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1

Trace Element Distribution in the Snow Cover of Different Functional Zones in Berezniki-Solikamsk Industrial Hub, Russia

Ushakova Evgeniya, Menshikova Elena, Karavaeva Tatiana, Puzik Alexey

Journal of Ecological Engineering

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2021

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Vol. 22, nr 10

28--39

EN

The current study considered the distribution of trace elements in snow cover taking into account the functional zoning of the territory of Berezniki-Solikamsk industrial hub, Perm Region, Russia. The concentrations of 22 trace elements were determined in the dissolved phase of snowmelt using ICP-MS method. On the basis of on the background approach, it was found that Ni, Se, Cu, and Sn are actively accumulated in the snow cover. Snowmelt surface runoff during snow melting period significantly contributes to the total watershed discharge of rivers; therefore, the compliance with the Russian fishery quality standards was assessed. It was found that meltwater is the source of Cu, Mn, Se, Zn, V in surface waters. Significant concentrations of Pb, Cd, W, As, Se in snow are characteristic of conditionally background sites in comparison with average values of global concentrations of dissolved trace elements in river waters, and Se, W, Pb, Ni, As, Cd are characteristic of all functional zones. This study presented the possible sources of priority pollutants. The greatest technogenic impact was observed in the area of transport infrastructure development. Upon that, recreational and residential functional zones also experience significant anthropogenic impact. In order to create a comfortable and healthy urban environment it is necessary to implement the measures to restore these areas.

2

Application of hydrochemistry for inrush water source identification in coal mine: approach based on statistical analysis

Sun L.

Mining Science

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2018

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Vol. 25

101--110

EN

The source of chemical constituents in the groundwater and the source of inrush water are two important issues related to the hydrochemical evolution and safety of coal mining in coalfield of China, respectively. In this study, major ion concentrations of thirty-four groundwater samples from three representative aquifers in northern Anhui province, China have been analyzed by a series of statistical methods for tracing the sources of major ions and inrush water. The differences of major ion concentrations in groundwater from different aquifers indicate that they have undergone different types and degrees of water rock interactions, and provide the possibility for water source identification based on major ions. Factor analysis has identified two potential sources responsible for the major ion concentrations of the groundwater, including dissolution of carbonates and evaporates and the weathering of silicate minerals, which was further confirmed by the Unmix model analysis. Discriminant analysis can classify the sources of groundwater with high efficiency, similar to the results obtained based on the source contributions of the Unmix model analysis. In summary, different with those of factor and discriminant analysis, the Unmix model analysis can provide information about source of major ions and water simultaneously.

3

Preliminary PM2.5 and PM10 fractions source apportionment complemented by statistical accuracy determination

Samek L., Stegowski Z., Furman L.

Nukleonika

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2016

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Vol. 61, No. 1

75--83

EN

Samples of PM10 and PM2.5 fractions were collected between the years 2010 and 2013 at the urban area of Krakow, Poland. Numerous types of air pollution sources are present at the site; these include steel and cement industries, traffic, municipal emission sources and biomass burning. Energy dispersive X-ray fluorescence was used to determine the concentrations of the following elements: Cl, K, Ca, Ti, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, As and Pb within the collected samples. Defi ning the elements as indicators, airborne particulate matter (APM) source profiles were prepared by applying principal component analysis (PCA), factor analysis (FA) and multiple linear regression (MLR). Four different factors identifying possible air pollution sources for both PM10 and PM2.5 fractions were attributed to municipal emissions, biomass burning, steel industry, traffic, cement and metal industry, Zn and Pb industry and secondary aerosols. The uncertainty associated with each loading was determined by a statistical simulation method that took into account the individual elemental concentrations and their corresponding uncertainties. It will be possible to identify two or more sources of air particulate matter pollution for a single factor in case it is extremely difficult to separate the sources.

4

Inverse method for a one-stage spur gear diagnosis

Akrout A., Tounsi D., Taktak M., Abbes M. S., Haddar M.

