The present study aims to determine the spatial distribution of soils with lead (Pb) content above the quality thresholds in a section of the Ogosta River valley (NW Bulgaria). The study area was ...contaminated with mine waste from the extraction and flotation of iron, lead-silver, and gold-bearing ores in the second half of the XX century. Predictive modeling was performed with the software Maximum Entropy Species Distribution Modeling (MaxEnt), Version 3.4.4, which uses machine learning algorithms and applies the maximum entropy method. The choice of predictors of contaminated soil distribution is consistent with the main factor for Pb dispersal within the valley floor - flooding from the Ogosta River. The following six parameters explained the environmental settings related to the accumulation of contaminated floodplain sediment: vertical distance to the river channel, lateral distance to the Ogosta River, terrain slope, land cover (CORINE Land Cover, 2019), morphographic units of topography, and elevation. The results represent the average values of 10 replicates of the model. We evaluated the individual models by the value of the area under the relative operating characteristic curve (AUC) and the geographic logic of the obtained results. The AUC score for the test samples was 0.666 for the soil group 1 with Pb ≤120 mg/kg, 0.782 for group 2 with Pb (120-500 mg/kg, and 0.934 for group 3 with Pb>500 mg/kg. The most significant predictors for the models are the vertical and lateral distance to the river and the slope of the terrain. Lead concentrations tend to decrease with the distance from the main river and by increasing the elevation above the river channel due to lower inundation frequency and deposition rate of polluted river sediments. The soils with a Pb concentration below the permissible threshold of 120 mg/kg cover more than 58.42% of the valley floor of the studied section, and lands with Pb content above the intervention value of 500 mg/kg occupy nearly 10.82% of the investigated territory. The selected predictors describe the distribution of highly contaminated soils well and define the range of soils with lower Pb content worse. Combining clean and contaminated soil samples into one group is considered the main reason for the poor performance of MaxEnt for soils with Pb ≤120 mg/kg. However, the results prove the model's ability to predict the spatial distribution of not only biological species but also the dispersal of hazardous substances in soil.
Light industry is one of the most important and priority industries in Bulgarian economy. It includes the production of textiles, clothing, and leather. Its development affects the state of the ...country's overall economy. Despite the numerous studies that use GIS, in Bulgaria there have been no publications on the application of statistical analysis with the use of ArcGIS software. This study aims to apply Geographic cluster analysis using ArcGIS software to analyze the light industry in Bulgaria as of 2010, 2015, and 2020. The grouping of areas by selected indicators in the present study was performed with the Grouping Analysis tool. NO_SPATIAL_CONSTRAINT was selected for the Spatial Constraints parameter and FIND_SEED_LOCATIONS - for the Initialization Method. In this case, we used the K-Means algorithm to partition features into groups. That algorithm is one of the most popular and widely used clustering algorithms in GIS applications. The areas were grouped into 10 clusters. The selection of indicators on which the clustering procedure was based, is following the generally accepted indicators for assessing the state and importance of the food industry in the structure of the economy. The following indicators were used: output for 2010, 2015, and 2020; number of employees and export earnings as of 2010, 2015, and 2020, for each administrative-territorial unit. The spatial distribution of the population, in combination with the historical and the modern economic development of the settlements, forms the regional differences in the development of the light industry in the country. The cluster analysis of certain indicators for the assessment of the light industry at the NUTS 3 level as of 2010, 2015, and 2020, shows some changes in the spatial development trends of the industry. The cluster analysis shows that there are slight spatial differences in production at the NUTS 3 level, with large consumer centers and markets being the most important.
This paper discusses the territorial organization of the chemical industry in Bulgaria. Using the ESRI ArcGIS software and applying cluster analysis, the study aims to group (cluster) the 28 ...Bulgarian districts (NUTS 3 level classification) based on produced output, persons employed, and Bulgarian lev (BGN) equivalent of foreign exchange earnings from exports for the period 2010?2020. Three reference years, 2010, 2015, and 2020, have been selected for the observed period. The general conclusion is that the chemical industry in Bulgaria is characterized by high territorial concentration. Varna was the leading district in developing the chemical industry in the observed period from 2010 to 2020, followed by Plovdiv, Ruse, and Sofia (the capital). At the other pole were the districts of Vidin, Montana, Vratsa, Pleven, Lovech, Razgrad, Silistra, Targoviste, Dobrich, Pernik, Kyustendil, Blagoevgrad, Sliven, Yambol, and Kardzhali. The findings of the research show that territorial polarization is linked with several factors that can be grouped according to their impact into four groups: 1) raw material and energy, 2) transport infrastructure and proximity to the end user, 3) state and environmental regulations, and 4) provision of skilled labor.
