Environmental Protection and Disaster Risks (EnviroRisks 2024)

Among natural disasters, earthquakes dominate regarding their social and economic effects on human life and the urban environment. One of the main objectives of the present study is to integrate the basic geo-datasets and to assess the seismic hazard using GIS to provide a basis for disaster management of the city of Veliko Tarnovo—the most Bulgarian city that in 2019 was declared the historical and spiritual capital of Bulgaria. Risk assessment and its associated management are the most effective approach to estimate the impact of natural hazards on the city of Veliko Tarnovo that is situated in an area that exhibits high seismic activity. The assessment of seismic hazard and generation of earthquake scenarios is the first step of seismic risk evaluation. The appropriate risk reduction strategies can be developed only with a better understanding of seismic hazard. The assessment of the strong earthquakes consequences is based on procedures for integration of seismic hazard and seismic vulnerability of the bearing structures of the building stock. Based on the collected information for the building stock and the analysis carried out, the assessment of direct damage and destruction is obtained. Earthquake scenarios and risk assessment are powerful tools to support disaster management decisions. The consideration of the earthquake scenarios into the policies for seismic risk reduction will allow focusing on the prevention of earthquake effects rather than on the activities following the disasters.

The wind is an essential climate variable and a key environmental factor affecting many geophysical processes. Researchers from multiple disciplines are faced with the need to determine the speed and direction of the surface wind for a particular location of interest. Regardless of the specifics of each particular task, in most cases, no data from direct measurements are available. For Bulgaria, an additional difficulty is the nature of traditional measurements in synoptic and climate stations with a Wild set. These circumstances require the application of alternative methods, in particular utilization of other sources of primary data. Methodologically, the most correct approach is the simulation of the 3-D structure of the airflow in the area of interest and its variation depending on the mechanical impact of the terrain and the influence of the temperature stratification of the atmospheric layer with a numerical aerodynamic model. This model should be based on the fundamental conservation laws and should be tailored to operate on the sub-kilometer spatial scale. The study presents some preliminary results from the exploration of the wind model WindNinja on the local scale over Bulgaria. The comparison of the output from the performed long-term model simulations with reference data demonstrates some degree of similarity revealing at the same time non-negligible differences.

In the past 30 years, the scientific community has shown a growing interest in creating models of the Earth's magnetic field. This interest can be explained by the large amounts of data collected from satellite missions. On the contrary, acquiring spatial data for a particular area using repeat station networks and geomagnetic measurements is gradually disappearing, although it is a reliable and well-established technique widely used in the near past. Nowadays, new technologies can quickly and accurately model even regional changes in the geomagnetic field. However, this study underscores the importance of assessing the reliability of these models by comparing their data with actual measurements taken in Bulgaria between 2018–2022. The data from low-orbit satellites and crystalline sources, which can cover vast areas, may cause a blurring effect, hence the crucial need for comparison with actual measurements. A secular network was established in Bulgaria as early as 1934 and continues to be operational today. This enduring network provides researchers with a unique opportunity to study the secular variation of the geomagnetic field in the country and analyze the accuracy of both regional and global models. In 2023, a four-year comprehensive measurement of the geomagnetic field in Bulgaria was completed under the auspices of the Military Geographical Service of the Ministry of Defense, with the support of the Geomagnetic Observatory Panagjurishte. This survey involved the re-measurement of over 400 points that were initially surveyed back in 1980, providing a unique opportunity for a comparative analysis of the geomagnetic field over a significant period. The data processed and reduced to epoch 2020.0 are compared to the regional and global IGRF13 and EMM models to assess their accuracy for regional field survey applications. Results show that the regional BulGRF model succeeds in reproducing to some extent the values obtained from the real measurements. EMM fails to predict the local declination distribution, but the magnitudes of H and Z produce very reasonable results. IGRF performs well in angular and magnitude estimates, providing close to real values and similar patterns.

About 20 strong earthquakes of magnitude 7 or greater occur each year. Exactly when they will happen cannot be determined in advance. Geological surveys can help determine the probability of an earthquake of a given magnitude. Thus, once the characteristics of the buildings in the area and the number of their inhabitants are known, mathematical models can be made for the possible damage. This can help to estimate in advance the number and type of casualties. In this paper we propose estimation of the dead and injured inhabitants, based on a model of the consequences of a possible earthquake of a given magnitude. The victims are divided into several types depending on the type of injuries.

In the analysis of the long-term Radon Volume Activity (RVA) results for the year 2022, we applied the Dobrovolsky model for radon anomaly identification using METER.AC network data. The radius of the precursor occurrence zone was estimated, and a geodynamic criterion (K ≥ 2.3) was employed, where ‘K’ represents the ratio of earthquake magnitude to the logarithm of the distance from the monitoring station to the event. Anomalies were defined as changes in radon concentrations exceeding ± 2 standard deviations from the mean value. The baseline RVA level was determined before each earthquake event, accounting for various factors such as temperature, humidity, tidal effects, etc. Radon volume activity measurements were conducted using two sensor types, RD200M and AlphaSensor, with reports generated every 10 min. The results were compared with seismic events meeting the criteria of M ≥ 2.6 (42 earthquakes) within the territory of Bulgaria and M ≥ 4.2 for the near zone up to 500 km from the Bulgaria borders (6 earthquakes), all satisfying the geodynamic criterion (K ≥ 2.3) and preceded by RVA anomalies. After excluding events with missing data from the preceding period, it was observed that the majority of those examined were preceded by radon anomalies.