Journal of Theoretical and Applied Mechanics

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2015

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Vol. 53 nr 3

617--628

EN

In this paper, a source separation approach based on the Blind Source Separation (BSS) is presented. In fact, the Independent Component Analysis (ICA), which is the main technique of BSS, consists in extracting different source signals from several observed mixtures. This inverse method is very useful in many fields such as telecommunication, signal processing and biomedicine. It is also very attractive for diagnosis of mechanical systems such as rotating machines. Generally, dynamic responses of a given mechanical system (displacements, accelerations and speeds) measured through sensors are used as inputs for the identification of internal defaults. In this study, the ICA concept is applied to the diagnosis of a one-stage gear mechanism in which two types of defects (the eccentricity error and the localized tooth defect)are introduced. The finite element method allows determination of the signals corresponding to the acceleration in some locations of the system, and those signals may be used also in the ICA algorithm. Hence, the vibratory signatures of each defect can be identified by the ICA concept. Thus, a good agreement is obtained by comparing the expected default signatures to those achieved by the developed inverse method.

5

Spatial Differentiation of Water Quality Between Reservoirs Under Anthropogenic and Natural Factors Based on Statistical Approach

Boyacioglu H.

Archives of Environmental Protection

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2014

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Vol. 40, no. 1

41--50

EN

This study illustrates the benefits of statistical techniques to analyze spatial and temporal variations in water quality. In this scope water quality differentiation caused by anthropogenic and natural factors in the Tahtali and Balçova reservoirs in western Turkey was investigated using discriminant analysis-DA, Mann Whitney U techniques. Effectiveness of pollution prevention measures was analyzed by Mann Kendall and Sen’s Slope estimator methods. The water quality variables were divided into three groups as physical-inorganic, organic and inorganic pollution parameters for the study. Results showed that water quality between reservoirs was differentiated for “physical-inorganic” and “organic pollution” parameters. Degree of influence of water quality by urbanization was higher in the Tahtali reservoir and in general, no trend detection at pollution indicators explained by effective management practices at both sites.

6

Masowy rozkład pierwiastków w próbkach pyłu zawieszonego pobranych w obszarze tła miejskiego: wyniki ośmiomiesięcznych badań w Zabrzu

Rogula-Kozłowska W., Klejnowski K., Rogula-Kopiec P., Błaszczak B., Mathews B., Szopa S.

Rocznik Ochrona Środowiska

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2013

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Tom 15, cz. 2

1022--1040

EN

The analysis of elemental composition of ambient dust can help not only evaluate the environmental and health effects due to the air pollution but also identify emission sources. However, the whole number of projects and studies on concentrations and elemental composition of ambient (especially fine) dust hardly concern these issues in Eastern Europe. Neither is the chemical (and elemental) composition of the submicron ambient dust in Poland well recognized. There is also a shortage of data from long-term and parallel studies of the elemental composition of separate dust fractions. In the heavily polluted areas, the elemental composition of atmospheric aerosol and the dependence of elemental composition of particles on their size can appear essential for analyzing the toxicity of dust and its environmental effects. This study presents the results of determination and comparison of the elemental composition of four fractions of ambient dust in Zabrze (Poland), an urban area typical of the exposure of the Upper-Silesian Agglomeration population to the polluted air. The samples of the four dust fractions (fine: ≤1 µm – PM1, 1–2.5 µm – PM1-2.5, coarse: 2.5–10 µm – PM2.5-10, and 10–40 µm – PM10-40,) were collected during eight months (January–August 2009) with the use of a DEKATI-PM10 cascade impactor. All the dust samples (204 samples) were analyzed using a PANalytical Epsilon 5 spectrometer (EDXRF – energy dispersive X-Ray fluorescence spectroscopy). The minimum, maximum and average concentrations, for winter (January–April, heating season) and summer (May–August, non-heating season), of 38 elements from each of the four examined dust fractions were calculated. The influence of anthropogenic sources on the ambient concentrations of elements from each dust fraction was determined by analyzing the enrichment factors (EF). The strength of linear relationships (Pearson’s linear correlation coefficients) between each pair of elements was determined separately for fine and coarse dust. The highest ambient concentrations were assumed by two nonmetals – sulfur and chlorine; their concentrations were significantly lower in summer than in winter. Both sulfur and chlorine were mainly bound onto the finest particles. Their share in the coarse dust, even in summer, was small. They came from anthropogenic sources. Ambient, typical crustal, Si, Al, Fe, Mg, K, Ca, Ti, Sr, Rb in Zabrze came from natural sources regardless of the fraction they were bound to. Small seasonal variations in ambient concentrations of these elements or some of the concentrations higher in summer than in winter confirmed the fact. A significant portion of the mass of the crustal elements, especially of Al, Si and Fe, was concentrated in the coarse fractions. However, the mass distribution among the dust fractions indicates some of them (K, Ca, Mg, Rb, Sr) as coming partly from anthropogenic sources. It particularly concerns their part bound to fine dust in winter. The mass contribution of crustal matter to ambient dust was about 6.8 in winter and 9.7% in summer; the contribution to PM1 was half of it. Almost all remaining 27 elements (except for Mn, Zn, Ge, Sb, La) had the ambient concentrations not greater than 100 ng m-3, usually higher in winter. The average mass shares of each of these 27 elements in PM1, PM1-2.5, PM2.5-10, and PM10-40, were different and depended on the season of a year. Co, Cu, Zn, Pb and As were cumulated mostly in fine dust, while V, Mn, Co, Cr, Ni, Ag, Cd and Ba in coarse dust. The former, in fine dust, were assumed to be rather of anthropogenic origin and closely associated with combustion. The later originated partly from combustion (especially in winter) but their greater part was secondary and came from road dust. The largest contributors to the mass of the elements in fine dust in Zabrze are domestic furnaces and car engines, i.e. combustion of fossil fuels, biomass, and waste. The possible effect of industrial sources was also identified. The elemental composition of coarse dust is due to re-suspension of soil and road dust, and to a lesser extent, to municipal emission.