The rich and diverse Natural Heritage of Bulgaria is a prerequisite for the development of nature- based tourism (NBT) of a new type. The research is carried out by the implementation of the ...ecosystem approach. The results include an assessment of the natural heritage capacity to provide goods and services for the development of NBT in the Tourist Regions (TR) of Bulgaria. The results show the spatial distribution of the natural heritage sites in all nine TR in Bulgaria and their natural capacity for development of different types of NBT. There are only 37 municipalities out of 265 with not a one Natural Heritage (NH) site, and all the rest have natural resources to develop NBT. The results can be of use for the achievement of the goals for sustainable tourism by assessment of the capacity to provide recreation ecosystem services (RES).
Natural heritage (NH) includes natural features that can be described as outstanding universal value at a national level. It refers to the importance of ecosystems, biodiversity, and geodiversity for ...their existence value, and the ecosystems can be considered as the spatial units for its mapping and assessment. The ecosystem services (ES) concept provides an appropriate basis in the form of assessment and mapping methods that enable linking the state of ecosystems with human well-being. Thus, it can be used as a platform to find solutions to the problems related to the conflicts between conservation and the use of the NH. In this paper, we aim to present the process of developing a methodological framework for mapping and assessment of ecosystem services provided by the natural heritage in Bulgaria for recreation and tourism. The conceptual framework of the ecosystem-based assessment of NH in Bulgaria is based on the assumption that the generation of NH for the needs of tourism can be presented as the linkages between the natural systems and tourism in the form of ES potential, flow, and demand. The results demonstrate that the NH can be presented as a spatial phenomenon conceptualized by the flows of benefits from ecosystems to people which contribute to human well-being. The mapping and assessment procedures are fully developed for application at a national level, while for the regional and local level, few pilot studies mark some basic foundations for further development.
The present paper is dedicated to the life and scientific work of Corresponding Member of the Bulgarian Academy of Sciences Professor Kiril Mishev Ivanov because of the 15th anniversary of his death ...in 2020. The article focuses on his background and family, his education and professional career. An overview of his renowned and significant scientific publications is made.
The current research aims to apply cluster analysis using the software ArcGIS in the study of the food industry in Bulgaria for the period 2010 to 2020. The use of clustering methods is necessary to ...differentiate homogeneous groups of administrative-territorial units of NUTS 3 level on certain indicators to reveal several features and implement specific economic policies and measures for areas of a cluster and others. The grouping of the areas according to the considered indicators was done with the tool Grouping Analysis. Grouping and classification techniques are some of the most widely used methods in machine learning. We have selected No_spatial_constraint for the Spatial Constraints parameter, for grouping using the K-Means algorithm. Based on the results of the "average intergroup connection" method, the areas are grouped into 7 clusters (food industry, 2010 and 2020; food and beverage products for the period 2010-2020) and into 4 clusters (tobacco production for the period 2010-2020). The selection of indicators based on which the clusters are formed is following the generally accepted indicators for assessing the state and importance of the food industry in the structure of the economy and their information accessibility. The following indicators were used output for 2010 and 2020, employees for 2010 and 2020, and export earnings for 2010 and 2020 for the given territorial unit The territorial distribution of the population, in combination with the historical and modern economic development of the settlements, forms the regional differences in the development of the food industry in the country. The cluster analysis of certain indicators for the assessment of the food industry at the NUTS 3 level for 2010 and 2020 shows some change in the trends in the territorial development of the industry. The cluster analysis shows that there are slight territorial differences at the NUTS 3 level in food production, with large consumer centers and markets being the most important. In the activities of tobacco and beverage production, the territorial differences are minimal.
•Magnetometric and geochemical study of urban park soils reveal anthropogenic influence.•Spatial maps of magnetic parameters delineate major functional zones in the urban park.•Data variability due ...to traffic, pedogesis, lithogenic plus anthropogenic organic waste inputs.•Novel mineral–magnetic Indicator (MAG) for soil quality evaluation defined.•Field magnetic susceptibility reflects overall anthropogenic load to urban park soils.
