TY - JOUR AU - Kiss, Emőke AU - Mester, Tamás AU - Balla, Dániel TI - A klímaaggodalmak és környezetbarát viselkedés kapcsolatának és jellemzőinek feltárása Debrecenben JF - TERÜLETI STATISZTIKA J2 - TERÜLETI STATISZTIKA PY - 2024 SN - 0018-7828 UR - https://m2.mtmt.hu/api/publication/34801314 ID - 34801314 AB - A klímaváltozás kihívásainak és alkalmazkodási lehetőségeinek elemzésekor a klímaaggodalmak és a környezetbarát viselkedés kapcsolatának kérdésköre is gyakran felvetődik. A 2020-ban kitört COVID-19 világjárvány elterelte az emberek figyelmét a klímaváltozásról, így a lakosság klímaaggodalmainak feltárása nagyon fontossá vált ebben az időszakban. Kutatásunkban mintaterületként egy kelet-közép-európai várost, Magyarország második legnépesebb települését, Debrecent, Hajdú-Bihar vármegyeszékhelyét választottuk. Munkánk során kérdőíves felmérést végeztünk 2020-ban a lakosok körében (N=200). Tanulmányunk fő célja a klímaaggodalmak és a környezetbarát viselkedés kapcsolatának vizsgálata és feltárása volt. A klímaaggodalom, a környezetbarát viselkedés és a kiválasztott prediktorok közötti kapcsolat szorosságát, erősségét és intenzitását korrelációelemzéssel vizsgáltuk, a regresszióelemzés a kiválasztott változók hatását és kapcsolatát vizsgálta. Kimutattuk, hogy a lakosok Klímaaggodalom Indexe (KAI) és Környezetbarát Viselkedés Indexe (KVI) magas. Kutatásunkban a korrelációelemzés egyik legfontosabb eredménye, hogy a KAI és KVI között egyáltalán nem találtunk szignifikáns kapcsolatot, tehát a kettő nem függött össze mintánkban. Másik fontos eredményük, hogy a KVI és a Kockázatérzékelés Indexek (KI) között sem mutatható ki szignifikáns kapcsolat, ugyanakkor a KAI és a KI között szignifikánsan pozitív irányú, közepes erősségű kapcsolatot fedeztünk fel. A többváltozós lineáris regresszióelemzésekben a demográfiai faktorok csak enyhén mérsékelték a változók hatását a KAI-ra és KVI-re. Eredményeink alátámasztják azokat a tanulmányokat, amelyek szerint az egyének klímaaggodalma nem vezet következetesen környezetbarát magatartáshoz. LA - Hungarian DB - MTMT ER - TY - JOUR AU - Madi, Heba AU - Kozma, Gábor AU - Szabó, György Emőd TI - Green concrete materials selection for achieving circular economy in residential buildings using system dynamics JF - CLEANER MATERIALS J2 - CLEANER MATERIALS VL - 11 PY - 2024 PG - 19 SN - 2772-3976 DO - 10.1016/j.clema.2024.100221 UR - https://m2.mtmt.hu/api/publication/34657898 ID - 34657898 LA - English DB - MTMT ER - TY - JOUR AU - Kovács, András Donát AU - Farkas, Jenő Zsolt AU - Vasárus, Gábor László AU - Balla, Dániel AU - Kiss, Emőke TI - Climate policy contradictions in light of the policy paradigms - the case of the Visegrád Countries JF - ENVIRONMENTAL SCIENCE & POLICY J2 - ENVIRON SCI POLICY VL - 154 PY - 2024 SP - 1 EP - 10 PG - 10 SN - 1462-9011 DO - 10.1016/j.envsci.2024.103689 UR - https://m2.mtmt.hu/api/publication/34566196 ID - 34566196 N1 - First online Feb 8. Published: April 2024 LA - English DB - MTMT ER - TY - JOUR AU - Hateffard, Fatemeh AU - Steinbuch, L. AU - Heuvelink, G.B.M. TI - Evaluating the extrapolation potential of random forest digital soil mapping JF - GEODERMA J2 - GEODERMA VL - 441 PY - 2024 SN - 0016-7061 DO - 10.1016/j.geoderma.2023.116740 UR - https://m2.mtmt.hu/api/publication/34549041 ID - 34549041 N1 - Export Date: 31 January 2024 CODEN: GEDMA Correspondence Address: Steinbuch, L.; Soil Geography and Landscape group, Netherlands; email: luc.steinbuch@wur.nl AB - Spatial soil information is essential for informed decision-making in a wide range of fields. Digital soil mapping (DSM) using machine learning algorithms has become a popular approach for generating soil maps. DSM capitalises on the relation between environmental variables (i.e., features) and a soil property of interest. It typically needs a training dataset