Assessment of the relationship of exacerbations of diseases of the cardiovascular system with the meteorological situation

Introduction. The impact of weather factors on the occurrence of exacerbations of diseases in meteodependent people is currently one of the actively studied problems of medicine. The aim of the study was to identify the relationship between exacerbations of diseases of the cardiovascular system with the meteorological situation to substantiate the need for preventive and informational work with meteodependent patients. Material and research methods. The study used daily data on the number of patients with cardiovascular diseases seeking medical care at Voronezh City Polyclinic No. 18 and daily information on weather conditions for 2018. The ratio of the average number of cases of medical assistance requests on days unfavourable for meteorological factors to the average number of cases of medical assistance requests per day during the year was calculated. Using software (Statistica Base V6.1), a correlation analysis of the relationship between the number of medical requests and meteorological factors was carried out. Results. It has been established that the appealability of patients with cardiovascular diseases for medical care on days unfavourable for meteorological factors is 1.1-2.0 times higher than the average annual indicator. The most informative characteristic of the six meteorological indicators taken into account in the study (average daily, minimum, maximum ambient air temperature; temperature drops by more than eight °C per day; atmospheric pressure; atmospheric pressure drops by 12 mm Hg per day or more) is a sharp drop in atmospheric pressure during the day, with which statistically significant (p <0.05) correlates the number of cases of patients with cardiovascular diseases seeking medical help. Conclusion. In medical institutions providing primary health care, it is advisable to single out separate groups of patients with meteorological dependence for dynamic observation and conduct information work with them to mitigate the severity of the course of diseases of the cardiovascular system on days unfavourable according to meteorological indicators.

The role of emission reductions and the meteorological situation for air quality improvements during the COVID-19 lockdown period in central Europe

The lockdown measures taken to prevent a rapid spreading of the coronavirus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years; however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 were extrapolated from most recent reported emission data, and lockdown adjustment factors were computed from reported activity data changes, e.g. Google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with 2-week-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to ±15 %) and showed both increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx / VOC emission ratio. PM2.5 revealed 2 %–12 % reductions of 2-week-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in northern central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

ASSESSMENT OF THE PROBABLE RELATIONSHIP OF EXACERBATIONS OF CARDIOVASCULAR DISEASES WITH THE METEOROLOGICAL SITUATION

Relevance. The analysis of these scientific publications has shown the relevance of studying the problem of the influence of sudden changes in meteorological factors on the functioning of the cardiovascular system, exacerbation of its leading diseases – arterial hypertension, brain vascular lesions, cerebrovascular diseases, angina. Aim: to identify the probable relationship of exacerbations of diseases of the cardiovascular system with the meteorological situation. Material and methods. A sample of data on the daily number of cases of patients 'requests for medical care to the registry of the Voronezh City Polyclinic No. 18 for 2018 was conducted. Results. At a temperature below-200C, which was registered on 27.02.2018, the number of requests for medical care due to hypertension without heart failure is 88 cases, with a diagnosis of brain vascular damage (specified) – 15, with a diagnosis of cerebrovascular disease-16, hypertension with heart failure-2, angina-0. The difference in the average daily temperature of more than 8 0C was recorded in 204 of 365 days. Out of 365 days, the atmospheric pressure drop of more than 6 mm Hg per day was recorded 52 times. Conclusions. The most informative characteristic of the six meteorological indicators taken into account in the study is a sharp drop in atmospheric pressure during the day, with which the number of cases of patients with cardiovascular diseases seeking medical care is statistically significantly correlated.

The role of emission reductions and the meteorological situation for air quality improvements during the COVID-19 lockdown period in Central Europe

The lockdown measures taken to prevent a rapid spreading of the Corona virus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years, however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in Central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 was extrapolated from most recent reported emission data and lockdown adjustment factors were computed from reported activity data changes, e.g. google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with two-weeks-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to +/−15 %) and showed both, increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx/VOC emission ratio. PM2.5 revealed 2–12 % reductions of two-weeks-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in Northern Central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

Modeling of spatial and temporal assessment of territorial risk in case of accidents during transportation of chemically dangerous goods by rail