Ecosystem surveys reveal the benefits to society, provided by the natural environment, which in turn is chiefly regulated by the geodiversity. Thus, physico-chemical processes regulating the solid rock/sediment response to environmental changes comprise an important part in the assessment of natural ecosystems. Environmental magnetism provides a wide set of field and laboratory data able to discover natural and anthropogenic processes affecting different environmental compartments. Despite this, geosciences and environmental magnetism in particular, are under-represented in ecosystem assessment tools due to the lack of unified and clearly articulated application template. In this study, we propose a new mineral magnetic indicator of soil’s quality, based on detailed appraisal of field- and laboratory mineral magnetic characteristics of a collection of 453 urban topsoil samples. Field magnetic susceptibility (Kfield) and laboratory measurements of magnetic parameters revealed that soil magnetism reflects sensitively soils affected by vehicle traffic and park’s alleys foot load from semi-natural soil. Geochemical analyses of the content of Potentially Toxic Elements (PTEs) on a sub-set of samples was used for magnetic data validation. Correlation analysis showed strong positive link between magnetic parameters and the main PTEs, the strongest being obtained between magnetic susceptibility and the complex pollution load index (PLI). Factor analysis suggested that three factors account for the 74% of data variability. They were assigned to: 1) traffic emissions, 2) pedogenic contribution and 3) lithogenic input plus anthropogenic organic waste additions. Novel mineral magnetic Indicator (MAG) was defined, combining information on composition, concentration and grain size of ferrimagnetic iron oxides, using scored contributions from five magnetic parameters and grain size sensitive ratios. Evaluation of the spatial MAG map showed its suitability as a complex indicator of soils’ contamination with PTEs. Kfield reflected sensitively overall anthropogenic load not necessarily related to PTEs contamination but also to foot trampling and application of fertilizers.
The determination and modelling of the territory is common scientific instrument for presentation of the state of the nature and human systems. The present research is based on the morphological and ...hydrological peculiarities in the river catchment. It observed of the Danube coastal zone in Bulgaria sector of the river. The differentiation and determination of the coastal area is key element in the process of the management of the territory and development of the regions. The general results of the research are related with differentiation and determination of the Danube coastal zone in Bulgaria, based on morphographic peculiarities of the region. The key element of the investigation is outlining of the south border line of the coastal zone. The second aspect of the investigation is generation of basic spatial model of the Danube coastal zone in Bulgaria. Using and applying GIS technologies is leading part of the research. Geographical and geospatial analysis of the coastal zone give opportunities for determination of three basic substructures - lowlands, regions of river mouths, including flooding areas and plateaus. They are base for the differentiation and classification of the landscape diversity of the region. Landscape diversity of the coastal zone can be used for the determination of the general directions in the development of the region. The clear definition and determination of coastal zone is important stage in the process of evaluation of the potential of Danubian region in Bulgaria. The applying aspects of the research are related with sustainable use of the recourses and nature protection in the regions. The results of the research can be use in the decision-making processes and management of different activities and politics in the region.
This study aimed to reveal the dependence of the spatial distribution of heavy metals in soil on the morphography of the Lower Danube floodplain in the Ostrovska Lowland in Bulgaria. The field ...campaign was conducted in 2017, and the concentration of Zn, Ni, Pb and Cr were measured in the fine fraction (<0.063 mm) of 10 soil samples using X-ray fluorescence analysis. The average content of Cr in the topsoil (0-20 cm) was 127 mg/kg ranging between 98 - 171 mg/kg. It was followed by Zn - 81 mg/kg (60 - 128 mg/kg), Ni - 54 mg/kg (40 - 85 mg/kg) and Pb - 30 mg/kg (18 - 53mg/kg). The metal levels exceeded the mean values for floodplain sediment in Europe in most samples. Chromium violated the quality target threshold for sediment applied by the Joint Danube Surveys in 90% of the samples and Ni in 60%. The concentrations of all the heavy metals except for Cr showed a relationship with the geomorphographic units. The elements Zn, Pb and Ni tended to accumulate mostly in the marshes and less in the active floodplain and sandy ridges. A negative correlation between vertical distance to the Danube and the concentration of elements was found for Zn (R2 0.73), Pb (R2 0.66) and Ni (R2 0.51). The results confirmed the more intensive accumulation of the three metals in the lowest parts of the floodplain, where the fine sediment was deposited during floods. The individual pattern of the spatial distribution of Cr indicated a specific source of origin of the element. The landforms had little control over the dispersal of the element in the floodplain of the Lower Danube. The obtained results showed that marshes were most threatened by metal contamination if flooded, and this should be consi dered if restoration of wetlands is conducted in the lowland. In contrast, the sandy ridges and high floodplain were naturally protected against the accumulation of hazardous substances via inundation by the Danube.
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