungary
  2. University of Szeged, Interdisciplinary Excellence Centre, Institute of Geography and Earth Sciences, Long Environmental Changes research team, H-6722 Szeged, Egyetem u. 2-6, Hungary
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Abstract

Sediment samples and hydrographic conditions were studied at 28 stations around Iceland. At these sites, Conductivity−Temperature−Depth (CTD) casts were conducted to collect hydrographic data and multicorer casts were conducted to collect data on sediment characteristics including grain size distribution, carbon and nitrogen concentration, and chloroplastic pigment concentration. A total of 14 environmental predictors were used to model sediment characteristics around Iceland on regional scale. Two approaches were used: Multivariate Adaptation Regression Splines (MARS) and randomForest regression models. RandomForest outperformed MARS in predicting grain size distribution. MARS models had a greater tendency to over− and underpredict sediment values in areas outside the environmental envelope defined by the training dataset. We provide first GIS layers on sediment characteristics around Iceland, that can be used as predictors in future models. Although models performed well, more samples, especially from the shelf areas, will be needed to improve the models in future.
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Authors and Affiliations

Alexandra Ostmann
Sarah Schnurr
Pedro Martínez Arbizu
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Abstract

This article introduces a groundwater vulnerability assessment model that utilises the fuzzy analytic hierarchy process (FAHP) in the Wadi AlHasa catchment, Jordan. The assessment takes into account both geomorphological and hydrogeological variables, employing a comprehensive methodology that integrates various parameters. To evaluate the catchment, the study employs remote sensing and Geographic Information System (GIS) techniques. The analysis of the digital elevation model enables the creation of a map illustrating the diverse geomorphology of the catchment. This geomorphology significantly influences drainage density, direction, and the spatial distribution and intensity of flash flood events. Moreover, the study develops and maps a fuzzy FAHP DRASTIC vulnerability index, which proves to be a valuable tool for assessing the susceptibility of groundwater resources to contamination. The unique feature of the index is its ability to incorporate uncertain or subjective data, providing a means to evaluate the significance of various influencing factors. This information serves as critical support for decision-making and management efforts geared towards safeguarding and enhancing groundwater resources. Within the study area, the DRASTIC vulnerability index values span from 0.08325 to 0.28409, with 18% of the site exhibiting a high vulnerability rate. Additionally, the article implements a managed aquifer recharge model (MAR), with 31% of the area falling into MAR classes. Among these, 22.1% are classified as a high MAR class, while 0.7% belong to a very high MAR class. These findings underscore the feasibility of MAR projects in regions with limited water resources.
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Authors and Affiliations

Alsharifa Hind Mohammad
1
ORCID: ORCID
Taleb Odeh
2
ORCID: ORCID
Mahmoud Abualhaijaa
1
ORCID: ORCID
Khaldoun Shatanawi
1 3
ORCID: ORCID
Maha Halalshe
1
ORCID: ORCID

  1. The University of Jordan, Water, Energy, and Environment Center, Queen Rania Street, 11942 Amman, Jordan
  2. The Hashemite University, Department of Water Management and Environment, Prince Al Hassan bin Talal College for Natural Resources and the Environment, P.O. Box 330127, 13133 Zarqa, Jordan
  3. The University of Jordan, School of Engineering, Queen Rania Street, 11942 Amman, Jordan
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Abstract

Based on data collected during an UCG pilot-scale experiment that took place during 2014 at Wieczorek mine, an active mine located in Upper Silesia (Poland), this research focuses on developing a dynamic fire risk prevention strategy addressing underground coal gasification processes (UCG) within active mines, preventing economic and physical losses derived from fires.

To achieve this goal, the forecasting performance of two different kinds of artificial neural network models (generalized regression and multi-layer feedforward) are studied, in order to forecast the syngas temperature at the georeactor outlet with one hour of anticipation, thus giving enough time to UCG operators to adjust the amount and characteristics of the gasifying agents if necessary.

The same model could be used to avoid undesired drops in the syngas temperature, as low temperature increases precipitation of contaminants reducing the inner diameter of the return pipeline. As a consequence the whole process of UGC might be stopped. Moreover, it could allow maintaining a high temperature that will lead to an increased efficiency, as UCG is a very exothermic process.

Results of this research were compared with the ones obtained by means of Multivariate Adaptative Regression Splines (MARS), a non-parametric regression technique able to model non-linearities that cannot be adequately modelled using other regression methods.

Syngas temperature forecast with one hour of anticipation at the georeactor outlet was achieved successfully, and conclusions clearly state that generalized regression neural networks (GRNN) achieve better forecasts than multi-layer feedforward networks (MLFN) and MARS models.

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Authors and Affiliations

Alicja Krzemień

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