This study analyzes the environmental impacts of the June 7, 2023, earthquake with a magnitude M4.8 that occurred in the vicinity of Plovdiv-Asenovgrad, Bulgaria, and was felt throughout the country. Its intensity in the epicenter area reached 6.5, and in the rest of the country, it varied in the range of 3–4.5. The time period June 7–10 was precisely analyzed using seismic data from the Bulgarian National Operative Telemetric System for Seismological Information (NOTSSI) and data with a resolution of 1 s for the ultra-low-frequency (ULF) variations of the geomagnetic field vector along its three directions: north-south (X), east-west (Y), and vertical (Z). A map of the intensity was constructed according to the Medvedev–Sponheuer–Karnik (MSK-64) macroseismic scale of the settlements in the vicinity of the epicenter, and its main features were discussed. The behavior of the geomagnetic field variations along the Y component, recorded in the Geomagnetic Observatory Panagjurishte, is altered after the main shock and continuously until the end of the aftershock series. This is expressed by an increase in the values of the variations and the emergence of sharp peaks only along the east-west direction of the geomagnetic field variations. According to the analysis, the effect on the geomagnetic field variations as a part of natural electromagnetic noise is not a consequence of the processes of Solar-Earth interactions, rather it might be related to the influence of co- or/and post-seismic activity effects.

The primary objective of this research is to apply the DInSAR (Differential Interferometric Synthetic Aperture Radar) method in investigating the interseismic period of the Dzherman fault near Sapareva Banya. It is used to detect and measure surface deformations occurring during this phase of the seismic cycle, characterized by low rates of strain accumulation. The analysis utilizes Sentinel-1 satellite radar images covering the timeframe from 2015 to 2022, with a yearly temporal resolution. A total of 14 interferograms derived from 7 pairs of ascending and 7 pairs of descending orbit images were processed. The main is to contribute to the profound understanding of stress accumulation processes and fault behavior in the examined region. The analysis reveals the presence of oscillatory movements along the Dzherman fault area, which are classified into three distinct models. These results are subjected to comprehensive discussion, acknowledging the methodological and technological constraints of the applied methodology. Despite these limitations, the study highlights the inherent potential of the DInSAR method in providing a qualitative assessment of surface deformations during the low strain interseismic period.

This study investigates the complex interplay of a multi-hazard event involving elevated levels of O3, PM10, high temperatures, and the intrusion of desert dust in the period 25–27 July 2023 in Bulgaria. The simultaneous occurrence of these stressors poses significant challenges to both human health and the environment, requiring a comprehensive understanding of the situation. The analysis of the episode comprises products by different type of models and observations relevant to synoptic and meteorological conditions, atmospheric dynamics and chemistry. Modelled data from Copernicus Atmosphere Monitoring Service's (CAMS) includes: analysis/forecast from the regional ensemble model for air quality in Europe, from the global model for atmospheric chemistry, from products for fire activity, as well as for PM10 speciation in the region of Sofia. The observational dataset includes air quality measurements at the stations of the Executive Environment Agency, observations at synoptic and climate stations, AOD from the two AERONET stations, and satellite retrieved data on aerosol content in the atmosphere. The combined analysis of these different sources of information contributes to better understanding of the causes of elevated pollution levels in the country during the episode and also provides some insights on model performance.

This study of short-term effects of air pollution builds upon previous research conducted in Sofia, expanding its scope to include Plovdiv and Varna, thus offering a broader perspective on the impact of air pollution on respiratory and cardiometabolic diseases in Bulgaria. The exposure-response relationships between hospital admissions for selected diseases (respiratory diseases (RD), ischemic heart disease (IHD), cerebral infarction (CI), and diabetes mellitus (DM)) and daily average air pollution concentrations from 2009 to 2018 were analyzed. Pollutants examined were particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Employing negative binomial regressions, we examined the effects of air pollution on hospital admissions, considering a seven-day period prior to each admission, while accounting for autocorrelations, time trends, day of the week, temperature, and relative humidity. Finally, we pooled some of the risk estimates across all cities using meta-analysis. Our findings reinforce the initial observations from Sofia, demonstrating a general increase in hospital admissions for RD, IHD and CI associated with higher pollution levels. For DM, the relationship remains less definitive though significant risks were also observed in some cases. Notably, the effect of air pollution on health outcomes displayed regional variations. While our results warrant cautious interpretation, they underscore the potential of air pollution to trigger acute episodes of related respiratory and cardiovascular diseases. This study offers insights for public health strategies and paves the way for further investigations into the environmental determinants of health across Bulgaria.

The Wildfire response system in Slovenia is divided into two parts: Into the Sub-Mediterranean fire-prone part, and into the inland part. The current Slovenian system and capacity for fighting wildfires throughout the country is mainly based on large fire trucks. There are about 1000 large multi-purpose fire trucks with powerful water pumps holding between 2000 and 15000 L of water. They are wider than 240 cm and their pipelines are about 300 m long. However, there are also several smaller firefighting vehicles with water, which are not so numerous and well distributed across the country and most of which are not sufficient for autonomous operations on severe wildfires. Access of most common bigger fire trucks into the forest in case of wildfire is provided with systematically maintained forest and fire roads with a width of at least 3 m. Their operational impact zone was defined as 250 m on each side. Although several kilometers of fire roads have already been built in the Sub-Mediterranean part of Slovenia, only 52.8% of the forests in this part are considered accessible for large fire tucks. The rest—the Slovenian inland forest—is much more accessible at 67.9%. In order to accurately allocate future needs for mechanization and infrastructure, the wildfire response system should be improved through some organizational reforms.

