An effective chaos-geometric computational approach to analysis and prediction of evolutionary dynamics of the environmental systems: Atmospheric pollution dynamics Abstract. The present paper concerns the results of computational studying dynamics of the atmospheric pollutants (dioxide of nitrogen, sulphur etc) concentrations in an atmosphere of the industrial cities (Odessa) by using the dynamical systems and chaos theory methods. A chaotic behaviour in the nitrogen dioxide and sulphurous anhydride concentration time series at several sites of the Odessa city is numerically investigated. As usually, to reconstruct the corresponding attractor, the time delay and embedding dimension are needed. The former is determined by the methods of autocorrelation function and average mutual information, and the latter is calculated by means of a correlation dimension method and algorithm of false nearest neighbours. Further, the Lyapunov's exponents spectrum, Kaplan-Yorke dimension and Kolmogorov entropy are computed. It has been found an existence of a low-D chaos in the time series of the atmospheric pollutants concentrations. IntroductionThe last decades have seen a great progress in the understanding, analysis, modelling and evet prediction of the evolutionary dynamics of nonlinear complex systems. Various methods and algorithms of the modern theory of dynamical systems and a chaos theory became a powerful tool in computational studying complex non-linear statistical systems [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. Many studies in different fields of science and technique have appeared, where the chaos theory methods were applied to a great number of dynamical systems. The studies concerning non-linear behaviour in the time series of atmospheric constituent concentrations are sparse, and their outcomes are ambiguous. In ref. [5] there is an analysis of the NO 2 , CO, O 3 concentrations time series and is not received an evidence of chaos. Also, it was shown that O 3 concentrations in Cincinnati (Ohio) and Istanbul are evidently chaotic, and non-linear approach provides satisfactory results [6]. In Ref.[14] it has been fulfilled the detailed analysis of the NO 2 , CO, CO 2 concentration time series in the Gdansk region (Polland) and it has been definitely obtained the evidence of a chaos. Moreover it has been given a short-range forecast of atmospheric pollutants time evolution using non-linear prediction method. These studies show that chaos theory methodology can be applied and the short-range forecast by the non-linear prediction method can be satisfactory. Time series of concentrations are however not always chaotic, and chaotic behaviour must be examined for each time series.In this work we study the temporal dynamics of the atmospheric constituents concentration in the Odessa region by using the non-linear prediction and chaos theory methods [3,4,[12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. A chaotic
We present the theoretical foundations of an effective universal complex chaos-dynamical approach to the analysis and prediction of atmospheric radon 222 Rn concentration using the beta particle activity data of radon monitors (with a pair of Geiger-Muller counters). The approach presented consistently includes a number of new or improved available methods (correlation integral, fractal analysis, algorithms of average mutual information and false nearest neighbors, Lyapunov's exponents, surrogate data, nonlinear prediction schemes, spectral methods, etc.) of modeling and analysis of atmospheric radon 222 Rn concentration time series. We first present the data on the topological and dynamical invariants for the time series of the 222 Rn concentration. Using the data measurements of the radon concentration time series at SMEAR II station of the Finnish Meteorological Institute, we found the elements of deterministic chaos.
