Search NASA⌕ Search

SEARCH · Search NASA

Results for “correlation analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

{gamma}-RAY LUMINOSITY FUNCTION AND THE CONTRIBUTION TO EXTRAGALACTIC {gamma}-RAY BACKGROUND FOR FERMI-DETECTED BLAZARS

We study {gamma}-ray luminosity functions (GLFs) and the contribution to the extragalactic diffuse {gamma}-rays for blazars. After using a clean blazar sample in which 485 blazars are observed at both the 8.4 GHz and {approx} GeV bands, we investigate the radio/{gamma}-ray luminosity correlation and find out that a strong correlation exists between the radio and {gamma}-ray luminosities using the partial correlation analysis method. Based on such a correlation, we obtain the GLF, while also considering the GLF based on studies of the X-ray luminosity function of active galactic nuclei and the GLF of the EGRET blazars. K-S tests indicate that these three kinds of GLFs are consistent with the observed data of our sample in a reasonable parameter range. Using these GLFs, we further investigate the blazar contribution to the extragalactic diffuse {gamma}-ray background (EGRB). Our results show that (1) the contribution of blazars are {approx}21.3% {+-} 2.7%, {approx}12.9% {+-} 1.7%, and {approx}37.9% {+-} 4.8% of unresolved Fermi EGRB flux for the three GLFs and (2) the contribution of flat-spectrum radio quasars are {approx}11.2% {+-} 1.6%, {approx}6.9% {+-} 1.0%, and {approx}9.0% {+-} 1.2% of unresolved Fermi EGRB flux for the three GLFs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

What drives galaxy quenching? A deep connection between galaxy kinematics and quenching in the local Universe

ABSTRACT We develop a 2D inclined rotating disc model, which we apply to the stellar velocity maps of 1862 galaxies taken from the MaNGA survey (SDSS public Data Release 15) . We use a random forest classifier to identify the kinematic parameters that are most connected to galaxy quenching. We find that kinematic parameters that relate predominantly to the disc (such as the mean rotational velocity) and parameters that characterize whether a galaxy is rotation- or dispersion-dominated (such as the ratio of rotational velocity to velocity dispersion) are not fundamentally linked to the quenching of star formation. Instead, we find overwhelmingly that it is the absolute level of velocity dispersion (a property that relates primarily to a galaxy’s bulge/spheroidal component) that is most important for separating star-forming and quenched galaxies. Furthermore, a partial correlation analysis shows that many commonly discussed correlations between galaxy properties and quenching are spurious, and that the fundamental correlation is between quenching and velocity dispersion. In particular, we find that at fixed velocity dispersion, there is only a very weak dependence of quenching on the disc properties, whereby more discy galaxies are slightly more likely to be forming stars. By invoking the tight relationship between black hole mass and velocity dispersion, and noting that black hole mass traces the total energy released by active galactic nuclei (AGNs), we argue that these data support a scenario in which quenching occurs by preventive feedback from AGNs. The kinematic measurements from this work are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Detection of significant cm to sub-mm band radio and γ-ray correlated variability in Fermi bright blazars

The exact location of the γ-ray emitting region in blazars is still controversial. In order to attack this problem we present first results of a cross-correlation analysis between radio (11 cm to 0.8 mm wavelength, F-GAMMA programme) and γ-ray (0.1–300 GeV) ~3.5 yr light curves of 54 Fermi-bright blazars. We perform a source stacking analysis and estimate significances and chance correlations using mixed source correlations. These results reveal: (i) the first highly significant multiband radio and γ-ray correlations (radio lagging γ rays) when averaging over the whole sample, (ii) average time delays (source frame: 76 ± 23 to 7 ± 9 d), systematically decreasing from cm to mm/sub-mm bands with a frequency dependence τr, γ(ν) ∝ ν -1 , in good agreement with jet opacity dominated by synchrotron self-absorption, (iii) a bulk γ-ray production region typically located within/upstream of the 3 mm core region (τ3mm, γ = 12 ± 8 d), (iv) mean distances between the region of γ-ray peak emission and the radio ‘τ = 1 photosphere’ decreasing from 9.8 ± 3.0 pc (11 cm) to 0.9 ± 1.1 pc (2 mm) and 1.4 ± 0.8 pc (0.8 mm), (v) 3 mm/γ-ray correlations in nine individual sources at a significance level where one is expected by chance (probability: 4 × 10 -6 ), (vi) opacity and ‘time lag core shift’ estimates for quasar 3C 454.3 providing a lower limit for the distance of the bulk γ-ray production region from the supermassive black hole (SMBH) of ~0.8–1.6 pc, i.e. at the outer edge of the broad-line region (BLR) or beyond. A 3 mm τ = 1 surface at ~2–3 pc from the jet base (i.e. well outside the ‘canonical BLR’) finally suggests that BLR material extends to several parsec distances from the SMBH.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Measurement of the Sensitivity of Two-Particle Correlations in $\mathcal{pp}$ Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the “ridge”—i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities—and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at $\sqrt{s}$=13 TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8 pb -1 , in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v2, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Experimental Analysis of the Effects of Simulator Complexity on Human Performance