The political changes in Bulgaria after 1989 and the transition from a centralized to a democratic market economy were accompanied by severe demographic and socio-economic crises, which led to a decrease in total water consumption for the population and the industry. In this context, the present work examines trends in the use of water resources in Bulgaria from 1990 until 2020, based on publicly available information provided by the National Statistical Institute (NSI). The check for tendencies was made using a linear trend. The statistical significance of the regression line was assessed by the Mann-Kendall test. Results show a statistically significant negative trend for total withdrawn freshwater volumes during the investigated period, in contrast to the more dynamic changes in water consumption by economic sectors. The branch of agriculture stands out, which, due to the land reform, the change in ownership, and the unclear vision for further development, remains incompletely reformed, with a sharp drop in the output production and a correspondingly decreasing share of water use. This work analyzes the current trends in the use of water resources in Bulgaria under a weakening anthropogenic pressure. The obtained results, on the one hand, will enrich the past studies, and on the other hand, they will be a good basis for the following ones.

BG-Alert is a new established warning system to warn the people and administrative bodies about natural and man-made hazards with high destructive potential in real or near real time domain. The floods, heavy rains, hails, fires (both – domestic and/or forest, or bush), industrial accidents, chemical and/or radioactive pollution, etc. are the number of disasters for which BG-Alert must warn and issue short instructions about the behavior of population. The introduction of BG-Alert system in operation shows several cases of missfunction or malfunction. The alerts are not issued at all or emitted too late with a confusing information about the methods of evacuation, etc. There are also some disaters not included in BG-Alert operation such earthquakes or other more difficult to predict disasters. The aim of this paper is to explain a possible integration of a seismic warning system for population as well as to mitigate the effects of destructive seismic events. The global approach to seismic warnings has two main branches – the dynamic models, based on the fast determination of the parameters of a strong earthquake (coordinates, depth, magnitude) after an event occurred and the kinematic models. For the last, only kinematic properties of the seismic waves are used – time, velocity, propagation ray from source to the warned site. Usually the kinematic models follow the information of the time propagation of the primary and secondary seismic waves detected by a dense network of seismometers. The difference of the arrival times of both types of waves is crucial for the effectiveness of such systems.

Bulgaria's brown bear (Ursus arctos L.) is a strictly protected species according to the Bulgarian Biodiversity Low. Therefore, monitoring the populations of these protected species is necessary for the effective management and conservation of their habitats. In this work, we present the features incorporated in the High-Performance Data Analysis (HPDA) service for automatic estimating of the brown bear (Ursus arctos L.) population in Bulgaria. The program software is written in C++ and includes statistical algorithms based on the maximum likelihood method. We use observed signs of bears in their habitats, collected by the route (transect) method, as input data. These signs primarily include footprints (width of fore paw footprints and length of hind paw footprints), as well as excrements and tree marks. The field data are gathered annually as part of National Field Monitoring organized by the Executive Environment Agency. Approaches for investigating the bear population by sex and age are also incorporated into this service. The output results of the HPDA service include: (i) estimates for brown bear population and density in their habitats—Alpine and Continental areas, as well as different mountains; and (ii) estimates for age structures and how threats influence the population.

The 2023 Turkey-Syria earthquake affected an area of 99000 km2 on Turkish side where two million people were left without home. The PGA values which have been recorded by various stations show values as high as 1.2g as well as relatively spectacular maximum vertical component (PGV). The focus of the paper is to focus on a noticeable phenomenon in the city of Kahramanmaras where, on one hand, almost all buildings in the historical centre have either collapsed or been severely damaged by the two earthquakes (Pazarcik at 4:17 AM and Elbistan at 1:24 PM, respectively) of February 6th 2023, whereas, on the other hand, structures in the surrounding areas have significantly less damage. Moreover, it is evident from seismic stations’ recordings that impact (in terms of PGA, acceleration and velocity time histories) of first major shock (M7.7 Pazarcik) is higher than the one of the second major shock (M7.6 Elbistan) at similar magnitude and comparable distance to the epicenter. For the sake of investigating further the influence of local soil conditions as possible reason for the observed events shear wave velocity and soil deposit fundamental frequency have been measured in two spots – first, where multiple collapsed structures were detected and second, a neighbouring area with mostly standing buildings. Results indicate that the on-site measurement of only S-waves might lead to wrong assumptions in terms of microseismical zonation and further considerations shall be accounted. Furthermore, some comments and preliminary assumptions regarding seismic motion amplification effects have been presented in the study.

Karst geosystems are one of the most vulnerable to both natural and anthropogenic impacts. At the same time, karst sites and especially cave systems are very interesting and attract more and more tourists. The cave environment is specific and reacts in a particular way to global changes, which can increase the health hazard for visitors and especially for tour guides in show caves. It is mostly related to the concentrations of radon and CO2, which, according to the cave morphology and ventilation mode, can reach critical values. Based on long-term integrated monitoring in tourist caves in Bulgaria (Speleo-MIKS) and trends in climate change, the health hazards and probability of their increase against the background of intensifying global changes have been analyzed. Examples of the consequences of episodic natural cataclysms such as floods after extreme rainfall in some of the show caves and hazards of collapses during tectono-seismic activity are also given. The hazards from socio-economic global changes are also included: effects of land-use reorganization in cave system areas and of pandemics on show cave attendance. The influence of the tourist flow as a factor for changes in the cave environment is discussed.