Formulation of the problem. The level of atmospheric air pollution in large cities is influenced by a number of factors, among which the most important are the emissions of pollutants into the air, the characteristics of the sources of admixtures, the landscape features, synoptic and meteorological conditions (Vystavnaya, Zubkovych 2014). The influence of the latter is associated with the scattering, washing out and transformation of harmful substances in the atmosphere, as well as the significant variability of their concentrations in space and time. The characteristics of the wind regime (wind direction and velocity), temperature inversions, and formation of low-troposphere currents are among the meteorological factors that most influence the concentrations of contaminants in the layer of atmosphere near the surface (Ivus 2017), (Agayar 2018) Shevchenko 2020). The purpose of the article is to develop and improve methods of forecasting meteorological conditions of atmospheric pollution over industrial areas of Odesa, as well as characterize the variability of meteorological values over the Northwest Black Sea. Methods. the data of four-time observations (01, 07, 13, 19 hours) for the main pollutants on the network of eight stationary posts for the February, April, July and October of 2011 are used as the initial materials. The catalog of typical synoptic processes over the territory of Ukraine for the period of 2011-2015 is compiled at the Department of Meteorology and Climatology of the OSENU. To clarify specific synoptic situations, synoptic maps of all levels (ground-level, AT-925, AT-850, AT-700 and AT-500) from the archive of the ARMSin (‘automatic forecaster workstation’- program for processing synoptic maps that is applied in Ukraine. Results. 1. CO concentrations in the city of Odesa increase with distance from the coastal strip in to the depth of land with maximum values in places with high traffic load, regardless of the season; 2. Absence of industrial facilities and meteorological conditions contribute to the low level of air pollution around post N 8. Exceedance of the maximum allowable concentrations of carbon monoxide is observed in 6 out of 8 observation posts; 3. Favorable conditions for the accumulation of admixtures are formed in peripheral processes with low-gradient pressure fields, in front parts of cyclones and in low-motion and small cyclones with the same air mass; 4. Temperature inversions almost always accompanied the accumulation of harmful admixtures in the ground layer of air above Odesa. Scientific novelty and practical significance. In this article we have analyzed influence of meteorological conditions on the level of atmospheric air pollution in Odesa region. For these purposes the more nuanced-based method of forecasting was adapted. We have demonstrated that its use has efficiency at the present time for improvement of operative prognostic units work for the Northwest Black Sea region. Such conclusions may be identified as a result of empirical findings.
Introduction. Nowadays the problem of storm winds appears to be a very relevant one in those spheres of human activities related to safety of human living, coastal infrastructure, seafaring, aviation etc. One of the conditions for successful forecasting of strong winds is familiarization with wind characteristics of the study area and with synoptic conditions causing them. The below listed results of research form continuation of previous works for search of a better synoptic classification reflecting completeness of macroscale baric processes causing formation of winds, including strong winds, over the South of Ukraine and also providing an opportunity to forecast winds in a more accurate manner. The purpose of this publication consists in analysis of interaction of large-scale atmospheric circulation with formation of unfavorable weather conditions (strong and very strong winds) on the north-west coast of the Black Sea. Methods and results. The impact of storm winds is significant for functioning of the national economic complex of the North-Western Black Sea region. In order to investigate this effect there were fifty seven cases of wind amplification up to criterion of strong ≥ 15 m·s-1 and very strong ≥ 25 m·s-1 selected within the Odessa region during the period from October to March in 2011 – 2014. Indexes of Katz circulation for isobaric surface of 500 hPa were calculated as per the data of synoptic archive for the cases with wind speed of ≥ 15 m·s-1. A more detailed study of the structure of macrocirculation processes under strong winds, except for Katz indexes, is provided by means of classification and calendar of successive change of elementary circulation mechanisms (ECM) in the Northern hemisphere according to Dzerdzeyevskyi B.L. and typification of synoptic processes developed at the Department of Theoretical Meteorology and Meteorological Forecasts of OSENU. It was determined that strong and very strong winds often occur in southern and central regions, particularly at the stations located on the shores of seas and estuaries (Bilgorod-Dnistrovskyi, Ust-Dunaysk, Pivdennyi port). Meridional type of atmospheric circulation (77.2%) creates favourable conditions for wind amplification in the North-Western part of the Black Sea up to the criterion of strong and very strong one, zonal type of circulation constitutes 22.8% from the total number of cases. Meridional type of circulation is mainly represented by mixed and western forms – (24.6%) and (22.8%) respectively. Main types of synoptic situations (5, 6) of Katz typification that used to cause strong winds were revealed. Most frequently strong wind was observed while moving of cyclonic vortexes from the South (ECM type – 12a, 13z) and in the area of cyclones and anticyclones interaction. Conclusion. It was found that wind speed amplification in the South of Ukraine up to the criteria of strong and very strong one mainly occurs due to the meridional type of atmospheric circulation which is dominated by mixed or western forms of circulation as per Katz typification, ECM type 12a and 13z according to Dzerdzeyevskyi B.L. and types 5 (subtype 5.2) and 6 (all subtypes depending on ECM) as per synoptic typification of OSENU. Directions for further research should include the following. The conclusions have preliminary character and need confirmation on the basis of bigger scope of statistical data.
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