Search Results (5)

High levels of sulfur dioxide (SO₂) due to human activities pose a serious air pollution issue in China, especially in urban agglomerations. However, limited research has investigated the impact of anthropogenic emissions on higher SO₂ concentrations in urban regions compared to rural areas in China. Here, we analyzed the trends in SO₂ concentrations from 1980 to 2021 in China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) dataset. SO₂ column concentrations from the Copernicus Atmosphere Monitoring Service (CAMS) and the Ozone Monitoring Instrument (OMI) during the years 2007–2021 were also examined for validation and comparison purposes. Eight representative areas, including four urban regions (Pearl River Delta [PRD], Beijing-Tianjin-Hebei [BTH], Yangtze River Delta [YRD], and Sichuan Basin [SCB]) and four rural regions (Northeast Region [NER], Mongolian Region [MR], West Region [WR], and Tibetan Plateau Region [TR]) were selected for the analysis. Overall, a significant but fluctuating increase in SO₂ concentrations over China was observed during 1980–2021. During 1980–1997 and 2000–2010, there was an increase in SO₂ concentration, while during 1997–2000 and 2010–2021, a decreasing trend was observed. The average increase in SO₂ concentration was approximately 16 times higher in urban regions than in the rural background. We also found that SO₂ dynamics were highly associated with expansion of urban areas, population density, and gross domestic product. Nonetheless, since 2007, SO₂ concentrations have exhibited a downward trend, which is mainly attributed to the air pollution policies implemented by the Chinese government. Our findings highlight the need for further studies on the impact of SO₂ on regional climate change in China. Full article

Information on historical flood levels can be communicated verbally, in documents, or in the form of flood marks. The latter are the most useful from the point of view of public awareness building and mathematical modeling of floods. Information about flood marks can be found in documents, but nowadays, they are starting to appear more often on the Internet. The only problem is finding them. The aim of the presented work is to create a new model for classifying Internet sources using advanced text analysis (including named entity recognition), deep neural networks, and spatial analysis. As a novelty in models of this type, it was proposed to use a matrix of minimum distances between toponyms (rivers and towns/villages) found in the text. The resulting distance matrix for Poland was published as open data. Each of the methods used is well known, but so far, no one has combined them into one ensemble machine learning model in such a way. The proposed SD-NER model achieved an F1 score of 0.920 for the binary classification task, improving the model without this spatial module by 17%. The proposed model can be successfully implemented after minor modifications for other classification tasks where spatial information about toponyms is important. Full article

The Ipoly Valley is a natural habitat along the Ipoly River, only slightly affected by water management; therefore, this is an especially sensitive area and reflects well the vegetation changes in the driest (2020) and wettest (2010) years. The study’s aim is to identify natural changes within habitats and the evaluation of habitat types’ boundaries. For the study, a hand-held GPS device was applied on-site. The habitat identification is based on the General National Habitat Classification System (Á-NÉR). In addition to on-site data, Sentinel-2A satellite data were used to compare different extreme years 2020 and 2021—changes in different habitat patches using different vegetation indices. A change in precipitation causes shifts in the vegetation, this is shown on a map. As we predicted, decreasing the precipitation results in a decrease of the area of wet habitat patches. The satellite image shows a more accurate picture of the real location of the associations, which is important for long-term research. In addition, we can get accurate data on the situation of areas (roads and paths) affected by anthropogenic factors. Full article

The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous. Full article

The purpose of the paper is to test forecasting of the sediment transport process, taking into account two main uncertainties involved in sediment transport modeling. These are: the lack of knowledge regarding future flows, and the uncertainty with respect to which sediment transport formula should be chosen for simulations. The river reach chosen for study is the outlet part of the Ner River, located in the central part of Poland. The main characteristic of the river is the presence of an intensive morphodynamic process, increasing flooding frequency. The approach proposed here is based on simulations with a sediment-routing model and assessment of the hydraulic condition changes on the basis of hydrodynamic calculations for the chosen characteristic flows. The data used include Digital Terrain Models (DTMs), cross-section measurements, and hydrological observations from the Dabie gauge station. The sediment and hydrodynamic calculations are performed using program HEC-RAS 5.0. Twenty inflow scenarios are of a 10-year duration and are composed on the basis of historical data. Meyer-Peter and Müller and Engelund-Hansen formulae are applied for the calculation of sediment transport intensity. The methodology presented here seems to be a good tool for the prediction of long-term impacts on water surface profiles caused by sediment deposition and erosion. Full article