The consumption of organically produced foods is gaining increasing popularity. Simultaneously, the areas under organic control are expanding. Data obtained from the Sentinel-2 satellite are exceptionally suitable for agricultural monitoring, as the mission provides data every 2–3 days, allowing for the tracking of changes in crops. Einkorn, known as the oldest wheat, finds wide application in various food products and is highly suitable for use in organic farming due to its resistance to weeds, various diseases, and pests. It is also highly suitable for crop rotation. In this study, we demonstrate the potential for monitoring yields of organic einkorn using Sentinel-2 satellite data. We tracked the development of the crop by selecting three different phenological phases: tillering, heading, and milk ripeness. We used images from these three phases, taken when we observed a mass entry of the crop into a given phase (minimum of 75% of plants in the crop in the respective phenological phase). Sampling sites were determined, with three different values of the Normalized Difference Vegetation Index (NDVI) established in the tillering stage: low, medium, and high. Upon reaching the technical ripeness phase, samples were taken in four replications at the three differences. Biometric measurements were taken, and the biological yield of the crop was determined. Correlation analysis was performed between ground-based yield data and Sentinel-2 satellite data. The study identified the phenological phases and vegetation indices most suitable for monitoring and predicting yields.

Remote sensing has been used for improving understanding of the climate system and its changes. It enables to monitor the Earth's surface, ocean and atmosphere at several spatio-temporal scales, thus allowing climate system observations, as well as investigating climate-related processes or long and short-term phenomena. Remote sensing techniques, and specifically satellite images, have been successfully used in a wide range of climate change fields, such as for (i) investigating global temperature trends, both at the ocean surface and in the atmosphere, (ii) detecting changes in solar radiation affecting global warming, (iii) monitoring aerosols, water vapour concentration, and changes in precipitation regime, (iv) studying the dynamics of snow extension and ice cover, (v) monitoring sea-level changes and coastal modifications, (vi) monitoring vegetation status and change, (vii) monitoring water resources and impact due to droughts and dry periods, (viii) monitoring fire events and fire emissions, (ix) predicting disaster risk, such as cyclone, floods, and drought, (x) guiding decision-making processes on climate change adaptation. In conclusion, remote sensing has been instrumental in climate change research by providing data and information about various aspects of the Earth system. It has allowed scientists to monitor changes in the Earth's climate system over time and to investigate the underlying processes driving these changes. This information is critical for understanding the impacts of climate change on our planet and for developing effective strategies for adapting to its effects.

Fog occurrence is a common phenomenon during the winter season in Sofia airport (alt. 531 m). Therefore, fog forecasting up to 3 h lead time are urgently needed in order to maintain air transport. Stochastic models with 0.5, 1, 2 and 3 h lead time for fog forecast occurrence (less than 1 km horizontal visibility) at Sofia airport based on binary logistic time series regression analysis are developed and discussed. The probabilities of fog occurrence versus non occurrence are estimated using historical meteorological observations. Data with different time scale for the period 01.01.2007–31.08.2023 were used for this purpose such as: a) half-hourly aeronautic observations for fog, temperature, dew point, wind speed and pressure from METAR reports at Sofia airport; b) 3-hourly observations from the SYNOP data for temperature, dew point, wind speed, pressure and fog measured at the Central Meteorological Station (CMS) (alt. 595 m) of NIMH, Sofia; c) aerological sounding data for temperature, relative humidity, wind direction and speed at standard pressure levels 925, 850 and 700 hPa measured at 12:00 GMT at CMS of NIMH, Sofia. Various lags from 1 to 6 of these meteorological data serve as input predictors in the models. The selection of most significant model predictors is based on lasso penalization. The generalized cross-validation technique is used in order to evaluate the model performance over testing data sets. Standard measures widely used in atmospheric sciences and statistical learning for forecast model assessment are used. The developed models explain a high percentage of the fog data variation and are reliable tools for fog forecasting.

Biomass combustion is currently widely used for residential heating within the European Union instead of coal or wood combustion. Solid biofuels are classified as highly reactive low-calorific fuels. One of the most efficient and environmentally friendly ways to utilize them is under fluidized bed conditions (FBC). However, the harmful by-products during biomass thermochemical decomposition still must be considered, such as particulate matter (PM). The atmospheric air quality monitoring is currently regulating PM10 and PM2.5, but particles of submicron size (PM<1) are being observed for having the major fraction in the flue gases of coal, wood or different types of biomass combustion. The present work aimed at studying thermal behavior and PM size distribution during oxidation of agricultural residue in FBC. A contemporaneous thermal analysis (TG-DTA/DSC) studied the effect of weight loss, thermal stability and energy at constant heating rate of 10 ºC/min and dynamic mode (20 ÷ 1100 ºC). Three general stages were distinguished: (1) dehydration, (2) devolatilization and volatiles ignition and (3) char combustion. Two types of biomass residues, namely peach and apricot stones were utilized in a formation rate unit at atmospheric pressure and temperatures: 700 ÷ 900 ºC. The primary gaseous products of carbon and nitrogen conversion and their reaction rates were experimentally measured simultaneously with the PM number density in the exhaust, short after the reactor’s outlet. The obtained unimodal PM size distribution confirmed that the normalized mass number density of the PM<1 is three orders of magnitude higher than those measured for PM2.5 and PM10.