7

Solving direct and inverse problems of plate vibration by using the Trefftz functions

Maciąg A., Pawińska A.

Journal of Theoretical and Applied Mechanics

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2013

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Vol. 51 nr 3

543--552

EN

The paper presents an approximate method of solving direct and inverse problems which are described by a non-homogenous plate vibration equation. The key idea of the presented approach is to use solving polynomials that satisfy the considered homogenous differentia equation identically. Inhomogeneity is expanded into the Taylor series and then, for each monomial, the inverse operator is calculated. In the paper, the properties of solving functions are investigated – a theorem concerning their linear independence is formulated and proved. The method of identification of the load (source) is described. It belongs to the group of inverse problems. The paper includes examples which illustrate the usefulness of the method.

8

Sensor network design for the estimation of spatially distributed processes

Uciński D., Patan M.

International Journal of Applied Mathematics and Computer Science

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2010

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Vol. 20, no 3

459-481

EN

In a typical moving contaminating source identification problem, after some type of biological or chemical contamination has occurred, there is a developing cloud of dangerous or toxic material. In order to detect and localize the contamination source, a sensor network can be used. Up to now, however, approaches aiming at guaranteeing a dense region coverage or satisfactory network connectivity have dominated this line of research and abstracted away from the mathematical description of the physical processes underlying the observed phenomena. The present work aims at bridging this gap and meeting the needs created in the context of the source identification problem. We assume that the paths of the moving sources are unknown, but they are sufficiently smooth to be approximated by combinations of given basis functions. This parametrization makes it possible to reduce the source detection and estimation problem to that of parameter identification. In order to estimate the source and medium parameters, the maximum--ikelihood estimator is used. Based on a scalar measure of performance defined on the Fisher information matrix related to the unknown parameters, which is commonly used in optimum experimental design theory, the problem is formulated as an optimal control one. From a practical point of view, it is desirable to have the computations dynamic data driven, i.e., the current measurements from the mobile sensors must serve as a basis for the update of parameter estimates and these, in turn, can be used to correct the sensor movements. In the proposed research, an attempt will also be made at applying a nonlinear model-predictive-control-like approach to attack this issue.

9

Source identification in distributed parameter systems

Skliar M., Ramirez W. F.

Applied Mathematics and Computer Science

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1998

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Vol. 8, no 4

733-754

EN

In this paper, we solve the problem of the pointwise source identification of the convection-diffusion transport processes. This is done by converting the identification problem into an optimization problem of finding a spatial location and the capacity of a point source which results in the best match of model-predicted measurements to actual observed measurements.