Human Reliability Analysis predicts accidents caused by human errors and is an important factor in Probabilistic Safety Assessment that comprehensively evaluates the safety of nuclear power plants. This study compares and analyzes the human performance of nuclear power plant operators according to the simulator complexity as part of the HRA data collection support method development project conducted by Idaho National Laboratory. This experiment was conducted by setting two types of simulators and scenarios as independent variables. The data collected by conducting the experiments in two different simulators were analyzed using an analysis of variance test and a correlation analysis, and four human performance charts were derived.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Human Performance Analysis Depending on Operator Expertise (Student vs. Operator) and Simulator Complexity (Rancor Microworld vs. Compact Nuclear Simulator)

Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

NEW RADIO OBSERVATIONS OF ANOMALOUS MICROWAVE EMISSION IN THE H II REGION RCW175

We have observed the H II region RCW175 with the 64 m Parkes telescope at 8.4 GHz and 13.5 GHz in total intensity, and at 21.5 GHz in both total intensity and polarization. High angular resolution ranging from 1 to 2.4 arcmin, high sensitivity, and polarization capability enable us to perform a detailed study of the different constituents of the H II region. For the first time, we resolve three distinct regions at microwave frequencies, two of which are part of the same annular diffuse structure. Our observations enable us to confirm the presence of anomalous microwave emission (AME) from RCW175. Fitting the integrated flux density across the entire region with the currently available spinning dust models, using physically motivated assumptions, indicates the presence of at least two spinning dust components: a warm component (T {sub gas} = 5800 K) with a relatively large hydrogen number density n {sub H} = 26.3/cm{sup 3} and a cold component (T {sub gas} = 100 K) with a hydrogen number density of n {sub H} = 150/cm{sup 3}. The present study is an example highlighting the potential of using high angular-resolution microwave data to break model parameter degeneracies. Thanks to the spectral coverage and angular resolution of the Parkes observations, we have been able to derive one of the first AME/excess maps, at 13.5 GHz, showing clear evidence that the bulk of the anomalous emission arises in particular from one of the source components, with some additional contribution from the diffuse structure. A cross-correlation analysis with thermal dust emission has shown a high degree of correlation with one of the regions within RCW175. In the center of RCW175, we find an average polarized emission at 21.5 GHz of 2.2 ± 0.2(rand.) ± 0.3(sys.)% of the total emission, where we have included both systematic and statistical uncertainties at 68% CL. This polarized emission could be due to sub-dominant synchrotron emission from the region and is thus consistent with very faint or non-polarized emission associated with AME.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Robust X-ray angular correlations for the study of meso-structures

As self-assembling nanomaterials become more sophisticated, it is becoming increasingly important to measure the structural order of finite-sized assemblies of nano-objects. These mesoscale clusters represent an acute challenge to conventional structural probes, owing to the range of implicated size scales (10 nm to several micrometres), the weak scattering signal and the dynamic nature of meso-clusters in native solution environments. The high X-ray flux and coherence of modern synchrotrons present an opportunity to extract structural information from these challenging systems, but conventional ensemble X-ray scattering averages out crucial information about local particle configurations. Conversely, a single meso-cluster scatters too weakly to recover the full diffraction pattern. Using X-ray angular cross-correlation analysis, it is possible to combine multiple noisy measurements to obtain robust structural information. This paper explores the key theoretical limits and experimental challenges that constrain the application of these methods to probing structural order in real nanomaterials. A metric is presented to quantify the signal-to-noise ratio of angular correlations, and it is used to identify several experimental artifacts that arise. In particular, it is found that background scattering, data masking and inter-cluster interference profoundly affect the quality of correlation analyses. A robust workflow is demonstrated for mitigating these effects and extracting reliable angular correlations from realistic experimental data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites: Observed cloud variability at ARM sites

Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy’s Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness all quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the log normal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Literature Review of Generalized Two-Dimensional Correlation Spectroscopy (2D-COS)