This research introduces an innovative waste management system leveraging deep learning algorithms in conjunction with Raspberry Pi 3 and intelligent bins, enhanced by a bin-fill sensor. The system offers a comprehensive solution for efficient waste sorting and bin management. Utilizing cameras connected to the Raspberry Pi, the deep learning model accurately identifies various types of garbage in real-time. Upon classification, the corresponding intelligent bin's lid is automatically opened through actuators controlled by the Raspberry Pi. Additionally, a bin-fill sensor integrated into each bin detects the level of waste accumulation, providing crucial data for optimizing waste collection schedules. This multi-faceted approach aims to revolutionize waste management processes, facilitating automated sorting, and timely waste collection, thereby contributing to sustainable environmental practices. The project underscores the synergy between deep learning, edge computing, and sensor technology in developing intelligent waste management solutions.

The development of information and communication technologies over the past two decades has led to a transformation of education. The digitalization of the educational process is reflected in the so-called interactive learning environments. This article explores interactive learning environments, their characteristics, advantages and opportunities for application in different educational directions. The main technologies part of a modern interactive learning environment—simulations and virtual reality, cloud collaborative platforms and adaptive educational platforms are explored and analysed. An example model of a lesson has been developed, part of a training for disaster and accident actions, specifically in earthquake with the use of simulations and virtual reality. The process of generating simulations by implementing Neural Networks has been optimized. A comparison of simulation with and without the use of neural networks has been made. The results of the research can support the use of interactive educational environments to acquire specific knowledge and skills.

Geophysical methods play a crucial role in mining waste management by providing valuable information about the subsurface characteristics of mining waste sites. One of the most used techniques is Electrical Resistivity Tomography (ERT). It is commonly used in mining waste management to assess the electrical resistivity of subsurface materials. The principle behind ERT is based on the statement that different materials have different electrical resistivity values. In the context of mining waste management, ERT can provide valuable information about the composition, structure, and potential contaminants within waste deposits. By imaging the variations in resistivity, ERT can reveal the internal structure of mining waste deposits, including layering and variations in material properties.

Geophysical methods play a crucial role in the management of integrated mine waste storage facilities, particularly in relation to water drainage. These facilities are designed to store mine waste, including tailings from beneficiation. Geophysical techniques are employed to assess and monitor the subsurface conditions, detect potential issues, and ensure the overall stability and safety of the storage facility.

The integration of social media and artificial intelligence (AI) into disaster management, particularly for earthquake response, represents a profound evolution in emergency management practices. In the digital age, real-time information sharing has reached unprecedented levels, with social media platforms emerging as crucial communication channels during crises. This shift has transformed traditional, centralized emergency services into more decentralized, participatory models of disaster situational awareness. Our study includes an experimental analysis of 8,900 social media interactions, including 2,920 posts and 5,980 replies on X (formerly Twitter), following a magnitude 5.1 earthquake in Oklahoma on February 2, 2024. The analysis covers data from the immediate aftermath and extends over the following seven days, illustrating the critical role of digital platforms in modern disaster response. The results demonstrate that social media platforms can be effectively used as real-time situational awareness tools, delivering critical information to society and authorities during emergencies.

A sizable portion of the current building stock in Bulgaria is of reinforced concrete structures that were constructed before the contemporary concepts for safe structural performance under earthquake action were implemented in the codes. The global characteristics of these aged building structures are identified alongside their conformance to the major typologies. The study provides a brief overview of the main strategies for enhancing performance and reducing the damage caused by strong earthquakes to these structures.

A significant portion of the buildings in Bulgaria was constructed under the conditions of relaxed requirements for seismic resistance. Effective seismic risk reduction through building retrofitting is successfully achieved when a strategy based on well-defined criteria based on reliable results from seismic vulnerability assessment is applied. The study provides a brief overview of the estimated seismic risk for Bulgaria based on the data that is currently accessible and presumed by experts regarding building vulnerability. Approaches and criteria for the selection of target buildings for aseismic rehabilitation in order to realistically provide noticeable outcomes are discussed.

This work presents the results from the first experimental campaign on BC measurement in the 60-m layer above the ground. The measurement was conducted with a portable micro aethalometer MA200 in Central Meteorological Observatory, Sofia on the 20th of November, 2023. Additionally, meteorological parameters such as air temperature, reassure and relative humidity were measured by aerologic probe. The results show a high correlation in the dynamics as well as similar values of Black Carbon concentration in the studied layer. This indicates the homogeneous distribution of the pollutant under the given synoptic situation. In addition, a comparison of the measured BC concentrations with portable MA200, stationary aethalometer AE33 and some gaseous air pollutants are presented and discussed.