During the operation of railway transport, various pollutants are emitted into the atmosphere. Sources of pollutants on rail transport are divided into two main classes. The first class is moving sources. The second is stationary sources. From the standpoint of assessing the level of environmental safety and environmental protection, it is necessary to identify two main types of emissions of pollutants. The first type is an organized issue. For example, the emission of fuel combustion products during the operation of a locomotive. The second type is unorganized emission in case of emergencies at the stage of transportation of dangerous goods, their loading or unloading. For example, depressurization of the tank. This article considers the problem of unorganized emissions of chemically hazardous substances into the atmosphere during the operation of railway rolling stock. The transport of dangerous goods by rail poses a potential threat of large-scale environmental pollution in case of emergencies. The analysis of the situation shows that accidents on the railways of Ukraine occur quite often. The main causes of emergencies during the transportation of chemically dangerous goods by rail are: mechanical damage to capacitive equipment; corrosion, thermal action on capacitive equipment; depressurization of shut-off valves, welded joints; getting into the capacitive equipment of foreign substances; fatigue phenomena in metal, welded elements; equipment defects; errors during the design, manufacture, installation, repair of equipment; lack of optimization of routes for delivery of chemically dangerous goods to the consumer; collision of a train with motor transport at crossings. We should also not forget about the possibility of sabotage at railway facilities. For example, blasting tracks. During emergencies, large areas of contamination are formed during the transportation of chemically dangerous goods by rail. These pollution zones extend far into the regions adjacent to the railway. There are the following striking factors in emergencies during the transportation of chemically dangerous goods: cloud (train) of toxic substances; the emergence of a fireball; shock wave. One of the main reasons for exceeding the permissible concentrations of toxic substances and carcinogens in the atmosphere in the surrounding area is the emission of exhaust gases during the operation of main and shunting locomotives and in emergencies during the transportation of chemically dangerous goods. In the case of emissions of harmful and chemically hazardous substances in transport, the following tasks must be solved: assessment of the scale of pollution; assessment of potential territorial risk; development of measures to protect the environment from pollution. To solve these problems, it is necessary to develop mathematical models that take into account the specifics of emissions of harmful and dangerous substances at railway facilities. When transporting chemically hazardous substances by rail, an important safety aspect must be taken into account – the distance between tracks, station areas and residential or industrial buildings. It is related to the requirement to protect, first of all, the population, as well as the territory from possible dangerous factors that arise during emergencies. Therefore, the purpose of this article is to forecast risk areas for residents of the adjacent accident site with chemically hazardous substances on the railway track, determine the rate of air pollution in the area and provide recommendations for the evacuation of civilians. In assessing the territorial risk in case of accidents on railway transport, accompanied by the emission of hazardous substances into the atmosphere, the method of spatial-temporal assessment was used. This method takes into account the following factors: the probable value of wind speed and direction; emission intensity; start and end time of the issue; state of the atmosphere; emission source movement. To forecast the territorial risk, it is necessary to know: the emission power of a hazardous substance; place of possible accident; scenario of meteorological situations; concentration field of a dangerous substance, which is formed for a specific meteorological situation. Territorial risk assessment in case of emergency leakage of hazardous substances at the railway station is carried out in two stages. Stage I – the calculation of the concentration field of a dangerous substance for a particular meteorological situation is carried out. Stage II – the calculation of the magnitude of territorial risk for each point of the region, taking into account the specified concentration threshold. Thus, the proposed mathematical model of the method of spatial-temporal assessment of territorial risk in the emission of hazardous substances by rail takes into account various factors. Namely: the influence of different meteorological situations, the power of the emission, the movement of the emission source, the trajectory of the warehouse, and so on. It also shows the speed (time) of propagation of the plume (cloud) of a dangerous substance, which allows the relevant services to carry out the necessary evacuation measures. The mathematical model of the method of spatial-temporal assessment of territorial risk is recommended to be used in the Head Department of the State Emergency Situations Service of Ukraine (DNSU of Ukraine) in Mykolayiv region to assess the consequences of extreme situations at chemically dangerous facilities in the region and transport.

Refractive properties of the troposphere of Baikal natural territory and surrounding areas.

The meteorological situation has a significant impact on the propagation of ultrashort radio waves. Refractive index of the atmosphere N is the main radio-meteorological characteristic of UHW propagation. The calculation of N is given on the basis of meteorological data of the atmospheric-soil measuring complex located on the basis of the measuring station in the village. Sosnovo-Ozerskoe, Eravninsky District, Republic of Buryatia. The regional features of the behavior refractive index in Buryatia, Yakutia and Mongolia are considered. The comparison with similar studies carried out on the basis of meteorological data from 1958-1977 was made. Global climate changes did not have a significant impact on the radio meteorological situation in the region was revealed.

Mechanism of neural network training for forecasting the meteorological situation when using GIS

This article is devoted to the mechanisms of neural network training for forecasting the meteorological situation when using GIS. The structural scheme of the GIS under consideration is proposed as a project solution and the main elements allowing to implement neural networks and their training are defined. The stochastic method is chosen as a tool for neural network training as it suggests the most probable outcome of the event based on the previous sample. The article gives an example of testing neural network training as an application program «Data Processor». The results described in the article allow us to judge about the applicability of the selected neural network training method for forecasting meteorological conditions and using data in geoinformation decision-making systems. Keywords: geoinformation system, synoptic forecast method, hydrodynamic forecast method, aggregator, data processor, knowledge base, deterministic method, expert estimation method, stochastic method, neural network, sampling, probability dispersion.