Generalized two-dimensional correlation spectroscopy (2D-COS) is a technique that has improved on traditional spectroscopic techniques by exposing samples to a variable amount of an external perturbation before they have been probed spectroscopically through IR, UV, Raman, etc. These perturbed signals are plotted over a second independent wavenumber axis and after mathematical manipulation, a dynamic spectrum is created that shows the synchronous and asynchronous spectra. The dynamic spectrum shows the way spectral changes in the material are correlated to each other, and a mechanism of material degradation can be proposed through a set of rules that Noda proposed. This technique is important to spectroscopic studies because of improved spectral resolution and the identification of complex or overlapping bands that cannot be distinguished in traditional analytical methods. This technique has been widely utilized since its inception, and has developed towards protein studies, as well as even wine chemistry, because of the advanced capabilities of band separation. Two-dimensional hetero-spectral correlation analysis has also been developed to find correlations in spectra with different spectroscopic probes. 2D-COS as an analytical technique has increasing avenues of expansion, and can be creatively used in many other fields in the future.

2D-COS↗
DOE OSTI2016

An Efficient Sampling-Based Method for Sensitivity and Uncertainty Analysis Through RAVEN

Sensitivity analysis (SA) and uncertainty quantification (UQ) are now widely recognized as essential parts of analyses for complex nuclear systems. Plenty of well-established methodologies are already available for performing SA and UQ, such as Monte Carlo analysis, adjoint-based method, and variance decomposition. The focus of this summary is on developing an efficient sampling-based approach to perform SA and UQ through RAVEN. RAVEN (Risk Analysis and Virtual control Environment) is a software framework able to perform SA and UQ, currently under development at the Idaho National Laboratory. In literature, a number of approaches have been developed to accelerate the process of SA and UQ for large complex systems, such as principal component analysis (PCA) of input space, input-output correlation analysis, and intersection subspace methods. The fundamental idea is to identify the dominant active directions in the parameter space prior to conducting SA and UQ. The premise is that the number of active directions is much less than the dimensionality of input space. In this work, the PCA or Karhunen-Loeve expansion or SVD method is implemented in RAVEN to identify the active directions. This approach is also combined with the forward sampling approaches, such as Monte Carlo, Grid, Latin Hypercube, and Response Surface Design sampling approaches that are currently available in RAVEN, to perform SA and UQ more efficiently. The summary is organized as follows. In the following section, we present the PCA-based forward sampling approach. The effectiveness and efficiency are discussed in the numerical results section. The paper then ends with a concluding summary. In this summary, we have presented PCA-based forward sampling approach to perform SA and UQ. The goal is to reduce the computational overhead for repetitive executions of complex nuclear systems that are generally required when performing SA and UQ. The control of correlations between input parameters is implemented in RAVEN to better represent the input relationships. In addition, we are currently examining our implementations with more realistic models, and we are also focusing on implementation of some new high-dimensional input reduction techniques in RAVEN. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Quantification of Prediction Bounds Caused by Model Form Uncertainty

Numerical simulations, irrespective of the discipline or application, are often plagued by arbitrary numerical and modeling choices. Arbitrary choices can originate from kinematic assumptions, for example the use of 1D beam, 2D shell, or 3D continuum elements, mesh discretization choices, boundary condition models, and the representation of contact and friction in the simulation. This works takes a step toward understanding the effect of arbitrary choices and model-form assumptions on the accuracy of numerical predictions. The application is the simulation of the first four resonant frequencies of a one-story aluminum portal frame structure under free-free boundary conditions. The main challenge of the portal frame structure resides in modeling joint connections, for which different modeling assumptions are available. To study this model-form uncertainty, and compare it to other types of uncertainty, two finite element models are developed using solid elements, and with differing representations of the beam-to-column and column-to-base plate connections using: (i) contact stiffness, and (ii) tied nodes. Test-analysis correlation is performed by comparing the range of numerical predictions obtained from parametric studies of the joint modeling strategies to the range of experimentally obtained natural frequencies. The approach proposed is, first, to characterize the experimental variability of the joints by varying the bolt torque, method of bolt tightening, and the sequence in which the bolts are tightened. The second step is to convert what is learned from these experimental studies to models that bound the range of observed bolt behavior. We show that this approach, that combines small-scale experiments, sensitivity analysis studies, and bounding-case models, successfully produces bounds of numerical predictions that match those measured experimentally on the frame structure.