Extreme hydrological events such as floods have been and still are one of the most important natural hazards causing loss of human life and economic losses. Flooding is a phenomenon that has had a strong impact over the centuries around the world. Society is more and more vulnerable to extreme events like floods and droughts due to climate change. Detailed research in recent years show variation in flood frequency and types in Bulgaria. The reasons are based on long term climate change effects along with short term weather shifts. According to scientific investigations of many institutions and universities (NOAA, NCAR) as well as reports and resolutions of international organizations (IPCC, WMO, FAO, ЕЕА) it is clearly stated that flood risk will probably increase in the future also as a result of socio-economic changes as are population growth, landuse and landcover changes and deforestation. Floods are an integral part of the hydrological regime of river basins. In this paper the typical flood types in Bulgaria are presented. Important floods from both the recent and distant past are shown. A historical flood was compared with the simulated one with the same probability. For mitigating flood risk it is essential to have suitable water resource management measures outlined including registered extreme events (flooding) archive. Studying past floods is useful for understanding the factors that trigger or enhance these events. It is also helpful for effective water resource management, flood risk mitigation and climate change adaptation.

In Romania the risk of forest fires is one of the highest in terms of probability of manifestation but the level of impact is relatively low compared to other types of risks. While Romania hasn't yet faced extreme fires, there are instances where emergency forces are overwhelmed by the occurrence of multiple small and medium sized wildfires simultaneously in a particular area. Climate scenarios indicate that countries that have not traditionally faced a significant risk of forest fires, such as those in Eastern Europe, will experience an increase in this hazard in the near future. This paper provides a general overview of the natural, social, and institutional context of forest fire defense in Romania with a focus on forest managers which are the first responders to fire incidents and proposes measures for its improvement within a best practices guide. It outlines the causes of forest fires in Romania, including historical trends and seasonal vulnerabilities and pinpoints the challenges and deficiencies of Romanian forest fires management system. The responsibilities and duties of forestry structures and personnel in preventing and combating forest fires are presented, along with the legal framework for fire management, roles of forestry personnel, intervention forces, and the involvement of forest owners in operational response. Overall, the paper shortly addresses the complex aspects of forest fire prevention, response and management, aiming to enhance forest managers capacity in protecting Romania's forest ecosystems against the threat of forest fires.

The earthquakes near Chirpan and Plovdiv, Bulgaria, occurring on April 14 (Ms 6.8) and 18, 1928 (Ms 7.0), respectively, represent significant seismic events in the region's history. These events are unique because geodetic measurements were carried out before and after the earthquakes. This study aims to evaluate the effects of the fault parameters on the focal mechanism solutions in respect to the observed displacements. The analysis utilizes the Okada model to calculate movements over the fault area testing different parameters. The focal mechanisms of the two events underwent parametric testing, with variations in the exploration of fault dip, rake and geometry. The contribution of each parameter was evaluated. Modelled solutions were compared with observations in order to understand the dynamic behavior of the media during seismic events. To enhance the accuracy of dislocation modelling across the fault, its length was divided into several segments. The applied approach provides an improved representation of real observations and dislocations.

Ice storms, caused be severe freezing rains and drizzles, are among the major weather hazards in winter. They influence seriously the air and ground traffic, disturb and even interrupt the distribution of electricity by snapping power lines or by bringing to standstill the production from wind farms. Different regions around the world are affected by these phenomena. Most frequently they are observed in mid-latitude regions in Canada, USA and Finland but even is some southern regions of Europe like Bulgaria. Although such severe events are relatively rare, they cause some of the highest damage costs per event. Freezing precipitation events in Bulgaria are also not very often observed but they can be surprisingly severe and the damages are comparable to that ones in Canada and USA. The most affected regions are in the north and especially in the northeastern part of the country. This severity is determined by the simultaneous influence of two factors – deep Mediterranean cyclone, passing south of the country, and a strong cold advection from north or northeast. Main goal of this investigation is to thoroughly reveal all important and temporal characteristics of the freezing rain, freezing drizzle and ice pellets in Bulgaria, which includes frequency of appearance, number of cases and intensity of the process and spatial extend, as well as the accompanying meteorological elements such as air temperature, wind speed and direction. For this purpose we have used data from 38 meteorological station for the period 1991–2020.

Firefighters in Bulgaria have very limited usage of ICT tools (Information and Communication Technologies) in their field response decision support processes. Our paper will describe a pilot platform implemented in five test municipal areas located in south Bulgaria. The system was developed to support field communication, meteorological conditions data exchange and wild fire related data analyses in simple GIS interface, needed for field response. The paper will describe main functionalities of the system and their potential usage in field operations.

Wildland fires are natural hazard that occur every year in different parts of the world. European Mediterranean countries often are suffering from this disaster and in some cases human casualties and infrastructure damages are in place. Bulgaria as part of the north east Mediterranean basin is affected by wildland fires in the last three decades more often than before. Fire behaviour analyses is the main tool for the decision makers to understand and better prepare for the future fire events. In our article we will describe the data collection challenges and wildfire simulation preparatory work that every wildfire analyst in Bulgaria has to overcome fulfilling the task.

A set of criteria for selecting accelerograms for seismic impact modeling for a time-history analysis of retaining walls is presented. Several accelerograms differing in peak ground acceleration, frequency content, duration, and other parameters have been analyzed and evaluated. The selection of appropriate accelerograms that can be used for the alternative modeling of the seismic impact within the FEM (finite element method) analysis of a part of a soil foundation with an adjacent retaining wall encompasses three consecutive steps: (1) definition of credible earthquake scenario; (2) compatibility verifications of the ground motion in time and frequency domain; (3) deconvolution of the selected free field accelerograms to the base of the FEM model. The study concerns the seismic behavior and response of retaining walls at sites within the city of Sofia. The deconvolution procedure is performed via one-dimensional wave propagation analysis using the ProShake software.