The significance of extreme floods in the transformation of mountain valleys and causing flood risk, on the example of the July 2001 flood that occurred in the upper catchment of the river Skawa

In July 2001, in the Carpathian basin of the Vistula, there was a lot of rainfall and storms. The meteorological situation of that time was similar to that of 1934 when a great flood occurred. On 25 July (2001st), in the upper part of the Skawa catchment, a violent storm occurred. Its centre was located right at Makowska Góra. The daily precipitation in Maków Podhalański was 190.8 mm that day. Most of the precipitation occurred during a storm. Although the precipitation was much lower in the other stations located in the drainage basin, the flow of the Skawa in Sucha Beskidzka was 660 m3 s-1, while the constructed dam in Świnna-Poręba – 1019 m3 s-1. Precipitation was so abundant that the floodplains terraces of the Skawa have been inundated, and made the streams flowing down the Makowska Mountain spill out of the trough. The centre of Maków Podhalański and the neighbouring streets were destroyed. The main current flowed through the streets of Źródlana, Krótka, Kościelna, Rynek, and Wolności. The biggest losses were caused by the Księży Potok and several smaller streams (Rzyczki, Grabce, and Czarny Potok) that poured out of the trough and flowed through them. The biggest losses have been incurred by the Budzów and Zembrzyce municipalities located on the other side of the mountain. The losses were caused by a small Paleczka stream.

Short-term photovoltaic generation forecasting using multiple heterogenous sources of data based on an analog approach.

&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Over the past years, environmental concerns have played a key role in the development of renewable energy sources (RES). In Europe, the installed capacity of photovoltaic (PV) has increased from around 10 GW in 2008 to nearly 119 GW in 2018 [1]. Due to this high penetration rate and the intermittent nature of RES, several challenges appear related to the economic and secure operation of a power system. To overcome these challenges, it is necessary to develop reliable forecasts of RES, and namely of PV production, for the next hours to days to adjust production planning, while intra-hourly forecasts may contribute to optimize operation of storage units coupled to RES plants.&lt;/p&gt;&lt;p&gt;The aim of this paper is to present a novel spatio-temporal (ST) spot forecasting approach able to use multiple heterogeneous sources of data as inputs to forecast short-term PV production (i.e. from 15 minutes up to a day ahead).&lt;/p&gt;&lt;p&gt;First, we consider measured production data from nearby power plants as input to forecast the output of a specific PV plant. These data permit to exploit the correlation between the production data of spatially distributed PV sites. The classical ST approach in the literature, based only on this source of data [2], permits to improve predictability for the next few minutes up to 6 hours ahead.&lt;/p&gt;&lt;p&gt;Then, we extend the model by the use of satellite images (i.e. global horizontal irradiance (GHI)) which provide meaningful spatial information at a larger extent.&lt;/p&gt;&lt;p&gt;Finally, we consider Numerical Weather Predictions (NWPs) as input, which permit to extend the applicability of the model to day-ahead lead times, so that, overall, the resulting model covers efficiently horizons ranging from a few minutes to day ahead.&lt;/p&gt;&lt;p&gt;The spatio-temporal relationships being dependent on the particular meteorological situation of the day at hand, we apply an analog ensemble approach, to condition the learning process with historical observations corresponding to similar meteorological situation. We used the analogue approach to select a subset of similar historical situations over which a dynamical calibration of the forecasted model is done, as it was for example suggested by [3,4]. In our paper we extend the analogs ensemble approach by considering geographically distributed observations of the physical variables of interest (as suggested by [4] for hydrological issues) rather than only those at the level of the PV plant.&lt;/p&gt;&lt;p&gt;The performance of the proposed ST model with heterogeneous inputs is compared with reference models and advanced ones such as the Random Forest model. Historical production data collected from 9 PV plants of CNR are considered. The power units, located in the South-East France, exhibit relevant spatial correlations which make them suitable for the proposed ST model.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;[1] IRENA - https://www.irena.org/Statistics/Download-Data&lt;/li&gt; &lt;li&gt;[2] Agoua, Girard, Kariniotakis. Short-Term Spatio-Temporal Forecasting of Photovoltaic Power Production. IEEE Transactions on Sustainable Energy , IEEE, 2018, 9 (2), pp. 538 - 546. https://doi.org/10.1109/TSTE.2017.2747765&lt;/li&gt; &lt;li&gt;[3] Alessandrini, Delle Monache, Sperati, Cervone. An analog ensemble for short-term probabilistic solar power forecast. Applied Energy, 2015. https://doi.org/10.1016/j.apenergy.2015.08.011&lt;/li&gt; &lt;li&gt;[4] Bellier, Bontron, Zin. Using meteorological analogues for reordering postprocessed precipitation ensembles in hydrological forecasting. Water Resources Research, 2017. https://doi.org/10.1002/2017wr021245&lt;/li&gt; &lt;/ul&gt;