42 ENGINEERING↗
DOE OSTI2012

A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Cell-Edge Detection via Selective Cooperation and Generalized Canonical Correlation

Improving the uplink quality of service for users located around the boundaries between cells is a key challenge in cellular systems. Existing approaches relying on power control throttle the rates of cell-center users, while multi-user detection requires accurate channel estimates for the cell-edge users, which is another challenge due to their low received signal-to-noise ratio (SNR). Utilizing the fact that cell-edge user signals are weak but common (received at roughly equal power) at different base stations (BSs), this paper establishes a connection between cell-edge user detection and generalized canonical correlation analysis (GCCA). It puts forth a GCCA-based method that leverages selective BS cooperation to recover the cell-edge user signal subspace even at low SNR. The cell-edge user signals can then be extracted from the resulting mixture via algebraic signal processing techniques. The paper includes theoretical analysis showing why GCCA recovers the correct subspace containing the cell-edge user signals under mild conditions. The proposed method can also identify the number of cell-edge users in the system, i.e., the common subspace dimension. Simulations reveal significant performance improvement relative to various multiuser detection techniques. Cell-edge detection performance is further studied as a function of how many / which BSs are selected, and it is shown that using the closest three BS is always the best choice.

base station cooperation↗
DOE OSTI2025

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Recent advancements in molecular Mass Spectrometry Imaging have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization, and time-of-flight secondary ion mass spectrometry imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

canonical correlation analysis↗
DOE OSTI2017

An overlooked nitrogen loss linked to anaerobic ammonium oxidation in estuarine sediments in China

Despite its importance, anammox (anaerobic ammonium oxidation) in estuarine sediment systems remains poorly understood, particularly at the continental scale. This study aimed to understand the abundance, diversity, and activity of anammox bacteria and to determine the main factors influencing the anammox process in estuarine sediments in China. Materials and methods Estuarine sediments were collected from 18 estuaries spanning over 4000 km. Experiments using an (15)Ntracer, quantitative PCR, and clone library construction were used to determine the activity, abundance, and diversity of anammox bacteria. The impact of environmental factors on anammox processes was also determined. Results and discussion The abundance of the anammox-specific hydrazine synthase (hzsB) gene ranged from 1.8 x 105 +/- 3.4 x 104 to 3.6 x 108 +/- 7.5 x 107 copies g(-1) dw. Candidatus Scalindua, Brocadia, Kuenenia, Jettenia, and two novel unidentified clusters were detected, with Scalindua dominating the anammox population. Additionally, the abundances of Scalindua, Kuenenia, and Brocadia were found to be significantly correlated with latitude. The anammox rates ranged from 0.29 +/- 0.15 to 13.68 +/- 3.98 nmol N g(-1) dw h(-1) and contributed to 2.39-82.61% of total N-2 production. Pearson correlation analysis revealed that the anammox rate was positively correlated with total nitrogen, total carbon, and temperature, and was negatively correlated with dissolved oxygen (DO). The key factors influencing the hzsB gene abundance were ammonium concentration, salinity, and DO. Ammonium concentration, pH, temperature, and latitude were main variables shaping the anammox-associated bacterial community. Conclusions Our results suggested that anammox bacteria are ubiquitous in coastal estuaries in China and underline the importance of anammox resulting in N loss at a continental scale.

activity↗
DOE OSTI2018

Copper and zinc levels in soil, water, wheat, and hair of inhabitants of three areas of the Orenburg region, Russia

Highlights: • Soil, water, wheat and hair levels of Zn and Cu in Orenburg region were studied. • Both Zn and Cu levels in the samples were higher in the eastern area. • Higher levels of Zn and Cu in the eastern area may occur due to industrial activities. • Water Zn levels were associated with hair Zn levels. The objective of the present study was to assess the level of zinc and copper in soil, water, wheat and hair of inhabitants of the western, central, and eastern areas of the Orenburg region. A total of 525 water, soil, and wheat samples, as well as 420 hair samples were assessed using atomic absorption spectrometry (water, soil, wheat) and inductively-coupled plasma mass spectrometry (hair). The highest levels of Zn and Cu in water (4.9(4.2–5.1) and 1.0(0.9–1.1) mg/l), soil (23.8(20.7–27.0) and 2.6(1.9–3.1) mg/kg), and wheat (24.7(20.5–31.0) and 4.8(4.2–5.5) mg/kg) were observed in the eastern area (p < 0.001). Hair zinc levels in inhabitants of the western (184(165–198) µg/g) and eastern (224(211–253) µg/g) areas of the region exceeded the respective values from the central area by 32% and 61% (p < 0.001). In turn, hair Cu levels in the central (16.4(14.3–17.8) µg/g) and eastern (17.9(16.4–19.0) µg/g) areas exceeded the values from the western area by 10% and 20%, respectively. Correlation analysis demonstrated that hair Zn levels were positively correlated with water and soil content, whereas wheat Zn levels were associated with soil and water content. For copper significant direct correlation was observed only between soil and water Cu content. In multiple regression models, only water zinc level was significantly associated with hair Zn content, although the general model accounted for 55% of variability of hair Zn content. Higher zinc and copper exposure in the eastern area is presumably associated with higher activity of metal-processing industry.

54 ENVIRONMENTAL SCIENCES↗