Most of the buildings in many mountain regions in Bulgaria were built during the first half of the last century of non-standard building materials – stonemasonry, adobe brick masonry, etc. The seismic behavior of such structures is unknown, and occupation of the buildings is dangerous. This paper offers an experimental methodology for assessment the seismic behavior of one-bay one-story masonry non-engineered buildings and options for their constructive remediation to improve the seismic stability of the latter. The sequence of the proposed methodology is the following: Architectural structural modeling of the investigated building, approximate numerical studies in the environment of software packages for dynamic analysis of structures, construction of an experimental scale model of the building, experimental study of a built scale model of the building, constructive reinforcement of the model, experimental study of the structurally reinforced model. Architectural modeling is based on on-site photography. Approximate numerical studies are in the SAP2000 environment. Harmonic excitation is applied to the experimental model, made on an approximate scale of 1:5, and the vibration forms and their corresponding frequencies are experimentally determined. The seismic behavior of the structure is evaluated based on the obtained first resonance frequency. After the study, the model is structurally reinforced with a horizontal, vertical, or mixed structural system and is re-tested. Based on the difference in the first resonance frequency, the improvement of the seismic behavior is evaluated.

Because of climate changes cyanotoxins have become as an emerging risk in recent decade due to their release from blooms in water bodies of toxic microalgae known as cyanobacteria. Proliferation of cyanobacteria is connected with increased amounts of nitrogen and phosphorus. Temperature also has a favorable effect on the growth of microalgae, which causes their widespread multiplication with the onset of climatic changes in increasing the temperature of water bodies. Cyanotoxins are harmful for human health and environment because they are hepatotoxins, neurotoxins, dermatotoxins, etc. The paper is a summary of data from studies of water collected in the period 2017–2020 from the Bistritsa dam in terms of species composition, algal toxins and nutrients. Bistritsa dam is used for recreation and fishing. Five water samples were tested, microcystins were detected in one water sample from 2020 (microcystin-LR concentration 22.82 µg/l and microcystin-YR 14.05 µg/l in the autumn season). The content corresponds to increased values of the concentrations of the studied nutrients (total nitrogen and total phosphorus 16.81 µg/l and 0.57 µg/l respectively). A bloom of the blue-green alga Anabaena solitaria was also found in the same sample. Regarding the saprobic/trophic status, the water body maintains a permanent beta-saprobic state corresponding to oligo-mesotrophicity. The presence of anatoxin-a was detected in 4 samples with highest concentration 0.4 µg/l. Cylindrospermopsin was nof found in the collected samples. The results show that the investigation of cyanobacterial blooms and the water quality of the reservoirs like Bistritsa dam are important for human health and environmental protection.

Modern flood risk assessment methods use multiple integrated concepts to perform analyses, taking into account multi-disciplinary expertise from different fields. A fundamental element for these analyses is the Digital Terrain Model (DTM), through which vulnerable areas can be identified based on hydraulic simulations. The overall process includes both analysis of meteorological conditions and local investigation of a specific section of the river system to predict the entire functional chain of the flood. For the needs of spatial analyses related to the territory of the Republic of Bulgaria, there are generally known freely available relief models such as: SRTM (30 × 30 m), EU-DEM (25 × 25 m), ALOS DEM (30 × 30 m). In addition to that free data, the available experimental DSM (4 × 4 m) at the MAF (Ministry of Agriculture and Food) can be used in flood risk studies, as well as the incoming high spatial resolution digital data (SfM, LiDAR) acquired through Unmanned Aerial Systems (UAS). There is no free LiDAR data available for Bulgaria's territory. In this paper, a comparative analysis of topographic conditions is made to identify potential floods in floodplains. This analysis evaluated different spatial resolutions of the terrain surface in a test area section of the Ogosta River. We used the FLO-2D Basic model for the simulation of the flows, freely available in its basic version. It consists of a quasi-2D hydrological–hydraulic dynamic flow model simulating channel flow, and unconfined overland flow over complex topography. Simulations were performed at different resolutions of DTMs obtained from UAS-SfM (structure from motion), which are acquired relatively quickly and at low cost. The data obtained by UASs are of high temporal and spatial resolution, allowing hydraulic models to be kept up-to-date for problematic river sections and potential high-risk flood areas.

The two devastating earthquakes on the East Anatolian Fault that hit Turkey and Syria on the 06th of February 2023 were an exceptional Balkan Region test on earthquake preparedness and building stock resilience. Field-collected information after visual assessment of the seismic performance of prefabricated buildings with reinforced concrete and steel structures is presented in this article. It has been collected during the National Earthquake Engineering Center (NEEC) at the University of Architecture, Civil Engineering and Geodesy (UACEG) visit to the region. Two case studies of neighbouring buildings at a site in Kahramanmaras are presented. Observations on the seismic response of low-rise reinforced concrete and steel industrial buildings are shared. The structural failure modes and damages are discussed in relevant details. A comparison of the Seismic Performance Level of two buildings with different structural systems, located on the same site is done. The actual seismic response of the inspected buildings has been discussed with respect to the available strong motion data recorded at the nearest stations and code defined Compliance Criteria. Some field collected findings regarding connection failure modes relevant to Bulgarian construction practice are pointed out. Based on the experience gained in Kahramanmaras, several directions for improvement of Bulgarian seismic resistant design practice of low-rise precast reinforced concrete buildings are formulated.