that covers the feature space well. Mapping in areas where there are no training data is challenging, because extrapolation in geographic space often induces extrapolation in feature space and can seriously deteriorate prediction accuracy. The objective of this study was to analyse the extrapolation effects of random forest DSM models by predicting topsoil properties (OC, clay, and pH) in four African countries using soil data from the ISRIC Africa Soil Profiles database. The study was conducted in eight experiments whereby soil data from one or three countries were used to predict in the other countries. We calculated similarities between donor and recipient areas using four measures, including soil type similarity, homosoil, dissimilarity index by area of applicability (AOA), and quantile regression forest (QRF) prediction interval width. The aim was to determine the level of agreement between these four measures and identify the method that had the strongest agreement with common validation metrics. The results indicated a positive correlation between soil type similarity, homosoil and dissimilarity index by AOA. Surprisingly, we observed a negative correlation between dissimilarity index by AOA and QRF prediction interval width. Although the cross-validation results for the trained models were acceptable, the extrapolation results were unsatisfactory, highlighting the risk of extrapolation. Using soil data from three countries instead of one increased the similarities for all measures, but it had a limited effect on improving extrapolation. Also, none of the measures had a strong correlation with the validation metrics. This was particularly disappointing for AOA and QRF, which we had expected to be strong indicators of extrapolation prediction performance. Results showed that homosoil and soil type methods had the strongest correlation with validation metrics. The results for this case study revealed limitations of using AOA and QRF as measures of extrapolation effects, highlighting the importance of not relying on these methods blindly. Further research and more case studies are needed to address the effects of extrapolation of DSM models. LA - English DB - MTMT ER - TY - JOUR AU - Hamma, Bellal AU - Alodah, Abdullah AU - Bouaicha, Foued AU - Bekkouche, Mohamed Faouzi AU - Barkat, Ayoub AU - Hussein, Enas E. TI - Hydrochemical assessment of groundwater using multivariate statistical methods and water quality indices (WQIs) JF - APPLIED WATER SCIENCE J2 - APP WATER SCI VL - 14 PY - 2024 IS - 2 SN - 2190-5487 DO - 10.1007/s13201-023-02084-0 UR - https://m2.mtmt.hu/api/publication/34541959 ID - 34541959 AB - Groundwater quality assessment is crucial for the sustainable management of water resources in arid regions, where groundwater is the primary source of water supply and increasing demand raises concerns. The study area in Southwest Algeria relies heavily on groundwater as a source of water supply, and the increasing demand for freshwater raises concerns about the quality of groundwater. To assess the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region, multivariate statistical methods, geochemical modeling and water quality indices were employed. The study revealed that the groundwater samples could be classified into four water groups using hierarchical cluster analysis Q mode (HCA), namely Ca–Mg–HCO 3 , Ca–Mg–Cl–SO 4 , Ca–SO 4 and Na–Cl. Factor analysis was used to identify the main factors controlling the study area’s hydrochemical processes. The results indicated that water–rock interaction, reverse ion exchange and anthropogenic pollution were the main hydrochemical processes affecting groundwater chemistry. The water quality index indicated that the groundwater was suitable for human consumption, with only 2.32% of the samples being unsuitable. Additionally, the