There is a growing interest in stand fuel inventories through the use of light detection and ranging (LiDAR) technology among fire researchers. In this study, canopy fuel load of Turkish red pine (Pinus brutia Ten.) stands was estimated based on point-cloud data collected from five sample plots using a mobile laser scanner (MLS). For this, stand fuel characteristics (i.e., dbh and number of trees) and fuel load models were used in combination. The estimation results were stand fuel characteristics were compared against the ground truth obtained through traditional field measurements. Preliminary results indicated that MLS was able to capture dbh and the number of trees information at the plot level. Thus, it is possible to estimate canopy fuel loads in Turkish red pine relying on species-specific models that utilize MLS data as input. Further research is needed for automating the point-cloud data analysis workflow and more accurate characterization of surface fuel in Mediterranean forests.

The SWAT model was applied to the watershed of Rusenski Lom River, North Bulgaria. The model is implemented using QSWAT, which is an interface between SWAT and QGIS. The data used are the measured values for river discharge at the NIMH hydrological station in the village of Bozhichen, Ruse region. The model was fed with data for the period 2007–2021. Calibration, validation and sensitivity analysis were performed using SWAT-CUP 2019, SUFI-2. Five factors were used for the estimation of model performance: R2 (coefficient of determination), Nash-Sutcliffe performance index (NSE), PBIAS (percentage bias), P-factor (model accuracy) and R-factor (model uncertainty). Eleven parameters were applied for the sensitivity analysis, with six (CN2, SOL_AWC, ESCO, REVAPMN, GWQMN, RCHRG_DP) found to be more sensitive (P < 0.05) to the river discharge. The SUFI-2 algorithm interfaced with SWAT-CUP was able to capture the behavior of the model with calibration results showing an R2 of 0.37 NSE index of 0.24, PBIAS of -1.0, while validation results revealed an R2 of 0.28, NSE of 0.26 and PBIAS of -2.0. The model produced a P-factor of 0.69 and an R-factor of 1.35 during calibration and during validation, 0.62 and 0.97 respectively.

Nowadays the artificial intelligence is widely used in almost every sphere of our life. It has been applied in most of the medical specialties and it is transforming the medical decision-making process – from the diagnostic testing procedures to the treatment protocols and preventive measures planning. COVID-19 pandemic dramatically reshaped the organization and management of healthcare delivery. The overloaded with critical patients hospitals were not able to admit and hospitalize all those in need, therefore the outpatients’ clinics were tasked with additional duties AI tools were widely applied into COVID-19 pandemic management – into organization of the healthcare systems, into diagnostic and testing, into infected patients’ management. The objective of this article is to present and analyze the Bulgarian pre-hospital healthcare providers’ perception about the capacities and capabilities of the AI and contemporary information-communication technologies (ICT) in medical practice – medical triage and patients monitoring. Results from survey among 57 Bulgarian pre-hospital healthcare providers regarding the artificial intelligence and information communication technologies implementation into their practice are presented and analyzed. Conclusion about the need of more focused information campaigns related to the possibilities for wider use of the artificial intelligence capabilities is noted.

In this article, we examine the evolution of broker roles and their capacity to rapidly transmit emergency information within emergency networks. Using a social network analysis (SNA) approach, we analyze text data on collaborative ties among organizations that responded to the flood disaster in Henan Province, China in 2021. We explore how broker roles facilitate the quick dissemination of emergency information, drawing on structural hole and resource dependence theories. We find that the involvement of numerous national, provincial, and municipal participants from various categories of organizations indicates the establishment of a highly centralized emergency system in China, where government-led efforts play a pivotal role in emergency response. Additionally, as the emergency mission shifts from rescue to recovery, the Emergency Management Department continues to act as a broker, while the Education, Civil Affairs, and Development and Reform Department emerge as brokers due to their specialized expertise. Our research on broker roles provides valuable insights into the overall efficacy of emergency response efforts and aids in enhancing coordination among emergency managers, empowering them to develop strategies that bolster the overall resilience of the emergency network.

Examining the casualty’s cardiac activity is an important component of first aid procedures before transporting the casualty to a specialised medical facility. During disasters and accidents, there are many victims and emergency teams must be equipped with specialised portable medical devices for measuring ECG, pulse, blood sugar, temperature, etc. This paper describes an innovative solution for ECG monitoring of victims during disasters and accidents. The proposed device provides the possibility of a quick warning of a deviation from the heart rate norms. A novel concept for communication is suggested based on uMAC. The results obtained from the device can be monitored remotely using a management program of the Local Operator Station (laptop, medical tablet or mobile device). AR/VR-based simulation software is also planned to be developed to train emergency medical personnel to operate the device.

This work presents the construction, development, and status of Bulgarian GPS/GNSS CORS and networks, which are considered a part of the national geodetic infrastructure. We discuss the need for and importance of evaluating the stability of reference stations and the quality of GNSS data for solving scientific and applied tasks. We identify open scientific questions related to expanding the possibilities of applying high-rate GNSS data for advanced research studies. Recent applications of GNSS measurements and their integration with other data to research natural risk processes are briefly outline.