groundwater was suitable for agricultural use, but salinity control was necessary. The saturation index values showed that the groundwater was supersaturated with aragonite, calcite, dolomite, anhydrite and gypsum, and undersaturated with halite. Ca-smectite, Mg-smectite and kaolinite were identified as the primary processes controlling the chemical composition of groundwater. The application of multivariate statistical methods, geochemical modeling and water quality indices provided a comprehensive understanding of the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region. The findings of the study can serve as a useful basis for future studies on groundwater quality assessment in the region. LA - English DB - MTMT ER - TY - JOUR AU - Zakaria, Rahal AU - Abderrahmane, Khechekhouche AU - Chekima, Hamza AU - Barkat, Ayoub AU - Smolyanichenko, Alla Sergeevna TI - Phytotoxicity Assessment of Oat Seeds Using Purified Water Treated with Palm Leaves and Date Pits JF - POLLUTION J2 - POLLUTION VL - 10 PY - 2024 IS - 1 SP - 201 EP - 209 PG - 9 SN - 2383-451X UR - https://m2.mtmt.hu/api/publication/34531871 ID - 34531871 LA - English DB - MTMT ER - TY - JOUR AU - Kovács, Tibor AU - Vasvári, Mária TI - Az „alföldiség” karakterisztikája a Nagykunságban. Kisújszállási esettanulmány JF - CITY.HU: VÁROSTUDOMÁNYI SZEMLE J2 - CITY.HU VL - 3 PY - 2023 IS - 2 SP - 67 EP - 92 PG - 26 SN - 2786-4022 UR - https://m2.mtmt.hu/api/publication/34670498 ID - 34670498 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Vass, Róbert TI - A bodrogzugi nyílt ártér tájhasználatának változása JF - FÖLDRAJZI KÖZLEMÉNYEK J2 - FÖLDRAJZI KÖZLEMÉNYEK VL - 147 PY - 2023 IS - 2 SP - 133 EP - 142 PG - 10 SN - 0015-5411 DO - 10.32643/f k.147.2.5 UR - https://m2.mtmt.hu/api/publication/34575858 ID - 34575858 AB - In this work, I determined the roughness conditions of the flood plain in an area of 523 ha in the southern part of Bodrogzug based on aerial photographs from 1965 and 2016. The inspiration for conducting the tests was the three recordings that were made of the area at the beginning and in the middle of the 20th century, and in the early 2000s. Based on the two previous recordings, the roughness of the area may have been much smaller than today due to the short grass pastures and the small amount of woody vegetation. To determine the roughness values, I used the categories developed by CHOW V. T. (1959) and NÉMETH E. (1959). The plant cover values recorded at the two times show significant differences. The proportion of very dense forests increased greatly, with the weighted roughness increasing by two and a half times in 2016 compared to 1965. This significantly reduces the speed of flood waters, which can lead to gradual siltation of the area. At the same time, the direction of landscape development is developing favourably, as the area's biodiversity is increasing. LA - Hungarian DB - MTMT ER - TY - JOUR AU - Zakaria, Rahal AU - Abderrahmane, Khechekhouche AU - Barkat, Ayoub AU - Smolyanichenko, Alla Sergeevna AU - Hamza, Chekima TI - Adsorption of Sodium in an Aqueous Solution in Activated Date Pits JF - INDONESIAN JOURNAL OF SCIENCE AND TECHNOLOGY J2 - INDON J SC TECH VL - 8 PY - 2023 IS - 3 SP - 397 EP - 412 PG - 16 SN - 2528-1410 UR - https://m2.mtmt.hu/api/publication/34565431 ID - 34565431 LA - English DB - MTMT ER - TY - JOUR AU - Balla, Dániel AU - Kiss, Emőke AU - Zichar, Marianna AU - Mester, Tamás TI - Vízminőségi monitoring adatok feldolgozása és publikálása WebGIS támogatással = Geoprocessing and publishing water quality monitoring data with WebGIS support JF - GEODÉZIA ÉS KARTOGRÁFIA J2 - GEODÉZIA ÉS KARTOGRÁFIA VL - 75 PY - 2023 IS - 6 SP - 4 EP - 9 PG - 6 SN - 0016-7118 DO - 10.30921/GK.75.2023.6.1 UR - https://m2.mtmt.hu/api/publication/34448328 ID - 34448328 LA - Hungarian DB - MTMT ER -